Returns the operations Resource.
Close httplib2 connections.
create(parent, body=None, x__xgafv=None)
Creates a Schedule.
Deletes a Schedule.
Gets a Schedule.
list(parent, filter=None, orderBy=None, pageSize=None, pageToken=None, x__xgafv=None)
Lists Schedules in a Location.
Retrieves the next page of results.
patch(name, body=None, updateMask=None, x__xgafv=None)
Updates an active or paused Schedule. When the Schedule is updated, new runs will be scheduled starting from the updated next execution time after the update time based on the time_specification in the updated Schedule. All unstarted runs before the update time will be skipped while already created runs will NOT be paused or canceled.
pause(name, body=None, x__xgafv=None)
Pauses a Schedule. Will mark Schedule.state to 'PAUSED'. If the schedule is paused, no new runs will be created. Already created runs will NOT be paused or canceled.
resume(name, body=None, x__xgafv=None)
Resumes a paused Schedule to start scheduling new runs. Will mark Schedule.state to 'ACTIVE'. Only paused Schedule can be resumed. When the Schedule is resumed, new runs will be scheduled starting from the next execution time after the current time based on the time_specification in the Schedule. If Schedule.catchUp is set up true, all missed runs will be scheduled for backfill first.
close()
Close httplib2 connections.
create(parent, body=None, x__xgafv=None)
Creates a Schedule.
Args:
parent: string, Required. The resource name of the Location to create the Schedule in. Format: `projects/{project}/locations/{location}` (required)
body: object, The request body.
The object takes the form of:
{ # An instance of a Schedule periodically schedules runs to make API calls based on user specified time specification and API request type.
"allowQueueing": True or False, # Optional. Whether new scheduled runs can be queued when max_concurrent_runs limit is reached. If set to true, new runs will be queued instead of skipped. Default to false.
"catchUp": True or False, # Output only. Whether to backfill missed runs when the schedule is resumed from PAUSED state. If set to true, all missed runs will be scheduled. New runs will be scheduled after the backfill is complete. Default to false.
"createNotebookExecutionJobRequest": { # Request message for [NotebookService.CreateNotebookExecutionJob] # Request for NotebookService.CreateNotebookExecutionJob.
"notebookExecutionJob": { # NotebookExecutionJob represents an instance of a notebook execution. # Required. The NotebookExecutionJob to create.
"createTime": "A String", # Output only. Timestamp when this NotebookExecutionJob was created.
"customEnvironmentSpec": { # Compute configuration to use for an execution job. # The custom compute configuration for an execution job.
"machineSpec": { # Specification of a single machine. # The specification of a single machine for the execution job.
"acceleratorCount": 42, # The number of accelerators to attach to the machine.
"acceleratorType": "A String", # Immutable. The type of accelerator(s) that may be attached to the machine as per accelerator_count.
"machineType": "A String", # Immutable. The type of the machine. See the [list of machine types supported for prediction](https://cloud.google.com/vertex-ai/docs/predictions/configure-compute#machine-types) See the [list of machine types supported for custom training](https://cloud.google.com/vertex-ai/docs/training/configure-compute#machine-types). For DeployedModel this field is optional, and the default value is `n1-standard-2`. For BatchPredictionJob or as part of WorkerPoolSpec this field is required.
"reservationAffinity": { # A ReservationAffinity can be used to configure a Vertex AI resource (e.g., a DeployedModel) to draw its Compute Engine resources from a Shared Reservation, or exclusively from on-demand capacity. # Optional. Immutable. Configuration controlling how this resource pool consumes reservation.
"key": "A String", # Optional. Corresponds to the label key of a reservation resource. To target a SPECIFIC_RESERVATION by name, use `compute.googleapis.com/reservation-name` as the key and specify the name of your reservation as its value.
"reservationAffinityType": "A String", # Required. Specifies the reservation affinity type.
"values": [ # Optional. Corresponds to the label values of a reservation resource. This must be the full resource name of the reservation.
"A String",
],
},
"tpuTopology": "A String", # Immutable. The topology of the TPUs. Corresponds to the TPU topologies available from GKE. (Example: tpu_topology: "2x2x1").
},
"networkSpec": { # Network spec. # The network configuration to use for the execution job.
"enableInternetAccess": True or False, # Whether to enable public internet access. Default false.
"network": "A String", # The full name of the Google Compute Engine [network](https://cloud.google.com//compute/docs/networks-and-firewalls#networks)
"subnetwork": "A String", # The name of the subnet that this instance is in. Format: `projects/{project_id_or_number}/regions/{region}/subnetworks/{subnetwork_id}`
},
"persistentDiskSpec": { # Represents the spec of persistent disk options. # The specification of a persistent disk to attach for the execution job.
"diskSizeGb": "A String", # Size in GB of the disk (default is 100GB).
"diskType": "A String", # Type of the disk (default is "pd-standard"). Valid values: "pd-ssd" (Persistent Disk Solid State Drive) "pd-standard" (Persistent Disk Hard Disk Drive) "pd-balanced" (Balanced Persistent Disk) "pd-extreme" (Extreme Persistent Disk)
},
},
"dataformRepositorySource": { # The Dataform Repository containing the input notebook. # The Dataform Repository pointing to a single file notebook repository.
"commitSha": "A String", # The commit SHA to read repository with. If unset, the file will be read at HEAD.
"dataformRepositoryResourceName": "A String", # The resource name of the Dataform Repository. Format: `projects/{project_id}/locations/{location}/repositories/{repository_id}`
},
"directNotebookSource": { # The content of the input notebook in ipynb format. # The contents of an input notebook file.
"content": "A String", # The base64-encoded contents of the input notebook file.
},
"displayName": "A String", # The display name of the NotebookExecutionJob. The name can be up to 128 characters long and can consist of any UTF-8 characters.
"encryptionSpec": { # Represents a customer-managed encryption key spec that can be applied to a top-level resource. # Customer-managed encryption key spec for the notebook execution job. This field is auto-populated if the NotebookService.NotebookRuntimeTemplate has an encryption spec.
"kmsKeyName": "A String", # Required. The Cloud KMS resource identifier of the customer managed encryption key used to protect a resource. Has the form: `projects/my-project/locations/my-region/keyRings/my-kr/cryptoKeys/my-key`. The key needs to be in the same region as where the compute resource is created.
},
"executionTimeout": "A String", # Max running time of the execution job in seconds (default 86400s / 24 hrs).
"executionUser": "A String", # The user email to run the execution as. Only supported by Colab runtimes.
"gcsNotebookSource": { # The Cloud Storage uri for the input notebook. # The Cloud Storage url pointing to the ipynb file. Format: `gs://bucket/notebook_file.ipynb`
"generation": "A String", # The version of the Cloud Storage object to read. If unset, the current version of the object is read. See https://cloud.google.com/storage/docs/metadata#generation-number.
"uri": "A String", # The Cloud Storage uri pointing to the ipynb file. Format: `gs://bucket/notebook_file.ipynb`
},
"gcsOutputUri": "A String", # The Cloud Storage location to upload the result to. Format: `gs://bucket-name`
"jobState": "A String", # Output only. The state of the NotebookExecutionJob.
"labels": { # The labels with user-defined metadata to organize NotebookExecutionJobs. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable.
"a_key": "A String",
},
"name": "A String", # Output only. The resource name of this NotebookExecutionJob. Format: `projects/{project_id}/locations/{location}/notebookExecutionJobs/{job_id}`
"notebookRuntimeTemplateResourceName": "A String", # The NotebookRuntimeTemplate to source compute configuration from.
"scheduleResourceName": "A String", # Output only. The Schedule resource name if this job is triggered by one. Format: `projects/{project_id}/locations/{location}/schedules/{schedule_id}`
"serviceAccount": "A String", # The service account to run the execution as.
"status": { # The `Status` type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by [gRPC](https://github.com/grpc). Each `Status` message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the [API Design Guide](https://cloud.google.com/apis/design/errors). # Output only. Populated when the NotebookExecutionJob is completed. When there is an error during notebook execution, the error details are populated.
"code": 42, # The status code, which should be an enum value of google.rpc.Code.
"details": [ # A list of messages that carry the error details. There is a common set of message types for APIs to use.
{
"a_key": "", # Properties of the object. Contains field @type with type URL.
},
],
"message": "A String", # A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.
},
"updateTime": "A String", # Output only. Timestamp when this NotebookExecutionJob was most recently updated.
},
"notebookExecutionJobId": "A String", # Optional. User specified ID for the NotebookExecutionJob.
"parent": "A String", # Required. The resource name of the Location to create the NotebookExecutionJob. Format: `projects/{project}/locations/{location}`
},
"createPipelineJobRequest": { # Request message for PipelineService.CreatePipelineJob. # Request for PipelineService.CreatePipelineJob. CreatePipelineJobRequest.parent field is required (format: projects/{project}/locations/{location}).
"parent": "A String", # Required. The resource name of the Location to create the PipelineJob in. Format: `projects/{project}/locations/{location}`
"pipelineJob": { # An instance of a machine learning PipelineJob. # Required. The PipelineJob to create.
"createTime": "A String", # Output only. Pipeline creation time.
"displayName": "A String", # The display name of the Pipeline. The name can be up to 128 characters long and can consist of any UTF-8 characters.
"encryptionSpec": { # Represents a customer-managed encryption key spec that can be applied to a top-level resource. # Customer-managed encryption key spec for a pipelineJob. If set, this PipelineJob and all of its sub-resources will be secured by this key.
"kmsKeyName": "A String", # Required. The Cloud KMS resource identifier of the customer managed encryption key used to protect a resource. Has the form: `projects/my-project/locations/my-region/keyRings/my-kr/cryptoKeys/my-key`. The key needs to be in the same region as where the compute resource is created.
},
"endTime": "A String", # Output only. Pipeline end time.
"error": { # The `Status` type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by [gRPC](https://github.com/grpc). Each `Status` message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the [API Design Guide](https://cloud.google.com/apis/design/errors). # Output only. The error that occurred during pipeline execution. Only populated when the pipeline's state is FAILED or CANCELLED.
"code": 42, # The status code, which should be an enum value of google.rpc.Code.
"details": [ # A list of messages that carry the error details. There is a common set of message types for APIs to use.
{
"a_key": "", # Properties of the object. Contains field @type with type URL.
},
],
"message": "A String", # A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.
},
"jobDetail": { # The runtime detail of PipelineJob. # Output only. The details of pipeline run. Not available in the list view.
"pipelineContext": { # Instance of a general context. # Output only. The context of the pipeline.
"createTime": "A String", # Output only. Timestamp when this Context was created.
"description": "A String", # Description of the Context
"displayName": "A String", # User provided display name of the Context. May be up to 128 Unicode characters.
"etag": "A String", # An eTag used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
"labels": { # The labels with user-defined metadata to organize your Contexts. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one Context (System labels are excluded).
"a_key": "A String",
},
"metadata": { # Properties of the Context. Top level metadata keys' heading and trailing spaces will be trimmed. The size of this field should not exceed 200KB.
"a_key": "", # Properties of the object.
},
"name": "A String", # Immutable. The resource name of the Context.
"parentContexts": [ # Output only. A list of resource names of Contexts that are parents of this Context. A Context may have at most 10 parent_contexts.
"A String",
],
"schemaTitle": "A String", # The title of the schema describing the metadata. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.
"schemaVersion": "A String", # The version of the schema in schema_name to use. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.
"updateTime": "A String", # Output only. Timestamp when this Context was last updated.
},
"pipelineRunContext": { # Instance of a general context. # Output only. The context of the current pipeline run.
"createTime": "A String", # Output only. Timestamp when this Context was created.
"description": "A String", # Description of the Context
"displayName": "A String", # User provided display name of the Context. May be up to 128 Unicode characters.
"etag": "A String", # An eTag used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
"labels": { # The labels with user-defined metadata to organize your Contexts. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one Context (System labels are excluded).
"a_key": "A String",
},
"metadata": { # Properties of the Context. Top level metadata keys' heading and trailing spaces will be trimmed. The size of this field should not exceed 200KB.
"a_key": "", # Properties of the object.
},
"name": "A String", # Immutable. The resource name of the Context.
"parentContexts": [ # Output only. A list of resource names of Contexts that are parents of this Context. A Context may have at most 10 parent_contexts.
"A String",
],
"schemaTitle": "A String", # The title of the schema describing the metadata. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.
"schemaVersion": "A String", # The version of the schema in schema_name to use. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.
"updateTime": "A String", # Output only. Timestamp when this Context was last updated.
},
"taskDetails": [ # Output only. The runtime details of the tasks under the pipeline.
{ # The runtime detail of a task execution.
"createTime": "A String", # Output only. Task create time.
"endTime": "A String", # Output only. Task end time.
"error": { # The `Status` type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by [gRPC](https://github.com/grpc). Each `Status` message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the [API Design Guide](https://cloud.google.com/apis/design/errors). # Output only. The error that occurred during task execution. Only populated when the task's state is FAILED or CANCELLED.
"code": 42, # The status code, which should be an enum value of google.rpc.Code.
"details": [ # A list of messages that carry the error details. There is a common set of message types for APIs to use.
{
"a_key": "", # Properties of the object. Contains field @type with type URL.
},
],
"message": "A String", # A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.
},
"execution": { # Instance of a general execution. # Output only. The execution metadata of the task.
"createTime": "A String", # Output only. Timestamp when this Execution was created.
"description": "A String", # Description of the Execution
"displayName": "A String", # User provided display name of the Execution. May be up to 128 Unicode characters.
"etag": "A String", # An eTag used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
"labels": { # The labels with user-defined metadata to organize your Executions. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one Execution (System labels are excluded).
"a_key": "A String",
},
"metadata": { # Properties of the Execution. Top level metadata keys' heading and trailing spaces will be trimmed. The size of this field should not exceed 200KB.
"a_key": "", # Properties of the object.
},
"name": "A String", # Output only. The resource name of the Execution.
"schemaTitle": "A String", # The title of the schema describing the metadata. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.
"schemaVersion": "A String", # The version of the schema in `schema_title` to use. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.
"state": "A String", # The state of this Execution. This is a property of the Execution, and does not imply or capture any ongoing process. This property is managed by clients (such as Vertex AI Pipelines) and the system does not prescribe or check the validity of state transitions.
"updateTime": "A String", # Output only. Timestamp when this Execution was last updated.
},
"executorDetail": { # The runtime detail of a pipeline executor. # Output only. The detailed execution info.
"containerDetail": { # The detail of a container execution. It contains the job names of the lifecycle of a container execution. # Output only. The detailed info for a container executor.
"failedMainJobs": [ # Output only. The names of the previously failed CustomJob for the main container executions. The list includes the all attempts in chronological order.
"A String",
],
"failedPreCachingCheckJobs": [ # Output only. The names of the previously failed CustomJob for the pre-caching-check container executions. This job will be available if the PipelineJob.pipeline_spec specifies the `pre_caching_check` hook in the lifecycle events. The list includes the all attempts in chronological order.
"A String",
],
"mainJob": "A String", # Output only. The name of the CustomJob for the main container execution.
"preCachingCheckJob": "A String", # Output only. The name of the CustomJob for the pre-caching-check container execution. This job will be available if the PipelineJob.pipeline_spec specifies the `pre_caching_check` hook in the lifecycle events.
},
"customJobDetail": { # The detailed info for a custom job executor. # Output only. The detailed info for a custom job executor.
"failedJobs": [ # Output only. The names of the previously failed CustomJob. The list includes the all attempts in chronological order.
"A String",
],
"job": "A String", # Output only. The name of the CustomJob.
},
},
"inputs": { # Output only. The runtime input artifacts of the task.
"a_key": { # A list of artifact metadata.
"artifacts": [ # Output only. A list of artifact metadata.
{ # Instance of a general artifact.
"createTime": "A String", # Output only. Timestamp when this Artifact was created.
"description": "A String", # Description of the Artifact
"displayName": "A String", # User provided display name of the Artifact. May be up to 128 Unicode characters.
"etag": "A String", # An eTag used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
"labels": { # The labels with user-defined metadata to organize your Artifacts. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one Artifact (System labels are excluded).
"a_key": "A String",
},
"metadata": { # Properties of the Artifact. Top level metadata keys' heading and trailing spaces will be trimmed. The size of this field should not exceed 200KB.
"a_key": "", # Properties of the object.
},
"name": "A String", # Output only. The resource name of the Artifact.
"schemaTitle": "A String", # The title of the schema describing the metadata. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.
"schemaVersion": "A String", # The version of the schema in schema_name to use. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.
"state": "A String", # The state of this Artifact. This is a property of the Artifact, and does not imply or capture any ongoing process. This property is managed by clients (such as Vertex AI Pipelines), and the system does not prescribe or check the validity of state transitions.
"updateTime": "A String", # Output only. Timestamp when this Artifact was last updated.
"uri": "A String", # The uniform resource identifier of the artifact file. May be empty if there is no actual artifact file.
},
],
},
},
"outputs": { # Output only. The runtime output artifacts of the task.
"a_key": { # A list of artifact metadata.
"artifacts": [ # Output only. A list of artifact metadata.
{ # Instance of a general artifact.
"createTime": "A String", # Output only. Timestamp when this Artifact was created.
"description": "A String", # Description of the Artifact
"displayName": "A String", # User provided display name of the Artifact. May be up to 128 Unicode characters.
"etag": "A String", # An eTag used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
"labels": { # The labels with user-defined metadata to organize your Artifacts. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one Artifact (System labels are excluded).
"a_key": "A String",
},
"metadata": { # Properties of the Artifact. Top level metadata keys' heading and trailing spaces will be trimmed. The size of this field should not exceed 200KB.
"a_key": "", # Properties of the object.
},
"name": "A String", # Output only. The resource name of the Artifact.
"schemaTitle": "A String", # The title of the schema describing the metadata. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.
"schemaVersion": "A String", # The version of the schema in schema_name to use. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.
"state": "A String", # The state of this Artifact. This is a property of the Artifact, and does not imply or capture any ongoing process. This property is managed by clients (such as Vertex AI Pipelines), and the system does not prescribe or check the validity of state transitions.
"updateTime": "A String", # Output only. Timestamp when this Artifact was last updated.
"uri": "A String", # The uniform resource identifier of the artifact file. May be empty if there is no actual artifact file.
},
],
},
},
"parentTaskId": "A String", # Output only. The id of the parent task if the task is within a component scope. Empty if the task is at the root level.
"pipelineTaskStatus": [ # Output only. A list of task status. This field keeps a record of task status evolving over time.
{ # A single record of the task status.
"error": { # The `Status` type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by [gRPC](https://github.com/grpc). Each `Status` message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the [API Design Guide](https://cloud.google.com/apis/design/errors). # Output only. The error that occurred during the state. May be set when the state is any of the non-final state (PENDING/RUNNING/CANCELLING) or FAILED state. If the state is FAILED, the error here is final and not going to be retried. If the state is a non-final state, the error indicates a system-error being retried.
"code": 42, # The status code, which should be an enum value of google.rpc.Code.
"details": [ # A list of messages that carry the error details. There is a common set of message types for APIs to use.
{
"a_key": "", # Properties of the object. Contains field @type with type URL.
},
],
"message": "A String", # A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.
},
"state": "A String", # Output only. The state of the task.
"updateTime": "A String", # Output only. Update time of this status.
},
],
"startTime": "A String", # Output only. Task start time.
"state": "A String", # Output only. State of the task.
"taskId": "A String", # Output only. The system generated ID of the task.
"taskName": "A String", # Output only. The user specified name of the task that is defined in pipeline_spec.
},
],
},
"labels": { # The labels with user-defined metadata to organize PipelineJob. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels. Note there is some reserved label key for Vertex AI Pipelines. - `vertex-ai-pipelines-run-billing-id`, user set value will get overrided.
"a_key": "A String",
},
"name": "A String", # Output only. The resource name of the PipelineJob.
"network": "A String", # The full name of the Compute Engine [network](/compute/docs/networks-and-firewalls#networks) to which the Pipeline Job's workload should be peered. For example, `projects/12345/global/networks/myVPC`. [Format](/compute/docs/reference/rest/v1/networks/insert) is of the form `projects/{project}/global/networks/{network}`. Where {project} is a project number, as in `12345`, and {network} is a network name. Private services access must already be configured for the network. Pipeline job will apply the network configuration to the Google Cloud resources being launched, if applied, such as Vertex AI Training or Dataflow job. If left unspecified, the workload is not peered with any network.
"pipelineSpec": { # The spec of the pipeline.
"a_key": "", # Properties of the object.
},
"preflightValidations": True or False, # Optional. Whether to do component level validations before job creation.
"reservedIpRanges": [ # A list of names for the reserved ip ranges under the VPC network that can be used for this Pipeline Job's workload. If set, we will deploy the Pipeline Job's workload within the provided ip ranges. Otherwise, the job will be deployed to any ip ranges under the provided VPC network. Example: ['vertex-ai-ip-range'].
"A String",
],
"runtimeConfig": { # The runtime config of a PipelineJob. # Runtime config of the pipeline.
"failurePolicy": "A String", # Represents the failure policy of a pipeline. Currently, the default of a pipeline is that the pipeline will continue to run until no more tasks can be executed, also known as PIPELINE_FAILURE_POLICY_FAIL_SLOW. However, if a pipeline is set to PIPELINE_FAILURE_POLICY_FAIL_FAST, it will stop scheduling any new tasks when a task has failed. Any scheduled tasks will continue to completion.
"gcsOutputDirectory": "A String", # Required. A path in a Cloud Storage bucket, which will be treated as the root output directory of the pipeline. It is used by the system to generate the paths of output artifacts. The artifact paths are generated with a sub-path pattern `{job_id}/{task_id}/{output_key}` under the specified output directory. The service account specified in this pipeline must have the `storage.objects.get` and `storage.objects.create` permissions for this bucket.
"inputArtifacts": { # The runtime artifacts of the PipelineJob. The key will be the input artifact name and the value would be one of the InputArtifact.
"a_key": { # The type of an input artifact.
"artifactId": "A String", # Artifact resource id from MLMD. Which is the last portion of an artifact resource name: `projects/{project}/locations/{location}/metadataStores/default/artifacts/{artifact_id}`. The artifact must stay within the same project, location and default metadatastore as the pipeline.
},
},
"parameterValues": { # The runtime parameters of the PipelineJob. The parameters will be passed into PipelineJob.pipeline_spec to replace the placeholders at runtime. This field is used by pipelines built using `PipelineJob.pipeline_spec.schema_version` 2.1.0, such as pipelines built using Kubeflow Pipelines SDK 1.9 or higher and the v2 DSL.
"a_key": "",
},
"parameters": { # Deprecated. Use RuntimeConfig.parameter_values instead. The runtime parameters of the PipelineJob. The parameters will be passed into PipelineJob.pipeline_spec to replace the placeholders at runtime. This field is used by pipelines built using `PipelineJob.pipeline_spec.schema_version` 2.0.0 or lower, such as pipelines built using Kubeflow Pipelines SDK 1.8 or lower.
"a_key": { # Value is the value of the field.
"doubleValue": 3.14, # A double value.
"intValue": "A String", # An integer value.
"stringValue": "A String", # A string value.
},
},
},
"scheduleName": "A String", # Output only. The schedule resource name. Only returned if the Pipeline is created by Schedule API.
"serviceAccount": "A String", # The service account that the pipeline workload runs as. If not specified, the Compute Engine default service account in the project will be used. See https://cloud.google.com/compute/docs/access/service-accounts#default_service_account Users starting the pipeline must have the `iam.serviceAccounts.actAs` permission on this service account.
"startTime": "A String", # Output only. Pipeline start time.
"state": "A String", # Output only. The detailed state of the job.
"templateMetadata": { # Pipeline template metadata if PipelineJob.template_uri is from supported template registry. Currently, the only supported registry is Artifact Registry. # Output only. Pipeline template metadata. Will fill up fields if PipelineJob.template_uri is from supported template registry.
"version": "A String", # The version_name in artifact registry. Will always be presented in output if the PipelineJob.template_uri is from supported template registry. Format is "sha256:abcdef123456...".
},
"templateUri": "A String", # A template uri from where the PipelineJob.pipeline_spec, if empty, will be downloaded. Currently, only uri from Vertex Template Registry & Gallery is supported. Reference to https://cloud.google.com/vertex-ai/docs/pipelines/create-pipeline-template.
"updateTime": "A String", # Output only. Timestamp when this PipelineJob was most recently updated.
},
"pipelineJobId": "A String", # The ID to use for the PipelineJob, which will become the final component of the PipelineJob name. If not provided, an ID will be automatically generated. This value should be less than 128 characters, and valid characters are `/a-z-/`.
},
"createTime": "A String", # Output only. Timestamp when this Schedule was created.
"cron": "A String", # Cron schedule (https://en.wikipedia.org/wiki/Cron) to launch scheduled runs. To explicitly set a timezone to the cron tab, apply a prefix in the cron tab: "CRON_TZ=${IANA_TIME_ZONE}" or "TZ=${IANA_TIME_ZONE}". The ${IANA_TIME_ZONE} may only be a valid string from IANA time zone database. For example, "CRON_TZ=America/New_York 1 * * * *", or "TZ=America/New_York 1 * * * *".
"displayName": "A String", # Required. User provided name of the Schedule. The name can be up to 128 characters long and can consist of any UTF-8 characters.
"endTime": "A String", # Optional. Timestamp after which no new runs can be scheduled. If specified, The schedule will be completed when either end_time is reached or when scheduled_run_count >= max_run_count. If not specified, new runs will keep getting scheduled until this Schedule is paused or deleted. Already scheduled runs will be allowed to complete. Unset if not specified.
"lastPauseTime": "A String", # Output only. Timestamp when this Schedule was last paused. Unset if never paused.
"lastResumeTime": "A String", # Output only. Timestamp when this Schedule was last resumed. Unset if never resumed from pause.
"lastScheduledRunResponse": { # Status of a scheduled run. # Output only. Response of the last scheduled run. This is the response for starting the scheduled requests and not the execution of the operations/jobs created by the requests (if applicable). Unset if no run has been scheduled yet.
"runResponse": "A String", # The response of the scheduled run.
"scheduledRunTime": "A String", # The scheduled run time based on the user-specified schedule.
},
"maxConcurrentRunCount": "A String", # Required. Maximum number of runs that can be started concurrently for this Schedule. This is the limit for starting the scheduled requests and not the execution of the operations/jobs created by the requests (if applicable).
"maxRunCount": "A String", # Optional. Maximum run count of the schedule. If specified, The schedule will be completed when either started_run_count >= max_run_count or when end_time is reached. If not specified, new runs will keep getting scheduled until this Schedule is paused or deleted. Already scheduled runs will be allowed to complete. Unset if not specified.
"name": "A String", # Immutable. The resource name of the Schedule.
"nextRunTime": "A String", # Output only. Timestamp when this Schedule should schedule the next run. Having a next_run_time in the past means the runs are being started behind schedule.
"startTime": "A String", # Optional. Timestamp after which the first run can be scheduled. Default to Schedule create time if not specified.
"startedRunCount": "A String", # Output only. The number of runs started by this schedule.
"state": "A String", # Output only. The state of this Schedule.
"updateTime": "A String", # Output only. Timestamp when this Schedule was updated.
}
x__xgafv: string, V1 error format.
Allowed values
1 - v1 error format
2 - v2 error format
Returns:
An object of the form:
{ # An instance of a Schedule periodically schedules runs to make API calls based on user specified time specification and API request type.
"allowQueueing": True or False, # Optional. Whether new scheduled runs can be queued when max_concurrent_runs limit is reached. If set to true, new runs will be queued instead of skipped. Default to false.
"catchUp": True or False, # Output only. Whether to backfill missed runs when the schedule is resumed from PAUSED state. If set to true, all missed runs will be scheduled. New runs will be scheduled after the backfill is complete. Default to false.
"createNotebookExecutionJobRequest": { # Request message for [NotebookService.CreateNotebookExecutionJob] # Request for NotebookService.CreateNotebookExecutionJob.
"notebookExecutionJob": { # NotebookExecutionJob represents an instance of a notebook execution. # Required. The NotebookExecutionJob to create.
"createTime": "A String", # Output only. Timestamp when this NotebookExecutionJob was created.
"customEnvironmentSpec": { # Compute configuration to use for an execution job. # The custom compute configuration for an execution job.
"machineSpec": { # Specification of a single machine. # The specification of a single machine for the execution job.
"acceleratorCount": 42, # The number of accelerators to attach to the machine.
"acceleratorType": "A String", # Immutable. The type of accelerator(s) that may be attached to the machine as per accelerator_count.
"machineType": "A String", # Immutable. The type of the machine. See the [list of machine types supported for prediction](https://cloud.google.com/vertex-ai/docs/predictions/configure-compute#machine-types) See the [list of machine types supported for custom training](https://cloud.google.com/vertex-ai/docs/training/configure-compute#machine-types). For DeployedModel this field is optional, and the default value is `n1-standard-2`. For BatchPredictionJob or as part of WorkerPoolSpec this field is required.
"reservationAffinity": { # A ReservationAffinity can be used to configure a Vertex AI resource (e.g., a DeployedModel) to draw its Compute Engine resources from a Shared Reservation, or exclusively from on-demand capacity. # Optional. Immutable. Configuration controlling how this resource pool consumes reservation.
"key": "A String", # Optional. Corresponds to the label key of a reservation resource. To target a SPECIFIC_RESERVATION by name, use `compute.googleapis.com/reservation-name` as the key and specify the name of your reservation as its value.
"reservationAffinityType": "A String", # Required. Specifies the reservation affinity type.
"values": [ # Optional. Corresponds to the label values of a reservation resource. This must be the full resource name of the reservation.
"A String",
],
},
"tpuTopology": "A String", # Immutable. The topology of the TPUs. Corresponds to the TPU topologies available from GKE. (Example: tpu_topology: "2x2x1").
},
"networkSpec": { # Network spec. # The network configuration to use for the execution job.
"enableInternetAccess": True or False, # Whether to enable public internet access. Default false.
"network": "A String", # The full name of the Google Compute Engine [network](https://cloud.google.com//compute/docs/networks-and-firewalls#networks)
"subnetwork": "A String", # The name of the subnet that this instance is in. Format: `projects/{project_id_or_number}/regions/{region}/subnetworks/{subnetwork_id}`
},
"persistentDiskSpec": { # Represents the spec of persistent disk options. # The specification of a persistent disk to attach for the execution job.
"diskSizeGb": "A String", # Size in GB of the disk (default is 100GB).
"diskType": "A String", # Type of the disk (default is "pd-standard"). Valid values: "pd-ssd" (Persistent Disk Solid State Drive) "pd-standard" (Persistent Disk Hard Disk Drive) "pd-balanced" (Balanced Persistent Disk) "pd-extreme" (Extreme Persistent Disk)
},
},
"dataformRepositorySource": { # The Dataform Repository containing the input notebook. # The Dataform Repository pointing to a single file notebook repository.
"commitSha": "A String", # The commit SHA to read repository with. If unset, the file will be read at HEAD.
"dataformRepositoryResourceName": "A String", # The resource name of the Dataform Repository. Format: `projects/{project_id}/locations/{location}/repositories/{repository_id}`
},
"directNotebookSource": { # The content of the input notebook in ipynb format. # The contents of an input notebook file.
"content": "A String", # The base64-encoded contents of the input notebook file.
},
"displayName": "A String", # The display name of the NotebookExecutionJob. The name can be up to 128 characters long and can consist of any UTF-8 characters.
"encryptionSpec": { # Represents a customer-managed encryption key spec that can be applied to a top-level resource. # Customer-managed encryption key spec for the notebook execution job. This field is auto-populated if the NotebookService.NotebookRuntimeTemplate has an encryption spec.
"kmsKeyName": "A String", # Required. The Cloud KMS resource identifier of the customer managed encryption key used to protect a resource. Has the form: `projects/my-project/locations/my-region/keyRings/my-kr/cryptoKeys/my-key`. The key needs to be in the same region as where the compute resource is created.
},
"executionTimeout": "A String", # Max running time of the execution job in seconds (default 86400s / 24 hrs).
"executionUser": "A String", # The user email to run the execution as. Only supported by Colab runtimes.
"gcsNotebookSource": { # The Cloud Storage uri for the input notebook. # The Cloud Storage url pointing to the ipynb file. Format: `gs://bucket/notebook_file.ipynb`
"generation": "A String", # The version of the Cloud Storage object to read. If unset, the current version of the object is read. See https://cloud.google.com/storage/docs/metadata#generation-number.
"uri": "A String", # The Cloud Storage uri pointing to the ipynb file. Format: `gs://bucket/notebook_file.ipynb`
},
"gcsOutputUri": "A String", # The Cloud Storage location to upload the result to. Format: `gs://bucket-name`
"jobState": "A String", # Output only. The state of the NotebookExecutionJob.
"labels": { # The labels with user-defined metadata to organize NotebookExecutionJobs. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable.
"a_key": "A String",
},
"name": "A String", # Output only. The resource name of this NotebookExecutionJob. Format: `projects/{project_id}/locations/{location}/notebookExecutionJobs/{job_id}`
"notebookRuntimeTemplateResourceName": "A String", # The NotebookRuntimeTemplate to source compute configuration from.
"scheduleResourceName": "A String", # Output only. The Schedule resource name if this job is triggered by one. Format: `projects/{project_id}/locations/{location}/schedules/{schedule_id}`
"serviceAccount": "A String", # The service account to run the execution as.
"status": { # The `Status` type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by [gRPC](https://github.com/grpc). Each `Status` message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the [API Design Guide](https://cloud.google.com/apis/design/errors). # Output only. Populated when the NotebookExecutionJob is completed. When there is an error during notebook execution, the error details are populated.
"code": 42, # The status code, which should be an enum value of google.rpc.Code.
"details": [ # A list of messages that carry the error details. There is a common set of message types for APIs to use.
{
"a_key": "", # Properties of the object. Contains field @type with type URL.
},
],
"message": "A String", # A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.
},
"updateTime": "A String", # Output only. Timestamp when this NotebookExecutionJob was most recently updated.
},
"notebookExecutionJobId": "A String", # Optional. User specified ID for the NotebookExecutionJob.
"parent": "A String", # Required. The resource name of the Location to create the NotebookExecutionJob. Format: `projects/{project}/locations/{location}`
},
"createPipelineJobRequest": { # Request message for PipelineService.CreatePipelineJob. # Request for PipelineService.CreatePipelineJob. CreatePipelineJobRequest.parent field is required (format: projects/{project}/locations/{location}).
"parent": "A String", # Required. The resource name of the Location to create the PipelineJob in. Format: `projects/{project}/locations/{location}`
"pipelineJob": { # An instance of a machine learning PipelineJob. # Required. The PipelineJob to create.
"createTime": "A String", # Output only. Pipeline creation time.
"displayName": "A String", # The display name of the Pipeline. The name can be up to 128 characters long and can consist of any UTF-8 characters.
"encryptionSpec": { # Represents a customer-managed encryption key spec that can be applied to a top-level resource. # Customer-managed encryption key spec for a pipelineJob. If set, this PipelineJob and all of its sub-resources will be secured by this key.
"kmsKeyName": "A String", # Required. The Cloud KMS resource identifier of the customer managed encryption key used to protect a resource. Has the form: `projects/my-project/locations/my-region/keyRings/my-kr/cryptoKeys/my-key`. The key needs to be in the same region as where the compute resource is created.
},
"endTime": "A String", # Output only. Pipeline end time.
"error": { # The `Status` type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by [gRPC](https://github.com/grpc). Each `Status` message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the [API Design Guide](https://cloud.google.com/apis/design/errors). # Output only. The error that occurred during pipeline execution. Only populated when the pipeline's state is FAILED or CANCELLED.
"code": 42, # The status code, which should be an enum value of google.rpc.Code.
"details": [ # A list of messages that carry the error details. There is a common set of message types for APIs to use.
{
"a_key": "", # Properties of the object. Contains field @type with type URL.
},
],
"message": "A String", # A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.
},
"jobDetail": { # The runtime detail of PipelineJob. # Output only. The details of pipeline run. Not available in the list view.
"pipelineContext": { # Instance of a general context. # Output only. The context of the pipeline.
"createTime": "A String", # Output only. Timestamp when this Context was created.
"description": "A String", # Description of the Context
"displayName": "A String", # User provided display name of the Context. May be up to 128 Unicode characters.
"etag": "A String", # An eTag used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
"labels": { # The labels with user-defined metadata to organize your Contexts. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one Context (System labels are excluded).
"a_key": "A String",
},
"metadata": { # Properties of the Context. Top level metadata keys' heading and trailing spaces will be trimmed. The size of this field should not exceed 200KB.
"a_key": "", # Properties of the object.
},
"name": "A String", # Immutable. The resource name of the Context.
"parentContexts": [ # Output only. A list of resource names of Contexts that are parents of this Context. A Context may have at most 10 parent_contexts.
"A String",
],
"schemaTitle": "A String", # The title of the schema describing the metadata. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.
"schemaVersion": "A String", # The version of the schema in schema_name to use. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.
"updateTime": "A String", # Output only. Timestamp when this Context was last updated.
},
"pipelineRunContext": { # Instance of a general context. # Output only. The context of the current pipeline run.
"createTime": "A String", # Output only. Timestamp when this Context was created.
"description": "A String", # Description of the Context
"displayName": "A String", # User provided display name of the Context. May be up to 128 Unicode characters.
"etag": "A String", # An eTag used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
"labels": { # The labels with user-defined metadata to organize your Contexts. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one Context (System labels are excluded).
"a_key": "A String",
},
"metadata": { # Properties of the Context. Top level metadata keys' heading and trailing spaces will be trimmed. The size of this field should not exceed 200KB.
"a_key": "", # Properties of the object.
},
"name": "A String", # Immutable. The resource name of the Context.
"parentContexts": [ # Output only. A list of resource names of Contexts that are parents of this Context. A Context may have at most 10 parent_contexts.
"A String",
],
"schemaTitle": "A String", # The title of the schema describing the metadata. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.
"schemaVersion": "A String", # The version of the schema in schema_name to use. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.
"updateTime": "A String", # Output only. Timestamp when this Context was last updated.
},
"taskDetails": [ # Output only. The runtime details of the tasks under the pipeline.
{ # The runtime detail of a task execution.
"createTime": "A String", # Output only. Task create time.
"endTime": "A String", # Output only. Task end time.
"error": { # The `Status` type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by [gRPC](https://github.com/grpc). Each `Status` message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the [API Design Guide](https://cloud.google.com/apis/design/errors). # Output only. The error that occurred during task execution. Only populated when the task's state is FAILED or CANCELLED.
"code": 42, # The status code, which should be an enum value of google.rpc.Code.
"details": [ # A list of messages that carry the error details. There is a common set of message types for APIs to use.
{
"a_key": "", # Properties of the object. Contains field @type with type URL.
},
],
"message": "A String", # A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.
},
"execution": { # Instance of a general execution. # Output only. The execution metadata of the task.
"createTime": "A String", # Output only. Timestamp when this Execution was created.
"description": "A String", # Description of the Execution
"displayName": "A String", # User provided display name of the Execution. May be up to 128 Unicode characters.
"etag": "A String", # An eTag used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
"labels": { # The labels with user-defined metadata to organize your Executions. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one Execution (System labels are excluded).
"a_key": "A String",
},
"metadata": { # Properties of the Execution. Top level metadata keys' heading and trailing spaces will be trimmed. The size of this field should not exceed 200KB.
"a_key": "", # Properties of the object.
},
"name": "A String", # Output only. The resource name of the Execution.
"schemaTitle": "A String", # The title of the schema describing the metadata. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.
"schemaVersion": "A String", # The version of the schema in `schema_title` to use. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.
"state": "A String", # The state of this Execution. This is a property of the Execution, and does not imply or capture any ongoing process. This property is managed by clients (such as Vertex AI Pipelines) and the system does not prescribe or check the validity of state transitions.
"updateTime": "A String", # Output only. Timestamp when this Execution was last updated.
},
"executorDetail": { # The runtime detail of a pipeline executor. # Output only. The detailed execution info.
"containerDetail": { # The detail of a container execution. It contains the job names of the lifecycle of a container execution. # Output only. The detailed info for a container executor.
"failedMainJobs": [ # Output only. The names of the previously failed CustomJob for the main container executions. The list includes the all attempts in chronological order.
"A String",
],
"failedPreCachingCheckJobs": [ # Output only. The names of the previously failed CustomJob for the pre-caching-check container executions. This job will be available if the PipelineJob.pipeline_spec specifies the `pre_caching_check` hook in the lifecycle events. The list includes the all attempts in chronological order.
"A String",
],
"mainJob": "A String", # Output only. The name of the CustomJob for the main container execution.
"preCachingCheckJob": "A String", # Output only. The name of the CustomJob for the pre-caching-check container execution. This job will be available if the PipelineJob.pipeline_spec specifies the `pre_caching_check` hook in the lifecycle events.
},
"customJobDetail": { # The detailed info for a custom job executor. # Output only. The detailed info for a custom job executor.
"failedJobs": [ # Output only. The names of the previously failed CustomJob. The list includes the all attempts in chronological order.
"A String",
],
"job": "A String", # Output only. The name of the CustomJob.
},
},
"inputs": { # Output only. The runtime input artifacts of the task.
"a_key": { # A list of artifact metadata.
"artifacts": [ # Output only. A list of artifact metadata.
{ # Instance of a general artifact.
"createTime": "A String", # Output only. Timestamp when this Artifact was created.
"description": "A String", # Description of the Artifact
"displayName": "A String", # User provided display name of the Artifact. May be up to 128 Unicode characters.
"etag": "A String", # An eTag used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
"labels": { # The labels with user-defined metadata to organize your Artifacts. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one Artifact (System labels are excluded).
"a_key": "A String",
},
"metadata": { # Properties of the Artifact. Top level metadata keys' heading and trailing spaces will be trimmed. The size of this field should not exceed 200KB.
"a_key": "", # Properties of the object.
},
"name": "A String", # Output only. The resource name of the Artifact.
"schemaTitle": "A String", # The title of the schema describing the metadata. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.
"schemaVersion": "A String", # The version of the schema in schema_name to use. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.
"state": "A String", # The state of this Artifact. This is a property of the Artifact, and does not imply or capture any ongoing process. This property is managed by clients (such as Vertex AI Pipelines), and the system does not prescribe or check the validity of state transitions.
"updateTime": "A String", # Output only. Timestamp when this Artifact was last updated.
"uri": "A String", # The uniform resource identifier of the artifact file. May be empty if there is no actual artifact file.
},
],
},
},
"outputs": { # Output only. The runtime output artifacts of the task.
"a_key": { # A list of artifact metadata.
"artifacts": [ # Output only. A list of artifact metadata.
{ # Instance of a general artifact.
"createTime": "A String", # Output only. Timestamp when this Artifact was created.
"description": "A String", # Description of the Artifact
"displayName": "A String", # User provided display name of the Artifact. May be up to 128 Unicode characters.
"etag": "A String", # An eTag used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
"labels": { # The labels with user-defined metadata to organize your Artifacts. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one Artifact (System labels are excluded).
"a_key": "A String",
},
"metadata": { # Properties of the Artifact. Top level metadata keys' heading and trailing spaces will be trimmed. The size of this field should not exceed 200KB.
"a_key": "", # Properties of the object.
},
"name": "A String", # Output only. The resource name of the Artifact.
"schemaTitle": "A String", # The title of the schema describing the metadata. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.
"schemaVersion": "A String", # The version of the schema in schema_name to use. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.
"state": "A String", # The state of this Artifact. This is a property of the Artifact, and does not imply or capture any ongoing process. This property is managed by clients (such as Vertex AI Pipelines), and the system does not prescribe or check the validity of state transitions.
"updateTime": "A String", # Output only. Timestamp when this Artifact was last updated.
"uri": "A String", # The uniform resource identifier of the artifact file. May be empty if there is no actual artifact file.
},
],
},
},
"parentTaskId": "A String", # Output only. The id of the parent task if the task is within a component scope. Empty if the task is at the root level.
"pipelineTaskStatus": [ # Output only. A list of task status. This field keeps a record of task status evolving over time.
{ # A single record of the task status.
"error": { # The `Status` type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by [gRPC](https://github.com/grpc). Each `Status` message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the [API Design Guide](https://cloud.google.com/apis/design/errors). # Output only. The error that occurred during the state. May be set when the state is any of the non-final state (PENDING/RUNNING/CANCELLING) or FAILED state. If the state is FAILED, the error here is final and not going to be retried. If the state is a non-final state, the error indicates a system-error being retried.
"code": 42, # The status code, which should be an enum value of google.rpc.Code.
"details": [ # A list of messages that carry the error details. There is a common set of message types for APIs to use.
{
"a_key": "", # Properties of the object. Contains field @type with type URL.
},
],
"message": "A String", # A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.
},
"state": "A String", # Output only. The state of the task.
"updateTime": "A String", # Output only. Update time of this status.
},
],
"startTime": "A String", # Output only. Task start time.
"state": "A String", # Output only. State of the task.
"taskId": "A String", # Output only. The system generated ID of the task.
"taskName": "A String", # Output only. The user specified name of the task that is defined in pipeline_spec.
},
],
},
"labels": { # The labels with user-defined metadata to organize PipelineJob. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels. Note there is some reserved label key for Vertex AI Pipelines. - `vertex-ai-pipelines-run-billing-id`, user set value will get overrided.
"a_key": "A String",
},
"name": "A String", # Output only. The resource name of the PipelineJob.
"network": "A String", # The full name of the Compute Engine [network](/compute/docs/networks-and-firewalls#networks) to which the Pipeline Job's workload should be peered. For example, `projects/12345/global/networks/myVPC`. [Format](/compute/docs/reference/rest/v1/networks/insert) is of the form `projects/{project}/global/networks/{network}`. Where {project} is a project number, as in `12345`, and {network} is a network name. Private services access must already be configured for the network. Pipeline job will apply the network configuration to the Google Cloud resources being launched, if applied, such as Vertex AI Training or Dataflow job. If left unspecified, the workload is not peered with any network.
"pipelineSpec": { # The spec of the pipeline.
"a_key": "", # Properties of the object.
},
"preflightValidations": True or False, # Optional. Whether to do component level validations before job creation.
"reservedIpRanges": [ # A list of names for the reserved ip ranges under the VPC network that can be used for this Pipeline Job's workload. If set, we will deploy the Pipeline Job's workload within the provided ip ranges. Otherwise, the job will be deployed to any ip ranges under the provided VPC network. Example: ['vertex-ai-ip-range'].
"A String",
],
"runtimeConfig": { # The runtime config of a PipelineJob. # Runtime config of the pipeline.
"failurePolicy": "A String", # Represents the failure policy of a pipeline. Currently, the default of a pipeline is that the pipeline will continue to run until no more tasks can be executed, also known as PIPELINE_FAILURE_POLICY_FAIL_SLOW. However, if a pipeline is set to PIPELINE_FAILURE_POLICY_FAIL_FAST, it will stop scheduling any new tasks when a task has failed. Any scheduled tasks will continue to completion.
"gcsOutputDirectory": "A String", # Required. A path in a Cloud Storage bucket, which will be treated as the root output directory of the pipeline. It is used by the system to generate the paths of output artifacts. The artifact paths are generated with a sub-path pattern `{job_id}/{task_id}/{output_key}` under the specified output directory. The service account specified in this pipeline must have the `storage.objects.get` and `storage.objects.create` permissions for this bucket.
"inputArtifacts": { # The runtime artifacts of the PipelineJob. The key will be the input artifact name and the value would be one of the InputArtifact.
"a_key": { # The type of an input artifact.
"artifactId": "A String", # Artifact resource id from MLMD. Which is the last portion of an artifact resource name: `projects/{project}/locations/{location}/metadataStores/default/artifacts/{artifact_id}`. The artifact must stay within the same project, location and default metadatastore as the pipeline.
},
},
"parameterValues": { # The runtime parameters of the PipelineJob. The parameters will be passed into PipelineJob.pipeline_spec to replace the placeholders at runtime. This field is used by pipelines built using `PipelineJob.pipeline_spec.schema_version` 2.1.0, such as pipelines built using Kubeflow Pipelines SDK 1.9 or higher and the v2 DSL.
"a_key": "",
},
"parameters": { # Deprecated. Use RuntimeConfig.parameter_values instead. The runtime parameters of the PipelineJob. The parameters will be passed into PipelineJob.pipeline_spec to replace the placeholders at runtime. This field is used by pipelines built using `PipelineJob.pipeline_spec.schema_version` 2.0.0 or lower, such as pipelines built using Kubeflow Pipelines SDK 1.8 or lower.
"a_key": { # Value is the value of the field.
"doubleValue": 3.14, # A double value.
"intValue": "A String", # An integer value.
"stringValue": "A String", # A string value.
},
},
},
"scheduleName": "A String", # Output only. The schedule resource name. Only returned if the Pipeline is created by Schedule API.
"serviceAccount": "A String", # The service account that the pipeline workload runs as. If not specified, the Compute Engine default service account in the project will be used. See https://cloud.google.com/compute/docs/access/service-accounts#default_service_account Users starting the pipeline must have the `iam.serviceAccounts.actAs` permission on this service account.
"startTime": "A String", # Output only. Pipeline start time.
"state": "A String", # Output only. The detailed state of the job.
"templateMetadata": { # Pipeline template metadata if PipelineJob.template_uri is from supported template registry. Currently, the only supported registry is Artifact Registry. # Output only. Pipeline template metadata. Will fill up fields if PipelineJob.template_uri is from supported template registry.
"version": "A String", # The version_name in artifact registry. Will always be presented in output if the PipelineJob.template_uri is from supported template registry. Format is "sha256:abcdef123456...".
},
"templateUri": "A String", # A template uri from where the PipelineJob.pipeline_spec, if empty, will be downloaded. Currently, only uri from Vertex Template Registry & Gallery is supported. Reference to https://cloud.google.com/vertex-ai/docs/pipelines/create-pipeline-template.
"updateTime": "A String", # Output only. Timestamp when this PipelineJob was most recently updated.
},
"pipelineJobId": "A String", # The ID to use for the PipelineJob, which will become the final component of the PipelineJob name. If not provided, an ID will be automatically generated. This value should be less than 128 characters, and valid characters are `/a-z-/`.
},
"createTime": "A String", # Output only. Timestamp when this Schedule was created.
"cron": "A String", # Cron schedule (https://en.wikipedia.org/wiki/Cron) to launch scheduled runs. To explicitly set a timezone to the cron tab, apply a prefix in the cron tab: "CRON_TZ=${IANA_TIME_ZONE}" or "TZ=${IANA_TIME_ZONE}". The ${IANA_TIME_ZONE} may only be a valid string from IANA time zone database. For example, "CRON_TZ=America/New_York 1 * * * *", or "TZ=America/New_York 1 * * * *".
"displayName": "A String", # Required. User provided name of the Schedule. The name can be up to 128 characters long and can consist of any UTF-8 characters.
"endTime": "A String", # Optional. Timestamp after which no new runs can be scheduled. If specified, The schedule will be completed when either end_time is reached or when scheduled_run_count >= max_run_count. If not specified, new runs will keep getting scheduled until this Schedule is paused or deleted. Already scheduled runs will be allowed to complete. Unset if not specified.
"lastPauseTime": "A String", # Output only. Timestamp when this Schedule was last paused. Unset if never paused.
"lastResumeTime": "A String", # Output only. Timestamp when this Schedule was last resumed. Unset if never resumed from pause.
"lastScheduledRunResponse": { # Status of a scheduled run. # Output only. Response of the last scheduled run. This is the response for starting the scheduled requests and not the execution of the operations/jobs created by the requests (if applicable). Unset if no run has been scheduled yet.
"runResponse": "A String", # The response of the scheduled run.
"scheduledRunTime": "A String", # The scheduled run time based on the user-specified schedule.
},
"maxConcurrentRunCount": "A String", # Required. Maximum number of runs that can be started concurrently for this Schedule. This is the limit for starting the scheduled requests and not the execution of the operations/jobs created by the requests (if applicable).
"maxRunCount": "A String", # Optional. Maximum run count of the schedule. If specified, The schedule will be completed when either started_run_count >= max_run_count or when end_time is reached. If not specified, new runs will keep getting scheduled until this Schedule is paused or deleted. Already scheduled runs will be allowed to complete. Unset if not specified.
"name": "A String", # Immutable. The resource name of the Schedule.
"nextRunTime": "A String", # Output only. Timestamp when this Schedule should schedule the next run. Having a next_run_time in the past means the runs are being started behind schedule.
"startTime": "A String", # Optional. Timestamp after which the first run can be scheduled. Default to Schedule create time if not specified.
"startedRunCount": "A String", # Output only. The number of runs started by this schedule.
"state": "A String", # Output only. The state of this Schedule.
"updateTime": "A String", # Output only. Timestamp when this Schedule was updated.
}
delete(name, x__xgafv=None)
Deletes a Schedule.
Args:
name: string, Required. The name of the Schedule resource to be deleted. Format: `projects/{project}/locations/{location}/schedules/{schedule}` (required)
x__xgafv: string, V1 error format.
Allowed values
1 - v1 error format
2 - v2 error format
Returns:
An object of the form:
{ # This resource represents a long-running operation that is the result of a network API call.
"done": True or False, # If the value is `false`, it means the operation is still in progress. If `true`, the operation is completed, and either `error` or `response` is available.
"error": { # The `Status` type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by [gRPC](https://github.com/grpc). Each `Status` message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the [API Design Guide](https://cloud.google.com/apis/design/errors). # The error result of the operation in case of failure or cancellation.
"code": 42, # The status code, which should be an enum value of google.rpc.Code.
"details": [ # A list of messages that carry the error details. There is a common set of message types for APIs to use.
{
"a_key": "", # Properties of the object. Contains field @type with type URL.
},
],
"message": "A String", # A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.
},
"metadata": { # Service-specific metadata associated with the operation. It typically contains progress information and common metadata such as create time. Some services might not provide such metadata. Any method that returns a long-running operation should document the metadata type, if any.
"a_key": "", # Properties of the object. Contains field @type with type URL.
},
"name": "A String", # The server-assigned name, which is only unique within the same service that originally returns it. If you use the default HTTP mapping, the `name` should be a resource name ending with `operations/{unique_id}`.
"response": { # The normal, successful response of the operation. If the original method returns no data on success, such as `Delete`, the response is `google.protobuf.Empty`. If the original method is standard `Get`/`Create`/`Update`, the response should be the resource. For other methods, the response should have the type `XxxResponse`, where `Xxx` is the original method name. For example, if the original method name is `TakeSnapshot()`, the inferred response type is `TakeSnapshotResponse`.
"a_key": "", # Properties of the object. Contains field @type with type URL.
},
}
get(name, x__xgafv=None)
Gets a Schedule.
Args:
name: string, Required. The name of the Schedule resource. Format: `projects/{project}/locations/{location}/schedules/{schedule}` (required)
x__xgafv: string, V1 error format.
Allowed values
1 - v1 error format
2 - v2 error format
Returns:
An object of the form:
{ # An instance of a Schedule periodically schedules runs to make API calls based on user specified time specification and API request type.
"allowQueueing": True or False, # Optional. Whether new scheduled runs can be queued when max_concurrent_runs limit is reached. If set to true, new runs will be queued instead of skipped. Default to false.
"catchUp": True or False, # Output only. Whether to backfill missed runs when the schedule is resumed from PAUSED state. If set to true, all missed runs will be scheduled. New runs will be scheduled after the backfill is complete. Default to false.
"createNotebookExecutionJobRequest": { # Request message for [NotebookService.CreateNotebookExecutionJob] # Request for NotebookService.CreateNotebookExecutionJob.
"notebookExecutionJob": { # NotebookExecutionJob represents an instance of a notebook execution. # Required. The NotebookExecutionJob to create.
"createTime": "A String", # Output only. Timestamp when this NotebookExecutionJob was created.
"customEnvironmentSpec": { # Compute configuration to use for an execution job. # The custom compute configuration for an execution job.
"machineSpec": { # Specification of a single machine. # The specification of a single machine for the execution job.
"acceleratorCount": 42, # The number of accelerators to attach to the machine.
"acceleratorType": "A String", # Immutable. The type of accelerator(s) that may be attached to the machine as per accelerator_count.
"machineType": "A String", # Immutable. The type of the machine. See the [list of machine types supported for prediction](https://cloud.google.com/vertex-ai/docs/predictions/configure-compute#machine-types) See the [list of machine types supported for custom training](https://cloud.google.com/vertex-ai/docs/training/configure-compute#machine-types). For DeployedModel this field is optional, and the default value is `n1-standard-2`. For BatchPredictionJob or as part of WorkerPoolSpec this field is required.
"reservationAffinity": { # A ReservationAffinity can be used to configure a Vertex AI resource (e.g., a DeployedModel) to draw its Compute Engine resources from a Shared Reservation, or exclusively from on-demand capacity. # Optional. Immutable. Configuration controlling how this resource pool consumes reservation.
"key": "A String", # Optional. Corresponds to the label key of a reservation resource. To target a SPECIFIC_RESERVATION by name, use `compute.googleapis.com/reservation-name` as the key and specify the name of your reservation as its value.
"reservationAffinityType": "A String", # Required. Specifies the reservation affinity type.
"values": [ # Optional. Corresponds to the label values of a reservation resource. This must be the full resource name of the reservation.
"A String",
],
},
"tpuTopology": "A String", # Immutable. The topology of the TPUs. Corresponds to the TPU topologies available from GKE. (Example: tpu_topology: "2x2x1").
},
"networkSpec": { # Network spec. # The network configuration to use for the execution job.
"enableInternetAccess": True or False, # Whether to enable public internet access. Default false.
"network": "A String", # The full name of the Google Compute Engine [network](https://cloud.google.com//compute/docs/networks-and-firewalls#networks)
"subnetwork": "A String", # The name of the subnet that this instance is in. Format: `projects/{project_id_or_number}/regions/{region}/subnetworks/{subnetwork_id}`
},
"persistentDiskSpec": { # Represents the spec of persistent disk options. # The specification of a persistent disk to attach for the execution job.
"diskSizeGb": "A String", # Size in GB of the disk (default is 100GB).
"diskType": "A String", # Type of the disk (default is "pd-standard"). Valid values: "pd-ssd" (Persistent Disk Solid State Drive) "pd-standard" (Persistent Disk Hard Disk Drive) "pd-balanced" (Balanced Persistent Disk) "pd-extreme" (Extreme Persistent Disk)
},
},
"dataformRepositorySource": { # The Dataform Repository containing the input notebook. # The Dataform Repository pointing to a single file notebook repository.
"commitSha": "A String", # The commit SHA to read repository with. If unset, the file will be read at HEAD.
"dataformRepositoryResourceName": "A String", # The resource name of the Dataform Repository. Format: `projects/{project_id}/locations/{location}/repositories/{repository_id}`
},
"directNotebookSource": { # The content of the input notebook in ipynb format. # The contents of an input notebook file.
"content": "A String", # The base64-encoded contents of the input notebook file.
},
"displayName": "A String", # The display name of the NotebookExecutionJob. The name can be up to 128 characters long and can consist of any UTF-8 characters.
"encryptionSpec": { # Represents a customer-managed encryption key spec that can be applied to a top-level resource. # Customer-managed encryption key spec for the notebook execution job. This field is auto-populated if the NotebookService.NotebookRuntimeTemplate has an encryption spec.
"kmsKeyName": "A String", # Required. The Cloud KMS resource identifier of the customer managed encryption key used to protect a resource. Has the form: `projects/my-project/locations/my-region/keyRings/my-kr/cryptoKeys/my-key`. The key needs to be in the same region as where the compute resource is created.
},
"executionTimeout": "A String", # Max running time of the execution job in seconds (default 86400s / 24 hrs).
"executionUser": "A String", # The user email to run the execution as. Only supported by Colab runtimes.
"gcsNotebookSource": { # The Cloud Storage uri for the input notebook. # The Cloud Storage url pointing to the ipynb file. Format: `gs://bucket/notebook_file.ipynb`
"generation": "A String", # The version of the Cloud Storage object to read. If unset, the current version of the object is read. See https://cloud.google.com/storage/docs/metadata#generation-number.
"uri": "A String", # The Cloud Storage uri pointing to the ipynb file. Format: `gs://bucket/notebook_file.ipynb`
},
"gcsOutputUri": "A String", # The Cloud Storage location to upload the result to. Format: `gs://bucket-name`
"jobState": "A String", # Output only. The state of the NotebookExecutionJob.
"labels": { # The labels with user-defined metadata to organize NotebookExecutionJobs. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable.
"a_key": "A String",
},
"name": "A String", # Output only. The resource name of this NotebookExecutionJob. Format: `projects/{project_id}/locations/{location}/notebookExecutionJobs/{job_id}`
"notebookRuntimeTemplateResourceName": "A String", # The NotebookRuntimeTemplate to source compute configuration from.
"scheduleResourceName": "A String", # Output only. The Schedule resource name if this job is triggered by one. Format: `projects/{project_id}/locations/{location}/schedules/{schedule_id}`
"serviceAccount": "A String", # The service account to run the execution as.
"status": { # The `Status` type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by [gRPC](https://github.com/grpc). Each `Status` message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the [API Design Guide](https://cloud.google.com/apis/design/errors). # Output only. Populated when the NotebookExecutionJob is completed. When there is an error during notebook execution, the error details are populated.
"code": 42, # The status code, which should be an enum value of google.rpc.Code.
"details": [ # A list of messages that carry the error details. There is a common set of message types for APIs to use.
{
"a_key": "", # Properties of the object. Contains field @type with type URL.
},
],
"message": "A String", # A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.
},
"updateTime": "A String", # Output only. Timestamp when this NotebookExecutionJob was most recently updated.
},
"notebookExecutionJobId": "A String", # Optional. User specified ID for the NotebookExecutionJob.
"parent": "A String", # Required. The resource name of the Location to create the NotebookExecutionJob. Format: `projects/{project}/locations/{location}`
},
"createPipelineJobRequest": { # Request message for PipelineService.CreatePipelineJob. # Request for PipelineService.CreatePipelineJob. CreatePipelineJobRequest.parent field is required (format: projects/{project}/locations/{location}).
"parent": "A String", # Required. The resource name of the Location to create the PipelineJob in. Format: `projects/{project}/locations/{location}`
"pipelineJob": { # An instance of a machine learning PipelineJob. # Required. The PipelineJob to create.
"createTime": "A String", # Output only. Pipeline creation time.
"displayName": "A String", # The display name of the Pipeline. The name can be up to 128 characters long and can consist of any UTF-8 characters.
"encryptionSpec": { # Represents a customer-managed encryption key spec that can be applied to a top-level resource. # Customer-managed encryption key spec for a pipelineJob. If set, this PipelineJob and all of its sub-resources will be secured by this key.
"kmsKeyName": "A String", # Required. The Cloud KMS resource identifier of the customer managed encryption key used to protect a resource. Has the form: `projects/my-project/locations/my-region/keyRings/my-kr/cryptoKeys/my-key`. The key needs to be in the same region as where the compute resource is created.
},
"endTime": "A String", # Output only. Pipeline end time.
"error": { # The `Status` type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by [gRPC](https://github.com/grpc). Each `Status` message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the [API Design Guide](https://cloud.google.com/apis/design/errors). # Output only. The error that occurred during pipeline execution. Only populated when the pipeline's state is FAILED or CANCELLED.
"code": 42, # The status code, which should be an enum value of google.rpc.Code.
"details": [ # A list of messages that carry the error details. There is a common set of message types for APIs to use.
{
"a_key": "", # Properties of the object. Contains field @type with type URL.
},
],
"message": "A String", # A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.
},
"jobDetail": { # The runtime detail of PipelineJob. # Output only. The details of pipeline run. Not available in the list view.
"pipelineContext": { # Instance of a general context. # Output only. The context of the pipeline.
"createTime": "A String", # Output only. Timestamp when this Context was created.
"description": "A String", # Description of the Context
"displayName": "A String", # User provided display name of the Context. May be up to 128 Unicode characters.
"etag": "A String", # An eTag used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
"labels": { # The labels with user-defined metadata to organize your Contexts. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one Context (System labels are excluded).
"a_key": "A String",
},
"metadata": { # Properties of the Context. Top level metadata keys' heading and trailing spaces will be trimmed. The size of this field should not exceed 200KB.
"a_key": "", # Properties of the object.
},
"name": "A String", # Immutable. The resource name of the Context.
"parentContexts": [ # Output only. A list of resource names of Contexts that are parents of this Context. A Context may have at most 10 parent_contexts.
"A String",
],
"schemaTitle": "A String", # The title of the schema describing the metadata. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.
"schemaVersion": "A String", # The version of the schema in schema_name to use. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.
"updateTime": "A String", # Output only. Timestamp when this Context was last updated.
},
"pipelineRunContext": { # Instance of a general context. # Output only. The context of the current pipeline run.
"createTime": "A String", # Output only. Timestamp when this Context was created.
"description": "A String", # Description of the Context
"displayName": "A String", # User provided display name of the Context. May be up to 128 Unicode characters.
"etag": "A String", # An eTag used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
"labels": { # The labels with user-defined metadata to organize your Contexts. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one Context (System labels are excluded).
"a_key": "A String",
},
"metadata": { # Properties of the Context. Top level metadata keys' heading and trailing spaces will be trimmed. The size of this field should not exceed 200KB.
"a_key": "", # Properties of the object.
},
"name": "A String", # Immutable. The resource name of the Context.
"parentContexts": [ # Output only. A list of resource names of Contexts that are parents of this Context. A Context may have at most 10 parent_contexts.
"A String",
],
"schemaTitle": "A String", # The title of the schema describing the metadata. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.
"schemaVersion": "A String", # The version of the schema in schema_name to use. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.
"updateTime": "A String", # Output only. Timestamp when this Context was last updated.
},
"taskDetails": [ # Output only. The runtime details of the tasks under the pipeline.
{ # The runtime detail of a task execution.
"createTime": "A String", # Output only. Task create time.
"endTime": "A String", # Output only. Task end time.
"error": { # The `Status` type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by [gRPC](https://github.com/grpc). Each `Status` message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the [API Design Guide](https://cloud.google.com/apis/design/errors). # Output only. The error that occurred during task execution. Only populated when the task's state is FAILED or CANCELLED.
"code": 42, # The status code, which should be an enum value of google.rpc.Code.
"details": [ # A list of messages that carry the error details. There is a common set of message types for APIs to use.
{
"a_key": "", # Properties of the object. Contains field @type with type URL.
},
],
"message": "A String", # A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.
},
"execution": { # Instance of a general execution. # Output only. The execution metadata of the task.
"createTime": "A String", # Output only. Timestamp when this Execution was created.
"description": "A String", # Description of the Execution
"displayName": "A String", # User provided display name of the Execution. May be up to 128 Unicode characters.
"etag": "A String", # An eTag used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
"labels": { # The labels with user-defined metadata to organize your Executions. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one Execution (System labels are excluded).
"a_key": "A String",
},
"metadata": { # Properties of the Execution. Top level metadata keys' heading and trailing spaces will be trimmed. The size of this field should not exceed 200KB.
"a_key": "", # Properties of the object.
},
"name": "A String", # Output only. The resource name of the Execution.
"schemaTitle": "A String", # The title of the schema describing the metadata. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.
"schemaVersion": "A String", # The version of the schema in `schema_title` to use. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.
"state": "A String", # The state of this Execution. This is a property of the Execution, and does not imply or capture any ongoing process. This property is managed by clients (such as Vertex AI Pipelines) and the system does not prescribe or check the validity of state transitions.
"updateTime": "A String", # Output only. Timestamp when this Execution was last updated.
},
"executorDetail": { # The runtime detail of a pipeline executor. # Output only. The detailed execution info.
"containerDetail": { # The detail of a container execution. It contains the job names of the lifecycle of a container execution. # Output only. The detailed info for a container executor.
"failedMainJobs": [ # Output only. The names of the previously failed CustomJob for the main container executions. The list includes the all attempts in chronological order.
"A String",
],
"failedPreCachingCheckJobs": [ # Output only. The names of the previously failed CustomJob for the pre-caching-check container executions. This job will be available if the PipelineJob.pipeline_spec specifies the `pre_caching_check` hook in the lifecycle events. The list includes the all attempts in chronological order.
"A String",
],
"mainJob": "A String", # Output only. The name of the CustomJob for the main container execution.
"preCachingCheckJob": "A String", # Output only. The name of the CustomJob for the pre-caching-check container execution. This job will be available if the PipelineJob.pipeline_spec specifies the `pre_caching_check` hook in the lifecycle events.
},
"customJobDetail": { # The detailed info for a custom job executor. # Output only. The detailed info for a custom job executor.
"failedJobs": [ # Output only. The names of the previously failed CustomJob. The list includes the all attempts in chronological order.
"A String",
],
"job": "A String", # Output only. The name of the CustomJob.
},
},
"inputs": { # Output only. The runtime input artifacts of the task.
"a_key": { # A list of artifact metadata.
"artifacts": [ # Output only. A list of artifact metadata.
{ # Instance of a general artifact.
"createTime": "A String", # Output only. Timestamp when this Artifact was created.
"description": "A String", # Description of the Artifact
"displayName": "A String", # User provided display name of the Artifact. May be up to 128 Unicode characters.
"etag": "A String", # An eTag used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
"labels": { # The labels with user-defined metadata to organize your Artifacts. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one Artifact (System labels are excluded).
"a_key": "A String",
},
"metadata": { # Properties of the Artifact. Top level metadata keys' heading and trailing spaces will be trimmed. The size of this field should not exceed 200KB.
"a_key": "", # Properties of the object.
},
"name": "A String", # Output only. The resource name of the Artifact.
"schemaTitle": "A String", # The title of the schema describing the metadata. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.
"schemaVersion": "A String", # The version of the schema in schema_name to use. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.
"state": "A String", # The state of this Artifact. This is a property of the Artifact, and does not imply or capture any ongoing process. This property is managed by clients (such as Vertex AI Pipelines), and the system does not prescribe or check the validity of state transitions.
"updateTime": "A String", # Output only. Timestamp when this Artifact was last updated.
"uri": "A String", # The uniform resource identifier of the artifact file. May be empty if there is no actual artifact file.
},
],
},
},
"outputs": { # Output only. The runtime output artifacts of the task.
"a_key": { # A list of artifact metadata.
"artifacts": [ # Output only. A list of artifact metadata.
{ # Instance of a general artifact.
"createTime": "A String", # Output only. Timestamp when this Artifact was created.
"description": "A String", # Description of the Artifact
"displayName": "A String", # User provided display name of the Artifact. May be up to 128 Unicode characters.
"etag": "A String", # An eTag used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
"labels": { # The labels with user-defined metadata to organize your Artifacts. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one Artifact (System labels are excluded).
"a_key": "A String",
},
"metadata": { # Properties of the Artifact. Top level metadata keys' heading and trailing spaces will be trimmed. The size of this field should not exceed 200KB.
"a_key": "", # Properties of the object.
},
"name": "A String", # Output only. The resource name of the Artifact.
"schemaTitle": "A String", # The title of the schema describing the metadata. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.
"schemaVersion": "A String", # The version of the schema in schema_name to use. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.
"state": "A String", # The state of this Artifact. This is a property of the Artifact, and does not imply or capture any ongoing process. This property is managed by clients (such as Vertex AI Pipelines), and the system does not prescribe or check the validity of state transitions.
"updateTime": "A String", # Output only. Timestamp when this Artifact was last updated.
"uri": "A String", # The uniform resource identifier of the artifact file. May be empty if there is no actual artifact file.
},
],
},
},
"parentTaskId": "A String", # Output only. The id of the parent task if the task is within a component scope. Empty if the task is at the root level.
"pipelineTaskStatus": [ # Output only. A list of task status. This field keeps a record of task status evolving over time.
{ # A single record of the task status.
"error": { # The `Status` type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by [gRPC](https://github.com/grpc). Each `Status` message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the [API Design Guide](https://cloud.google.com/apis/design/errors). # Output only. The error that occurred during the state. May be set when the state is any of the non-final state (PENDING/RUNNING/CANCELLING) or FAILED state. If the state is FAILED, the error here is final and not going to be retried. If the state is a non-final state, the error indicates a system-error being retried.
"code": 42, # The status code, which should be an enum value of google.rpc.Code.
"details": [ # A list of messages that carry the error details. There is a common set of message types for APIs to use.
{
"a_key": "", # Properties of the object. Contains field @type with type URL.
},
],
"message": "A String", # A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.
},
"state": "A String", # Output only. The state of the task.
"updateTime": "A String", # Output only. Update time of this status.
},
],
"startTime": "A String", # Output only. Task start time.
"state": "A String", # Output only. State of the task.
"taskId": "A String", # Output only. The system generated ID of the task.
"taskName": "A String", # Output only. The user specified name of the task that is defined in pipeline_spec.
},
],
},
"labels": { # The labels with user-defined metadata to organize PipelineJob. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels. Note there is some reserved label key for Vertex AI Pipelines. - `vertex-ai-pipelines-run-billing-id`, user set value will get overrided.
"a_key": "A String",
},
"name": "A String", # Output only. The resource name of the PipelineJob.
"network": "A String", # The full name of the Compute Engine [network](/compute/docs/networks-and-firewalls#networks) to which the Pipeline Job's workload should be peered. For example, `projects/12345/global/networks/myVPC`. [Format](/compute/docs/reference/rest/v1/networks/insert) is of the form `projects/{project}/global/networks/{network}`. Where {project} is a project number, as in `12345`, and {network} is a network name. Private services access must already be configured for the network. Pipeline job will apply the network configuration to the Google Cloud resources being launched, if applied, such as Vertex AI Training or Dataflow job. If left unspecified, the workload is not peered with any network.
"pipelineSpec": { # The spec of the pipeline.
"a_key": "", # Properties of the object.
},
"preflightValidations": True or False, # Optional. Whether to do component level validations before job creation.
"reservedIpRanges": [ # A list of names for the reserved ip ranges under the VPC network that can be used for this Pipeline Job's workload. If set, we will deploy the Pipeline Job's workload within the provided ip ranges. Otherwise, the job will be deployed to any ip ranges under the provided VPC network. Example: ['vertex-ai-ip-range'].
"A String",
],
"runtimeConfig": { # The runtime config of a PipelineJob. # Runtime config of the pipeline.
"failurePolicy": "A String", # Represents the failure policy of a pipeline. Currently, the default of a pipeline is that the pipeline will continue to run until no more tasks can be executed, also known as PIPELINE_FAILURE_POLICY_FAIL_SLOW. However, if a pipeline is set to PIPELINE_FAILURE_POLICY_FAIL_FAST, it will stop scheduling any new tasks when a task has failed. Any scheduled tasks will continue to completion.
"gcsOutputDirectory": "A String", # Required. A path in a Cloud Storage bucket, which will be treated as the root output directory of the pipeline. It is used by the system to generate the paths of output artifacts. The artifact paths are generated with a sub-path pattern `{job_id}/{task_id}/{output_key}` under the specified output directory. The service account specified in this pipeline must have the `storage.objects.get` and `storage.objects.create` permissions for this bucket.
"inputArtifacts": { # The runtime artifacts of the PipelineJob. The key will be the input artifact name and the value would be one of the InputArtifact.
"a_key": { # The type of an input artifact.
"artifactId": "A String", # Artifact resource id from MLMD. Which is the last portion of an artifact resource name: `projects/{project}/locations/{location}/metadataStores/default/artifacts/{artifact_id}`. The artifact must stay within the same project, location and default metadatastore as the pipeline.
},
},
"parameterValues": { # The runtime parameters of the PipelineJob. The parameters will be passed into PipelineJob.pipeline_spec to replace the placeholders at runtime. This field is used by pipelines built using `PipelineJob.pipeline_spec.schema_version` 2.1.0, such as pipelines built using Kubeflow Pipelines SDK 1.9 or higher and the v2 DSL.
"a_key": "",
},
"parameters": { # Deprecated. Use RuntimeConfig.parameter_values instead. The runtime parameters of the PipelineJob. The parameters will be passed into PipelineJob.pipeline_spec to replace the placeholders at runtime. This field is used by pipelines built using `PipelineJob.pipeline_spec.schema_version` 2.0.0 or lower, such as pipelines built using Kubeflow Pipelines SDK 1.8 or lower.
"a_key": { # Value is the value of the field.
"doubleValue": 3.14, # A double value.
"intValue": "A String", # An integer value.
"stringValue": "A String", # A string value.
},
},
},
"scheduleName": "A String", # Output only. The schedule resource name. Only returned if the Pipeline is created by Schedule API.
"serviceAccount": "A String", # The service account that the pipeline workload runs as. If not specified, the Compute Engine default service account in the project will be used. See https://cloud.google.com/compute/docs/access/service-accounts#default_service_account Users starting the pipeline must have the `iam.serviceAccounts.actAs` permission on this service account.
"startTime": "A String", # Output only. Pipeline start time.
"state": "A String", # Output only. The detailed state of the job.
"templateMetadata": { # Pipeline template metadata if PipelineJob.template_uri is from supported template registry. Currently, the only supported registry is Artifact Registry. # Output only. Pipeline template metadata. Will fill up fields if PipelineJob.template_uri is from supported template registry.
"version": "A String", # The version_name in artifact registry. Will always be presented in output if the PipelineJob.template_uri is from supported template registry. Format is "sha256:abcdef123456...".
},
"templateUri": "A String", # A template uri from where the PipelineJob.pipeline_spec, if empty, will be downloaded. Currently, only uri from Vertex Template Registry & Gallery is supported. Reference to https://cloud.google.com/vertex-ai/docs/pipelines/create-pipeline-template.
"updateTime": "A String", # Output only. Timestamp when this PipelineJob was most recently updated.
},
"pipelineJobId": "A String", # The ID to use for the PipelineJob, which will become the final component of the PipelineJob name. If not provided, an ID will be automatically generated. This value should be less than 128 characters, and valid characters are `/a-z-/`.
},
"createTime": "A String", # Output only. Timestamp when this Schedule was created.
"cron": "A String", # Cron schedule (https://en.wikipedia.org/wiki/Cron) to launch scheduled runs. To explicitly set a timezone to the cron tab, apply a prefix in the cron tab: "CRON_TZ=${IANA_TIME_ZONE}" or "TZ=${IANA_TIME_ZONE}". The ${IANA_TIME_ZONE} may only be a valid string from IANA time zone database. For example, "CRON_TZ=America/New_York 1 * * * *", or "TZ=America/New_York 1 * * * *".
"displayName": "A String", # Required. User provided name of the Schedule. The name can be up to 128 characters long and can consist of any UTF-8 characters.
"endTime": "A String", # Optional. Timestamp after which no new runs can be scheduled. If specified, The schedule will be completed when either end_time is reached or when scheduled_run_count >= max_run_count. If not specified, new runs will keep getting scheduled until this Schedule is paused or deleted. Already scheduled runs will be allowed to complete. Unset if not specified.
"lastPauseTime": "A String", # Output only. Timestamp when this Schedule was last paused. Unset if never paused.
"lastResumeTime": "A String", # Output only. Timestamp when this Schedule was last resumed. Unset if never resumed from pause.
"lastScheduledRunResponse": { # Status of a scheduled run. # Output only. Response of the last scheduled run. This is the response for starting the scheduled requests and not the execution of the operations/jobs created by the requests (if applicable). Unset if no run has been scheduled yet.
"runResponse": "A String", # The response of the scheduled run.
"scheduledRunTime": "A String", # The scheduled run time based on the user-specified schedule.
},
"maxConcurrentRunCount": "A String", # Required. Maximum number of runs that can be started concurrently for this Schedule. This is the limit for starting the scheduled requests and not the execution of the operations/jobs created by the requests (if applicable).
"maxRunCount": "A String", # Optional. Maximum run count of the schedule. If specified, The schedule will be completed when either started_run_count >= max_run_count or when end_time is reached. If not specified, new runs will keep getting scheduled until this Schedule is paused or deleted. Already scheduled runs will be allowed to complete. Unset if not specified.
"name": "A String", # Immutable. The resource name of the Schedule.
"nextRunTime": "A String", # Output only. Timestamp when this Schedule should schedule the next run. Having a next_run_time in the past means the runs are being started behind schedule.
"startTime": "A String", # Optional. Timestamp after which the first run can be scheduled. Default to Schedule create time if not specified.
"startedRunCount": "A String", # Output only. The number of runs started by this schedule.
"state": "A String", # Output only. The state of this Schedule.
"updateTime": "A String", # Output only. Timestamp when this Schedule was updated.
}
list(parent, filter=None, orderBy=None, pageSize=None, pageToken=None, x__xgafv=None)
Lists Schedules in a Location.
Args:
parent: string, Required. The resource name of the Location to list the Schedules from. Format: `projects/{project}/locations/{location}` (required)
filter: string, Lists the Schedules that match the filter expression. The following fields are supported: * `display_name`: Supports `=`, `!=` comparisons, and `:` wildcard. * `state`: Supports `=` and `!=` comparisons. * `request`: Supports existence of the check. (e.g. `create_pipeline_job_request:*` --> Schedule has create_pipeline_job_request). * `create_time`: Supports `=`, `!=`, `<`, `>`, `<=`, and `>=` comparisons. Values must be in RFC 3339 format. * `start_time`: Supports `=`, `!=`, `<`, `>`, `<=`, and `>=` comparisons. Values must be in RFC 3339 format. * `end_time`: Supports `=`, `!=`, `<`, `>`, `<=`, `>=` comparisons and `:*` existence check. Values must be in RFC 3339 format. * `next_run_time`: Supports `=`, `!=`, `<`, `>`, `<=`, and `>=` comparisons. Values must be in RFC 3339 format. Filter expressions can be combined together using logical operators (`NOT`, `AND` & `OR`). The syntax to define filter expression is based on https://google.aip.dev/160. Examples: * `state="ACTIVE" AND display_name:"my_schedule_*"` * `NOT display_name="my_schedule"` * `create_time>"2021-05-18T00:00:00Z"` * `end_time>"2021-05-18T00:00:00Z" OR NOT end_time:*` * `create_pipeline_job_request:*`
orderBy: string, A comma-separated list of fields to order by. The default sort order is in ascending order. Use "desc" after a field name for descending. You can have multiple order_by fields provided. For example, using "create_time desc, end_time" will order results by create time in descending order, and if there are multiple schedules having the same create time, order them by the end time in ascending order. If order_by is not specified, it will order by default with create_time in descending order. Supported fields: * `create_time` * `start_time` * `end_time` * `next_run_time`
pageSize: integer, The standard list page size. Default to 100 if not specified.
pageToken: string, The standard list page token. Typically obtained via ListSchedulesResponse.next_page_token of the previous ScheduleService.ListSchedules call.
x__xgafv: string, V1 error format.
Allowed values
1 - v1 error format
2 - v2 error format
Returns:
An object of the form:
{ # Response message for ScheduleService.ListSchedules
"nextPageToken": "A String", # A token to retrieve the next page of results. Pass to ListSchedulesRequest.page_token to obtain that page.
"schedules": [ # List of Schedules in the requested page.
{ # An instance of a Schedule periodically schedules runs to make API calls based on user specified time specification and API request type.
"allowQueueing": True or False, # Optional. Whether new scheduled runs can be queued when max_concurrent_runs limit is reached. If set to true, new runs will be queued instead of skipped. Default to false.
"catchUp": True or False, # Output only. Whether to backfill missed runs when the schedule is resumed from PAUSED state. If set to true, all missed runs will be scheduled. New runs will be scheduled after the backfill is complete. Default to false.
"createNotebookExecutionJobRequest": { # Request message for [NotebookService.CreateNotebookExecutionJob] # Request for NotebookService.CreateNotebookExecutionJob.
"notebookExecutionJob": { # NotebookExecutionJob represents an instance of a notebook execution. # Required. The NotebookExecutionJob to create.
"createTime": "A String", # Output only. Timestamp when this NotebookExecutionJob was created.
"customEnvironmentSpec": { # Compute configuration to use for an execution job. # The custom compute configuration for an execution job.
"machineSpec": { # Specification of a single machine. # The specification of a single machine for the execution job.
"acceleratorCount": 42, # The number of accelerators to attach to the machine.
"acceleratorType": "A String", # Immutable. The type of accelerator(s) that may be attached to the machine as per accelerator_count.
"machineType": "A String", # Immutable. The type of the machine. See the [list of machine types supported for prediction](https://cloud.google.com/vertex-ai/docs/predictions/configure-compute#machine-types) See the [list of machine types supported for custom training](https://cloud.google.com/vertex-ai/docs/training/configure-compute#machine-types). For DeployedModel this field is optional, and the default value is `n1-standard-2`. For BatchPredictionJob or as part of WorkerPoolSpec this field is required.
"reservationAffinity": { # A ReservationAffinity can be used to configure a Vertex AI resource (e.g., a DeployedModel) to draw its Compute Engine resources from a Shared Reservation, or exclusively from on-demand capacity. # Optional. Immutable. Configuration controlling how this resource pool consumes reservation.
"key": "A String", # Optional. Corresponds to the label key of a reservation resource. To target a SPECIFIC_RESERVATION by name, use `compute.googleapis.com/reservation-name` as the key and specify the name of your reservation as its value.
"reservationAffinityType": "A String", # Required. Specifies the reservation affinity type.
"values": [ # Optional. Corresponds to the label values of a reservation resource. This must be the full resource name of the reservation.
"A String",
],
},
"tpuTopology": "A String", # Immutable. The topology of the TPUs. Corresponds to the TPU topologies available from GKE. (Example: tpu_topology: "2x2x1").
},
"networkSpec": { # Network spec. # The network configuration to use for the execution job.
"enableInternetAccess": True or False, # Whether to enable public internet access. Default false.
"network": "A String", # The full name of the Google Compute Engine [network](https://cloud.google.com//compute/docs/networks-and-firewalls#networks)
"subnetwork": "A String", # The name of the subnet that this instance is in. Format: `projects/{project_id_or_number}/regions/{region}/subnetworks/{subnetwork_id}`
},
"persistentDiskSpec": { # Represents the spec of persistent disk options. # The specification of a persistent disk to attach for the execution job.
"diskSizeGb": "A String", # Size in GB of the disk (default is 100GB).
"diskType": "A String", # Type of the disk (default is "pd-standard"). Valid values: "pd-ssd" (Persistent Disk Solid State Drive) "pd-standard" (Persistent Disk Hard Disk Drive) "pd-balanced" (Balanced Persistent Disk) "pd-extreme" (Extreme Persistent Disk)
},
},
"dataformRepositorySource": { # The Dataform Repository containing the input notebook. # The Dataform Repository pointing to a single file notebook repository.
"commitSha": "A String", # The commit SHA to read repository with. If unset, the file will be read at HEAD.
"dataformRepositoryResourceName": "A String", # The resource name of the Dataform Repository. Format: `projects/{project_id}/locations/{location}/repositories/{repository_id}`
},
"directNotebookSource": { # The content of the input notebook in ipynb format. # The contents of an input notebook file.
"content": "A String", # The base64-encoded contents of the input notebook file.
},
"displayName": "A String", # The display name of the NotebookExecutionJob. The name can be up to 128 characters long and can consist of any UTF-8 characters.
"encryptionSpec": { # Represents a customer-managed encryption key spec that can be applied to a top-level resource. # Customer-managed encryption key spec for the notebook execution job. This field is auto-populated if the NotebookService.NotebookRuntimeTemplate has an encryption spec.
"kmsKeyName": "A String", # Required. The Cloud KMS resource identifier of the customer managed encryption key used to protect a resource. Has the form: `projects/my-project/locations/my-region/keyRings/my-kr/cryptoKeys/my-key`. The key needs to be in the same region as where the compute resource is created.
},
"executionTimeout": "A String", # Max running time of the execution job in seconds (default 86400s / 24 hrs).
"executionUser": "A String", # The user email to run the execution as. Only supported by Colab runtimes.
"gcsNotebookSource": { # The Cloud Storage uri for the input notebook. # The Cloud Storage url pointing to the ipynb file. Format: `gs://bucket/notebook_file.ipynb`
"generation": "A String", # The version of the Cloud Storage object to read. If unset, the current version of the object is read. See https://cloud.google.com/storage/docs/metadata#generation-number.
"uri": "A String", # The Cloud Storage uri pointing to the ipynb file. Format: `gs://bucket/notebook_file.ipynb`
},
"gcsOutputUri": "A String", # The Cloud Storage location to upload the result to. Format: `gs://bucket-name`
"jobState": "A String", # Output only. The state of the NotebookExecutionJob.
"labels": { # The labels with user-defined metadata to organize NotebookExecutionJobs. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable.
"a_key": "A String",
},
"name": "A String", # Output only. The resource name of this NotebookExecutionJob. Format: `projects/{project_id}/locations/{location}/notebookExecutionJobs/{job_id}`
"notebookRuntimeTemplateResourceName": "A String", # The NotebookRuntimeTemplate to source compute configuration from.
"scheduleResourceName": "A String", # Output only. The Schedule resource name if this job is triggered by one. Format: `projects/{project_id}/locations/{location}/schedules/{schedule_id}`
"serviceAccount": "A String", # The service account to run the execution as.
"status": { # The `Status` type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by [gRPC](https://github.com/grpc). Each `Status` message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the [API Design Guide](https://cloud.google.com/apis/design/errors). # Output only. Populated when the NotebookExecutionJob is completed. When there is an error during notebook execution, the error details are populated.
"code": 42, # The status code, which should be an enum value of google.rpc.Code.
"details": [ # A list of messages that carry the error details. There is a common set of message types for APIs to use.
{
"a_key": "", # Properties of the object. Contains field @type with type URL.
},
],
"message": "A String", # A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.
},
"updateTime": "A String", # Output only. Timestamp when this NotebookExecutionJob was most recently updated.
},
"notebookExecutionJobId": "A String", # Optional. User specified ID for the NotebookExecutionJob.
"parent": "A String", # Required. The resource name of the Location to create the NotebookExecutionJob. Format: `projects/{project}/locations/{location}`
},
"createPipelineJobRequest": { # Request message for PipelineService.CreatePipelineJob. # Request for PipelineService.CreatePipelineJob. CreatePipelineJobRequest.parent field is required (format: projects/{project}/locations/{location}).
"parent": "A String", # Required. The resource name of the Location to create the PipelineJob in. Format: `projects/{project}/locations/{location}`
"pipelineJob": { # An instance of a machine learning PipelineJob. # Required. The PipelineJob to create.
"createTime": "A String", # Output only. Pipeline creation time.
"displayName": "A String", # The display name of the Pipeline. The name can be up to 128 characters long and can consist of any UTF-8 characters.
"encryptionSpec": { # Represents a customer-managed encryption key spec that can be applied to a top-level resource. # Customer-managed encryption key spec for a pipelineJob. If set, this PipelineJob and all of its sub-resources will be secured by this key.
"kmsKeyName": "A String", # Required. The Cloud KMS resource identifier of the customer managed encryption key used to protect a resource. Has the form: `projects/my-project/locations/my-region/keyRings/my-kr/cryptoKeys/my-key`. The key needs to be in the same region as where the compute resource is created.
},
"endTime": "A String", # Output only. Pipeline end time.
"error": { # The `Status` type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by [gRPC](https://github.com/grpc). Each `Status` message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the [API Design Guide](https://cloud.google.com/apis/design/errors). # Output only. The error that occurred during pipeline execution. Only populated when the pipeline's state is FAILED or CANCELLED.
"code": 42, # The status code, which should be an enum value of google.rpc.Code.
"details": [ # A list of messages that carry the error details. There is a common set of message types for APIs to use.
{
"a_key": "", # Properties of the object. Contains field @type with type URL.
},
],
"message": "A String", # A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.
},
"jobDetail": { # The runtime detail of PipelineJob. # Output only. The details of pipeline run. Not available in the list view.
"pipelineContext": { # Instance of a general context. # Output only. The context of the pipeline.
"createTime": "A String", # Output only. Timestamp when this Context was created.
"description": "A String", # Description of the Context
"displayName": "A String", # User provided display name of the Context. May be up to 128 Unicode characters.
"etag": "A String", # An eTag used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
"labels": { # The labels with user-defined metadata to organize your Contexts. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one Context (System labels are excluded).
"a_key": "A String",
},
"metadata": { # Properties of the Context. Top level metadata keys' heading and trailing spaces will be trimmed. The size of this field should not exceed 200KB.
"a_key": "", # Properties of the object.
},
"name": "A String", # Immutable. The resource name of the Context.
"parentContexts": [ # Output only. A list of resource names of Contexts that are parents of this Context. A Context may have at most 10 parent_contexts.
"A String",
],
"schemaTitle": "A String", # The title of the schema describing the metadata. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.
"schemaVersion": "A String", # The version of the schema in schema_name to use. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.
"updateTime": "A String", # Output only. Timestamp when this Context was last updated.
},
"pipelineRunContext": { # Instance of a general context. # Output only. The context of the current pipeline run.
"createTime": "A String", # Output only. Timestamp when this Context was created.
"description": "A String", # Description of the Context
"displayName": "A String", # User provided display name of the Context. May be up to 128 Unicode characters.
"etag": "A String", # An eTag used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
"labels": { # The labels with user-defined metadata to organize your Contexts. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one Context (System labels are excluded).
"a_key": "A String",
},
"metadata": { # Properties of the Context. Top level metadata keys' heading and trailing spaces will be trimmed. The size of this field should not exceed 200KB.
"a_key": "", # Properties of the object.
},
"name": "A String", # Immutable. The resource name of the Context.
"parentContexts": [ # Output only. A list of resource names of Contexts that are parents of this Context. A Context may have at most 10 parent_contexts.
"A String",
],
"schemaTitle": "A String", # The title of the schema describing the metadata. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.
"schemaVersion": "A String", # The version of the schema in schema_name to use. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.
"updateTime": "A String", # Output only. Timestamp when this Context was last updated.
},
"taskDetails": [ # Output only. The runtime details of the tasks under the pipeline.
{ # The runtime detail of a task execution.
"createTime": "A String", # Output only. Task create time.
"endTime": "A String", # Output only. Task end time.
"error": { # The `Status` type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by [gRPC](https://github.com/grpc). Each `Status` message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the [API Design Guide](https://cloud.google.com/apis/design/errors). # Output only. The error that occurred during task execution. Only populated when the task's state is FAILED or CANCELLED.
"code": 42, # The status code, which should be an enum value of google.rpc.Code.
"details": [ # A list of messages that carry the error details. There is a common set of message types for APIs to use.
{
"a_key": "", # Properties of the object. Contains field @type with type URL.
},
],
"message": "A String", # A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.
},
"execution": { # Instance of a general execution. # Output only. The execution metadata of the task.
"createTime": "A String", # Output only. Timestamp when this Execution was created.
"description": "A String", # Description of the Execution
"displayName": "A String", # User provided display name of the Execution. May be up to 128 Unicode characters.
"etag": "A String", # An eTag used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
"labels": { # The labels with user-defined metadata to organize your Executions. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one Execution (System labels are excluded).
"a_key": "A String",
},
"metadata": { # Properties of the Execution. Top level metadata keys' heading and trailing spaces will be trimmed. The size of this field should not exceed 200KB.
"a_key": "", # Properties of the object.
},
"name": "A String", # Output only. The resource name of the Execution.
"schemaTitle": "A String", # The title of the schema describing the metadata. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.
"schemaVersion": "A String", # The version of the schema in `schema_title` to use. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.
"state": "A String", # The state of this Execution. This is a property of the Execution, and does not imply or capture any ongoing process. This property is managed by clients (such as Vertex AI Pipelines) and the system does not prescribe or check the validity of state transitions.
"updateTime": "A String", # Output only. Timestamp when this Execution was last updated.
},
"executorDetail": { # The runtime detail of a pipeline executor. # Output only. The detailed execution info.
"containerDetail": { # The detail of a container execution. It contains the job names of the lifecycle of a container execution. # Output only. The detailed info for a container executor.
"failedMainJobs": [ # Output only. The names of the previously failed CustomJob for the main container executions. The list includes the all attempts in chronological order.
"A String",
],
"failedPreCachingCheckJobs": [ # Output only. The names of the previously failed CustomJob for the pre-caching-check container executions. This job will be available if the PipelineJob.pipeline_spec specifies the `pre_caching_check` hook in the lifecycle events. The list includes the all attempts in chronological order.
"A String",
],
"mainJob": "A String", # Output only. The name of the CustomJob for the main container execution.
"preCachingCheckJob": "A String", # Output only. The name of the CustomJob for the pre-caching-check container execution. This job will be available if the PipelineJob.pipeline_spec specifies the `pre_caching_check` hook in the lifecycle events.
},
"customJobDetail": { # The detailed info for a custom job executor. # Output only. The detailed info for a custom job executor.
"failedJobs": [ # Output only. The names of the previously failed CustomJob. The list includes the all attempts in chronological order.
"A String",
],
"job": "A String", # Output only. The name of the CustomJob.
},
},
"inputs": { # Output only. The runtime input artifacts of the task.
"a_key": { # A list of artifact metadata.
"artifacts": [ # Output only. A list of artifact metadata.
{ # Instance of a general artifact.
"createTime": "A String", # Output only. Timestamp when this Artifact was created.
"description": "A String", # Description of the Artifact
"displayName": "A String", # User provided display name of the Artifact. May be up to 128 Unicode characters.
"etag": "A String", # An eTag used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
"labels": { # The labels with user-defined metadata to organize your Artifacts. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one Artifact (System labels are excluded).
"a_key": "A String",
},
"metadata": { # Properties of the Artifact. Top level metadata keys' heading and trailing spaces will be trimmed. The size of this field should not exceed 200KB.
"a_key": "", # Properties of the object.
},
"name": "A String", # Output only. The resource name of the Artifact.
"schemaTitle": "A String", # The title of the schema describing the metadata. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.
"schemaVersion": "A String", # The version of the schema in schema_name to use. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.
"state": "A String", # The state of this Artifact. This is a property of the Artifact, and does not imply or capture any ongoing process. This property is managed by clients (such as Vertex AI Pipelines), and the system does not prescribe or check the validity of state transitions.
"updateTime": "A String", # Output only. Timestamp when this Artifact was last updated.
"uri": "A String", # The uniform resource identifier of the artifact file. May be empty if there is no actual artifact file.
},
],
},
},
"outputs": { # Output only. The runtime output artifacts of the task.
"a_key": { # A list of artifact metadata.
"artifacts": [ # Output only. A list of artifact metadata.
{ # Instance of a general artifact.
"createTime": "A String", # Output only. Timestamp when this Artifact was created.
"description": "A String", # Description of the Artifact
"displayName": "A String", # User provided display name of the Artifact. May be up to 128 Unicode characters.
"etag": "A String", # An eTag used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
"labels": { # The labels with user-defined metadata to organize your Artifacts. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one Artifact (System labels are excluded).
"a_key": "A String",
},
"metadata": { # Properties of the Artifact. Top level metadata keys' heading and trailing spaces will be trimmed. The size of this field should not exceed 200KB.
"a_key": "", # Properties of the object.
},
"name": "A String", # Output only. The resource name of the Artifact.
"schemaTitle": "A String", # The title of the schema describing the metadata. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.
"schemaVersion": "A String", # The version of the schema in schema_name to use. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.
"state": "A String", # The state of this Artifact. This is a property of the Artifact, and does not imply or capture any ongoing process. This property is managed by clients (such as Vertex AI Pipelines), and the system does not prescribe or check the validity of state transitions.
"updateTime": "A String", # Output only. Timestamp when this Artifact was last updated.
"uri": "A String", # The uniform resource identifier of the artifact file. May be empty if there is no actual artifact file.
},
],
},
},
"parentTaskId": "A String", # Output only. The id of the parent task if the task is within a component scope. Empty if the task is at the root level.
"pipelineTaskStatus": [ # Output only. A list of task status. This field keeps a record of task status evolving over time.
{ # A single record of the task status.
"error": { # The `Status` type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by [gRPC](https://github.com/grpc). Each `Status` message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the [API Design Guide](https://cloud.google.com/apis/design/errors). # Output only. The error that occurred during the state. May be set when the state is any of the non-final state (PENDING/RUNNING/CANCELLING) or FAILED state. If the state is FAILED, the error here is final and not going to be retried. If the state is a non-final state, the error indicates a system-error being retried.
"code": 42, # The status code, which should be an enum value of google.rpc.Code.
"details": [ # A list of messages that carry the error details. There is a common set of message types for APIs to use.
{
"a_key": "", # Properties of the object. Contains field @type with type URL.
},
],
"message": "A String", # A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.
},
"state": "A String", # Output only. The state of the task.
"updateTime": "A String", # Output only. Update time of this status.
},
],
"startTime": "A String", # Output only. Task start time.
"state": "A String", # Output only. State of the task.
"taskId": "A String", # Output only. The system generated ID of the task.
"taskName": "A String", # Output only. The user specified name of the task that is defined in pipeline_spec.
},
],
},
"labels": { # The labels with user-defined metadata to organize PipelineJob. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels. Note there is some reserved label key for Vertex AI Pipelines. - `vertex-ai-pipelines-run-billing-id`, user set value will get overrided.
"a_key": "A String",
},
"name": "A String", # Output only. The resource name of the PipelineJob.
"network": "A String", # The full name of the Compute Engine [network](/compute/docs/networks-and-firewalls#networks) to which the Pipeline Job's workload should be peered. For example, `projects/12345/global/networks/myVPC`. [Format](/compute/docs/reference/rest/v1/networks/insert) is of the form `projects/{project}/global/networks/{network}`. Where {project} is a project number, as in `12345`, and {network} is a network name. Private services access must already be configured for the network. Pipeline job will apply the network configuration to the Google Cloud resources being launched, if applied, such as Vertex AI Training or Dataflow job. If left unspecified, the workload is not peered with any network.
"pipelineSpec": { # The spec of the pipeline.
"a_key": "", # Properties of the object.
},
"preflightValidations": True or False, # Optional. Whether to do component level validations before job creation.
"reservedIpRanges": [ # A list of names for the reserved ip ranges under the VPC network that can be used for this Pipeline Job's workload. If set, we will deploy the Pipeline Job's workload within the provided ip ranges. Otherwise, the job will be deployed to any ip ranges under the provided VPC network. Example: ['vertex-ai-ip-range'].
"A String",
],
"runtimeConfig": { # The runtime config of a PipelineJob. # Runtime config of the pipeline.
"failurePolicy": "A String", # Represents the failure policy of a pipeline. Currently, the default of a pipeline is that the pipeline will continue to run until no more tasks can be executed, also known as PIPELINE_FAILURE_POLICY_FAIL_SLOW. However, if a pipeline is set to PIPELINE_FAILURE_POLICY_FAIL_FAST, it will stop scheduling any new tasks when a task has failed. Any scheduled tasks will continue to completion.
"gcsOutputDirectory": "A String", # Required. A path in a Cloud Storage bucket, which will be treated as the root output directory of the pipeline. It is used by the system to generate the paths of output artifacts. The artifact paths are generated with a sub-path pattern `{job_id}/{task_id}/{output_key}` under the specified output directory. The service account specified in this pipeline must have the `storage.objects.get` and `storage.objects.create` permissions for this bucket.
"inputArtifacts": { # The runtime artifacts of the PipelineJob. The key will be the input artifact name and the value would be one of the InputArtifact.
"a_key": { # The type of an input artifact.
"artifactId": "A String", # Artifact resource id from MLMD. Which is the last portion of an artifact resource name: `projects/{project}/locations/{location}/metadataStores/default/artifacts/{artifact_id}`. The artifact must stay within the same project, location and default metadatastore as the pipeline.
},
},
"parameterValues": { # The runtime parameters of the PipelineJob. The parameters will be passed into PipelineJob.pipeline_spec to replace the placeholders at runtime. This field is used by pipelines built using `PipelineJob.pipeline_spec.schema_version` 2.1.0, such as pipelines built using Kubeflow Pipelines SDK 1.9 or higher and the v2 DSL.
"a_key": "",
},
"parameters": { # Deprecated. Use RuntimeConfig.parameter_values instead. The runtime parameters of the PipelineJob. The parameters will be passed into PipelineJob.pipeline_spec to replace the placeholders at runtime. This field is used by pipelines built using `PipelineJob.pipeline_spec.schema_version` 2.0.0 or lower, such as pipelines built using Kubeflow Pipelines SDK 1.8 or lower.
"a_key": { # Value is the value of the field.
"doubleValue": 3.14, # A double value.
"intValue": "A String", # An integer value.
"stringValue": "A String", # A string value.
},
},
},
"scheduleName": "A String", # Output only. The schedule resource name. Only returned if the Pipeline is created by Schedule API.
"serviceAccount": "A String", # The service account that the pipeline workload runs as. If not specified, the Compute Engine default service account in the project will be used. See https://cloud.google.com/compute/docs/access/service-accounts#default_service_account Users starting the pipeline must have the `iam.serviceAccounts.actAs` permission on this service account.
"startTime": "A String", # Output only. Pipeline start time.
"state": "A String", # Output only. The detailed state of the job.
"templateMetadata": { # Pipeline template metadata if PipelineJob.template_uri is from supported template registry. Currently, the only supported registry is Artifact Registry. # Output only. Pipeline template metadata. Will fill up fields if PipelineJob.template_uri is from supported template registry.
"version": "A String", # The version_name in artifact registry. Will always be presented in output if the PipelineJob.template_uri is from supported template registry. Format is "sha256:abcdef123456...".
},
"templateUri": "A String", # A template uri from where the PipelineJob.pipeline_spec, if empty, will be downloaded. Currently, only uri from Vertex Template Registry & Gallery is supported. Reference to https://cloud.google.com/vertex-ai/docs/pipelines/create-pipeline-template.
"updateTime": "A String", # Output only. Timestamp when this PipelineJob was most recently updated.
},
"pipelineJobId": "A String", # The ID to use for the PipelineJob, which will become the final component of the PipelineJob name. If not provided, an ID will be automatically generated. This value should be less than 128 characters, and valid characters are `/a-z-/`.
},
"createTime": "A String", # Output only. Timestamp when this Schedule was created.
"cron": "A String", # Cron schedule (https://en.wikipedia.org/wiki/Cron) to launch scheduled runs. To explicitly set a timezone to the cron tab, apply a prefix in the cron tab: "CRON_TZ=${IANA_TIME_ZONE}" or "TZ=${IANA_TIME_ZONE}". The ${IANA_TIME_ZONE} may only be a valid string from IANA time zone database. For example, "CRON_TZ=America/New_York 1 * * * *", or "TZ=America/New_York 1 * * * *".
"displayName": "A String", # Required. User provided name of the Schedule. The name can be up to 128 characters long and can consist of any UTF-8 characters.
"endTime": "A String", # Optional. Timestamp after which no new runs can be scheduled. If specified, The schedule will be completed when either end_time is reached or when scheduled_run_count >= max_run_count. If not specified, new runs will keep getting scheduled until this Schedule is paused or deleted. Already scheduled runs will be allowed to complete. Unset if not specified.
"lastPauseTime": "A String", # Output only. Timestamp when this Schedule was last paused. Unset if never paused.
"lastResumeTime": "A String", # Output only. Timestamp when this Schedule was last resumed. Unset if never resumed from pause.
"lastScheduledRunResponse": { # Status of a scheduled run. # Output only. Response of the last scheduled run. This is the response for starting the scheduled requests and not the execution of the operations/jobs created by the requests (if applicable). Unset if no run has been scheduled yet.
"runResponse": "A String", # The response of the scheduled run.
"scheduledRunTime": "A String", # The scheduled run time based on the user-specified schedule.
},
"maxConcurrentRunCount": "A String", # Required. Maximum number of runs that can be started concurrently for this Schedule. This is the limit for starting the scheduled requests and not the execution of the operations/jobs created by the requests (if applicable).
"maxRunCount": "A String", # Optional. Maximum run count of the schedule. If specified, The schedule will be completed when either started_run_count >= max_run_count or when end_time is reached. If not specified, new runs will keep getting scheduled until this Schedule is paused or deleted. Already scheduled runs will be allowed to complete. Unset if not specified.
"name": "A String", # Immutable. The resource name of the Schedule.
"nextRunTime": "A String", # Output only. Timestamp when this Schedule should schedule the next run. Having a next_run_time in the past means the runs are being started behind schedule.
"startTime": "A String", # Optional. Timestamp after which the first run can be scheduled. Default to Schedule create time if not specified.
"startedRunCount": "A String", # Output only. The number of runs started by this schedule.
"state": "A String", # Output only. The state of this Schedule.
"updateTime": "A String", # Output only. Timestamp when this Schedule was updated.
},
],
}
list_next()
Retrieves the next page of results.
Args:
previous_request: The request for the previous page. (required)
previous_response: The response from the request for the previous page. (required)
Returns:
A request object that you can call 'execute()' on to request the next
page. Returns None if there are no more items in the collection.
patch(name, body=None, updateMask=None, x__xgafv=None)
Updates an active or paused Schedule. When the Schedule is updated, new runs will be scheduled starting from the updated next execution time after the update time based on the time_specification in the updated Schedule. All unstarted runs before the update time will be skipped while already created runs will NOT be paused or canceled.
Args:
name: string, Immutable. The resource name of the Schedule. (required)
body: object, The request body.
The object takes the form of:
{ # An instance of a Schedule periodically schedules runs to make API calls based on user specified time specification and API request type.
"allowQueueing": True or False, # Optional. Whether new scheduled runs can be queued when max_concurrent_runs limit is reached. If set to true, new runs will be queued instead of skipped. Default to false.
"catchUp": True or False, # Output only. Whether to backfill missed runs when the schedule is resumed from PAUSED state. If set to true, all missed runs will be scheduled. New runs will be scheduled after the backfill is complete. Default to false.
"createNotebookExecutionJobRequest": { # Request message for [NotebookService.CreateNotebookExecutionJob] # Request for NotebookService.CreateNotebookExecutionJob.
"notebookExecutionJob": { # NotebookExecutionJob represents an instance of a notebook execution. # Required. The NotebookExecutionJob to create.
"createTime": "A String", # Output only. Timestamp when this NotebookExecutionJob was created.
"customEnvironmentSpec": { # Compute configuration to use for an execution job. # The custom compute configuration for an execution job.
"machineSpec": { # Specification of a single machine. # The specification of a single machine for the execution job.
"acceleratorCount": 42, # The number of accelerators to attach to the machine.
"acceleratorType": "A String", # Immutable. The type of accelerator(s) that may be attached to the machine as per accelerator_count.
"machineType": "A String", # Immutable. The type of the machine. See the [list of machine types supported for prediction](https://cloud.google.com/vertex-ai/docs/predictions/configure-compute#machine-types) See the [list of machine types supported for custom training](https://cloud.google.com/vertex-ai/docs/training/configure-compute#machine-types). For DeployedModel this field is optional, and the default value is `n1-standard-2`. For BatchPredictionJob or as part of WorkerPoolSpec this field is required.
"reservationAffinity": { # A ReservationAffinity can be used to configure a Vertex AI resource (e.g., a DeployedModel) to draw its Compute Engine resources from a Shared Reservation, or exclusively from on-demand capacity. # Optional. Immutable. Configuration controlling how this resource pool consumes reservation.
"key": "A String", # Optional. Corresponds to the label key of a reservation resource. To target a SPECIFIC_RESERVATION by name, use `compute.googleapis.com/reservation-name` as the key and specify the name of your reservation as its value.
"reservationAffinityType": "A String", # Required. Specifies the reservation affinity type.
"values": [ # Optional. Corresponds to the label values of a reservation resource. This must be the full resource name of the reservation.
"A String",
],
},
"tpuTopology": "A String", # Immutable. The topology of the TPUs. Corresponds to the TPU topologies available from GKE. (Example: tpu_topology: "2x2x1").
},
"networkSpec": { # Network spec. # The network configuration to use for the execution job.
"enableInternetAccess": True or False, # Whether to enable public internet access. Default false.
"network": "A String", # The full name of the Google Compute Engine [network](https://cloud.google.com//compute/docs/networks-and-firewalls#networks)
"subnetwork": "A String", # The name of the subnet that this instance is in. Format: `projects/{project_id_or_number}/regions/{region}/subnetworks/{subnetwork_id}`
},
"persistentDiskSpec": { # Represents the spec of persistent disk options. # The specification of a persistent disk to attach for the execution job.
"diskSizeGb": "A String", # Size in GB of the disk (default is 100GB).
"diskType": "A String", # Type of the disk (default is "pd-standard"). Valid values: "pd-ssd" (Persistent Disk Solid State Drive) "pd-standard" (Persistent Disk Hard Disk Drive) "pd-balanced" (Balanced Persistent Disk) "pd-extreme" (Extreme Persistent Disk)
},
},
"dataformRepositorySource": { # The Dataform Repository containing the input notebook. # The Dataform Repository pointing to a single file notebook repository.
"commitSha": "A String", # The commit SHA to read repository with. If unset, the file will be read at HEAD.
"dataformRepositoryResourceName": "A String", # The resource name of the Dataform Repository. Format: `projects/{project_id}/locations/{location}/repositories/{repository_id}`
},
"directNotebookSource": { # The content of the input notebook in ipynb format. # The contents of an input notebook file.
"content": "A String", # The base64-encoded contents of the input notebook file.
},
"displayName": "A String", # The display name of the NotebookExecutionJob. The name can be up to 128 characters long and can consist of any UTF-8 characters.
"encryptionSpec": { # Represents a customer-managed encryption key spec that can be applied to a top-level resource. # Customer-managed encryption key spec for the notebook execution job. This field is auto-populated if the NotebookService.NotebookRuntimeTemplate has an encryption spec.
"kmsKeyName": "A String", # Required. The Cloud KMS resource identifier of the customer managed encryption key used to protect a resource. Has the form: `projects/my-project/locations/my-region/keyRings/my-kr/cryptoKeys/my-key`. The key needs to be in the same region as where the compute resource is created.
},
"executionTimeout": "A String", # Max running time of the execution job in seconds (default 86400s / 24 hrs).
"executionUser": "A String", # The user email to run the execution as. Only supported by Colab runtimes.
"gcsNotebookSource": { # The Cloud Storage uri for the input notebook. # The Cloud Storage url pointing to the ipynb file. Format: `gs://bucket/notebook_file.ipynb`
"generation": "A String", # The version of the Cloud Storage object to read. If unset, the current version of the object is read. See https://cloud.google.com/storage/docs/metadata#generation-number.
"uri": "A String", # The Cloud Storage uri pointing to the ipynb file. Format: `gs://bucket/notebook_file.ipynb`
},
"gcsOutputUri": "A String", # The Cloud Storage location to upload the result to. Format: `gs://bucket-name`
"jobState": "A String", # Output only. The state of the NotebookExecutionJob.
"labels": { # The labels with user-defined metadata to organize NotebookExecutionJobs. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable.
"a_key": "A String",
},
"name": "A String", # Output only. The resource name of this NotebookExecutionJob. Format: `projects/{project_id}/locations/{location}/notebookExecutionJobs/{job_id}`
"notebookRuntimeTemplateResourceName": "A String", # The NotebookRuntimeTemplate to source compute configuration from.
"scheduleResourceName": "A String", # Output only. The Schedule resource name if this job is triggered by one. Format: `projects/{project_id}/locations/{location}/schedules/{schedule_id}`
"serviceAccount": "A String", # The service account to run the execution as.
"status": { # The `Status` type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by [gRPC](https://github.com/grpc). Each `Status` message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the [API Design Guide](https://cloud.google.com/apis/design/errors). # Output only. Populated when the NotebookExecutionJob is completed. When there is an error during notebook execution, the error details are populated.
"code": 42, # The status code, which should be an enum value of google.rpc.Code.
"details": [ # A list of messages that carry the error details. There is a common set of message types for APIs to use.
{
"a_key": "", # Properties of the object. Contains field @type with type URL.
},
],
"message": "A String", # A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.
},
"updateTime": "A String", # Output only. Timestamp when this NotebookExecutionJob was most recently updated.
},
"notebookExecutionJobId": "A String", # Optional. User specified ID for the NotebookExecutionJob.
"parent": "A String", # Required. The resource name of the Location to create the NotebookExecutionJob. Format: `projects/{project}/locations/{location}`
},
"createPipelineJobRequest": { # Request message for PipelineService.CreatePipelineJob. # Request for PipelineService.CreatePipelineJob. CreatePipelineJobRequest.parent field is required (format: projects/{project}/locations/{location}).
"parent": "A String", # Required. The resource name of the Location to create the PipelineJob in. Format: `projects/{project}/locations/{location}`
"pipelineJob": { # An instance of a machine learning PipelineJob. # Required. The PipelineJob to create.
"createTime": "A String", # Output only. Pipeline creation time.
"displayName": "A String", # The display name of the Pipeline. The name can be up to 128 characters long and can consist of any UTF-8 characters.
"encryptionSpec": { # Represents a customer-managed encryption key spec that can be applied to a top-level resource. # Customer-managed encryption key spec for a pipelineJob. If set, this PipelineJob and all of its sub-resources will be secured by this key.
"kmsKeyName": "A String", # Required. The Cloud KMS resource identifier of the customer managed encryption key used to protect a resource. Has the form: `projects/my-project/locations/my-region/keyRings/my-kr/cryptoKeys/my-key`. The key needs to be in the same region as where the compute resource is created.
},
"endTime": "A String", # Output only. Pipeline end time.
"error": { # The `Status` type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by [gRPC](https://github.com/grpc). Each `Status` message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the [API Design Guide](https://cloud.google.com/apis/design/errors). # Output only. The error that occurred during pipeline execution. Only populated when the pipeline's state is FAILED or CANCELLED.
"code": 42, # The status code, which should be an enum value of google.rpc.Code.
"details": [ # A list of messages that carry the error details. There is a common set of message types for APIs to use.
{
"a_key": "", # Properties of the object. Contains field @type with type URL.
},
],
"message": "A String", # A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.
},
"jobDetail": { # The runtime detail of PipelineJob. # Output only. The details of pipeline run. Not available in the list view.
"pipelineContext": { # Instance of a general context. # Output only. The context of the pipeline.
"createTime": "A String", # Output only. Timestamp when this Context was created.
"description": "A String", # Description of the Context
"displayName": "A String", # User provided display name of the Context. May be up to 128 Unicode characters.
"etag": "A String", # An eTag used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
"labels": { # The labels with user-defined metadata to organize your Contexts. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one Context (System labels are excluded).
"a_key": "A String",
},
"metadata": { # Properties of the Context. Top level metadata keys' heading and trailing spaces will be trimmed. The size of this field should not exceed 200KB.
"a_key": "", # Properties of the object.
},
"name": "A String", # Immutable. The resource name of the Context.
"parentContexts": [ # Output only. A list of resource names of Contexts that are parents of this Context. A Context may have at most 10 parent_contexts.
"A String",
],
"schemaTitle": "A String", # The title of the schema describing the metadata. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.
"schemaVersion": "A String", # The version of the schema in schema_name to use. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.
"updateTime": "A String", # Output only. Timestamp when this Context was last updated.
},
"pipelineRunContext": { # Instance of a general context. # Output only. The context of the current pipeline run.
"createTime": "A String", # Output only. Timestamp when this Context was created.
"description": "A String", # Description of the Context
"displayName": "A String", # User provided display name of the Context. May be up to 128 Unicode characters.
"etag": "A String", # An eTag used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
"labels": { # The labels with user-defined metadata to organize your Contexts. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one Context (System labels are excluded).
"a_key": "A String",
},
"metadata": { # Properties of the Context. Top level metadata keys' heading and trailing spaces will be trimmed. The size of this field should not exceed 200KB.
"a_key": "", # Properties of the object.
},
"name": "A String", # Immutable. The resource name of the Context.
"parentContexts": [ # Output only. A list of resource names of Contexts that are parents of this Context. A Context may have at most 10 parent_contexts.
"A String",
],
"schemaTitle": "A String", # The title of the schema describing the metadata. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.
"schemaVersion": "A String", # The version of the schema in schema_name to use. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.
"updateTime": "A String", # Output only. Timestamp when this Context was last updated.
},
"taskDetails": [ # Output only. The runtime details of the tasks under the pipeline.
{ # The runtime detail of a task execution.
"createTime": "A String", # Output only. Task create time.
"endTime": "A String", # Output only. Task end time.
"error": { # The `Status` type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by [gRPC](https://github.com/grpc). Each `Status` message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the [API Design Guide](https://cloud.google.com/apis/design/errors). # Output only. The error that occurred during task execution. Only populated when the task's state is FAILED or CANCELLED.
"code": 42, # The status code, which should be an enum value of google.rpc.Code.
"details": [ # A list of messages that carry the error details. There is a common set of message types for APIs to use.
{
"a_key": "", # Properties of the object. Contains field @type with type URL.
},
],
"message": "A String", # A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.
},
"execution": { # Instance of a general execution. # Output only. The execution metadata of the task.
"createTime": "A String", # Output only. Timestamp when this Execution was created.
"description": "A String", # Description of the Execution
"displayName": "A String", # User provided display name of the Execution. May be up to 128 Unicode characters.
"etag": "A String", # An eTag used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
"labels": { # The labels with user-defined metadata to organize your Executions. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one Execution (System labels are excluded).
"a_key": "A String",
},
"metadata": { # Properties of the Execution. Top level metadata keys' heading and trailing spaces will be trimmed. The size of this field should not exceed 200KB.
"a_key": "", # Properties of the object.
},
"name": "A String", # Output only. The resource name of the Execution.
"schemaTitle": "A String", # The title of the schema describing the metadata. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.
"schemaVersion": "A String", # The version of the schema in `schema_title` to use. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.
"state": "A String", # The state of this Execution. This is a property of the Execution, and does not imply or capture any ongoing process. This property is managed by clients (such as Vertex AI Pipelines) and the system does not prescribe or check the validity of state transitions.
"updateTime": "A String", # Output only. Timestamp when this Execution was last updated.
},
"executorDetail": { # The runtime detail of a pipeline executor. # Output only. The detailed execution info.
"containerDetail": { # The detail of a container execution. It contains the job names of the lifecycle of a container execution. # Output only. The detailed info for a container executor.
"failedMainJobs": [ # Output only. The names of the previously failed CustomJob for the main container executions. The list includes the all attempts in chronological order.
"A String",
],
"failedPreCachingCheckJobs": [ # Output only. The names of the previously failed CustomJob for the pre-caching-check container executions. This job will be available if the PipelineJob.pipeline_spec specifies the `pre_caching_check` hook in the lifecycle events. The list includes the all attempts in chronological order.
"A String",
],
"mainJob": "A String", # Output only. The name of the CustomJob for the main container execution.
"preCachingCheckJob": "A String", # Output only. The name of the CustomJob for the pre-caching-check container execution. This job will be available if the PipelineJob.pipeline_spec specifies the `pre_caching_check` hook in the lifecycle events.
},
"customJobDetail": { # The detailed info for a custom job executor. # Output only. The detailed info for a custom job executor.
"failedJobs": [ # Output only. The names of the previously failed CustomJob. The list includes the all attempts in chronological order.
"A String",
],
"job": "A String", # Output only. The name of the CustomJob.
},
},
"inputs": { # Output only. The runtime input artifacts of the task.
"a_key": { # A list of artifact metadata.
"artifacts": [ # Output only. A list of artifact metadata.
{ # Instance of a general artifact.
"createTime": "A String", # Output only. Timestamp when this Artifact was created.
"description": "A String", # Description of the Artifact
"displayName": "A String", # User provided display name of the Artifact. May be up to 128 Unicode characters.
"etag": "A String", # An eTag used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
"labels": { # The labels with user-defined metadata to organize your Artifacts. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one Artifact (System labels are excluded).
"a_key": "A String",
},
"metadata": { # Properties of the Artifact. Top level metadata keys' heading and trailing spaces will be trimmed. The size of this field should not exceed 200KB.
"a_key": "", # Properties of the object.
},
"name": "A String", # Output only. The resource name of the Artifact.
"schemaTitle": "A String", # The title of the schema describing the metadata. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.
"schemaVersion": "A String", # The version of the schema in schema_name to use. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.
"state": "A String", # The state of this Artifact. This is a property of the Artifact, and does not imply or capture any ongoing process. This property is managed by clients (such as Vertex AI Pipelines), and the system does not prescribe or check the validity of state transitions.
"updateTime": "A String", # Output only. Timestamp when this Artifact was last updated.
"uri": "A String", # The uniform resource identifier of the artifact file. May be empty if there is no actual artifact file.
},
],
},
},
"outputs": { # Output only. The runtime output artifacts of the task.
"a_key": { # A list of artifact metadata.
"artifacts": [ # Output only. A list of artifact metadata.
{ # Instance of a general artifact.
"createTime": "A String", # Output only. Timestamp when this Artifact was created.
"description": "A String", # Description of the Artifact
"displayName": "A String", # User provided display name of the Artifact. May be up to 128 Unicode characters.
"etag": "A String", # An eTag used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
"labels": { # The labels with user-defined metadata to organize your Artifacts. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one Artifact (System labels are excluded).
"a_key": "A String",
},
"metadata": { # Properties of the Artifact. Top level metadata keys' heading and trailing spaces will be trimmed. The size of this field should not exceed 200KB.
"a_key": "", # Properties of the object.
},
"name": "A String", # Output only. The resource name of the Artifact.
"schemaTitle": "A String", # The title of the schema describing the metadata. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.
"schemaVersion": "A String", # The version of the schema in schema_name to use. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.
"state": "A String", # The state of this Artifact. This is a property of the Artifact, and does not imply or capture any ongoing process. This property is managed by clients (such as Vertex AI Pipelines), and the system does not prescribe or check the validity of state transitions.
"updateTime": "A String", # Output only. Timestamp when this Artifact was last updated.
"uri": "A String", # The uniform resource identifier of the artifact file. May be empty if there is no actual artifact file.
},
],
},
},
"parentTaskId": "A String", # Output only. The id of the parent task if the task is within a component scope. Empty if the task is at the root level.
"pipelineTaskStatus": [ # Output only. A list of task status. This field keeps a record of task status evolving over time.
{ # A single record of the task status.
"error": { # The `Status` type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by [gRPC](https://github.com/grpc). Each `Status` message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the [API Design Guide](https://cloud.google.com/apis/design/errors). # Output only. The error that occurred during the state. May be set when the state is any of the non-final state (PENDING/RUNNING/CANCELLING) or FAILED state. If the state is FAILED, the error here is final and not going to be retried. If the state is a non-final state, the error indicates a system-error being retried.
"code": 42, # The status code, which should be an enum value of google.rpc.Code.
"details": [ # A list of messages that carry the error details. There is a common set of message types for APIs to use.
{
"a_key": "", # Properties of the object. Contains field @type with type URL.
},
],
"message": "A String", # A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.
},
"state": "A String", # Output only. The state of the task.
"updateTime": "A String", # Output only. Update time of this status.
},
],
"startTime": "A String", # Output only. Task start time.
"state": "A String", # Output only. State of the task.
"taskId": "A String", # Output only. The system generated ID of the task.
"taskName": "A String", # Output only. The user specified name of the task that is defined in pipeline_spec.
},
],
},
"labels": { # The labels with user-defined metadata to organize PipelineJob. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels. Note there is some reserved label key for Vertex AI Pipelines. - `vertex-ai-pipelines-run-billing-id`, user set value will get overrided.
"a_key": "A String",
},
"name": "A String", # Output only. The resource name of the PipelineJob.
"network": "A String", # The full name of the Compute Engine [network](/compute/docs/networks-and-firewalls#networks) to which the Pipeline Job's workload should be peered. For example, `projects/12345/global/networks/myVPC`. [Format](/compute/docs/reference/rest/v1/networks/insert) is of the form `projects/{project}/global/networks/{network}`. Where {project} is a project number, as in `12345`, and {network} is a network name. Private services access must already be configured for the network. Pipeline job will apply the network configuration to the Google Cloud resources being launched, if applied, such as Vertex AI Training or Dataflow job. If left unspecified, the workload is not peered with any network.
"pipelineSpec": { # The spec of the pipeline.
"a_key": "", # Properties of the object.
},
"preflightValidations": True or False, # Optional. Whether to do component level validations before job creation.
"reservedIpRanges": [ # A list of names for the reserved ip ranges under the VPC network that can be used for this Pipeline Job's workload. If set, we will deploy the Pipeline Job's workload within the provided ip ranges. Otherwise, the job will be deployed to any ip ranges under the provided VPC network. Example: ['vertex-ai-ip-range'].
"A String",
],
"runtimeConfig": { # The runtime config of a PipelineJob. # Runtime config of the pipeline.
"failurePolicy": "A String", # Represents the failure policy of a pipeline. Currently, the default of a pipeline is that the pipeline will continue to run until no more tasks can be executed, also known as PIPELINE_FAILURE_POLICY_FAIL_SLOW. However, if a pipeline is set to PIPELINE_FAILURE_POLICY_FAIL_FAST, it will stop scheduling any new tasks when a task has failed. Any scheduled tasks will continue to completion.
"gcsOutputDirectory": "A String", # Required. A path in a Cloud Storage bucket, which will be treated as the root output directory of the pipeline. It is used by the system to generate the paths of output artifacts. The artifact paths are generated with a sub-path pattern `{job_id}/{task_id}/{output_key}` under the specified output directory. The service account specified in this pipeline must have the `storage.objects.get` and `storage.objects.create` permissions for this bucket.
"inputArtifacts": { # The runtime artifacts of the PipelineJob. The key will be the input artifact name and the value would be one of the InputArtifact.
"a_key": { # The type of an input artifact.
"artifactId": "A String", # Artifact resource id from MLMD. Which is the last portion of an artifact resource name: `projects/{project}/locations/{location}/metadataStores/default/artifacts/{artifact_id}`. The artifact must stay within the same project, location and default metadatastore as the pipeline.
},
},
"parameterValues": { # The runtime parameters of the PipelineJob. The parameters will be passed into PipelineJob.pipeline_spec to replace the placeholders at runtime. This field is used by pipelines built using `PipelineJob.pipeline_spec.schema_version` 2.1.0, such as pipelines built using Kubeflow Pipelines SDK 1.9 or higher and the v2 DSL.
"a_key": "",
},
"parameters": { # Deprecated. Use RuntimeConfig.parameter_values instead. The runtime parameters of the PipelineJob. The parameters will be passed into PipelineJob.pipeline_spec to replace the placeholders at runtime. This field is used by pipelines built using `PipelineJob.pipeline_spec.schema_version` 2.0.0 or lower, such as pipelines built using Kubeflow Pipelines SDK 1.8 or lower.
"a_key": { # Value is the value of the field.
"doubleValue": 3.14, # A double value.
"intValue": "A String", # An integer value.
"stringValue": "A String", # A string value.
},
},
},
"scheduleName": "A String", # Output only. The schedule resource name. Only returned if the Pipeline is created by Schedule API.
"serviceAccount": "A String", # The service account that the pipeline workload runs as. If not specified, the Compute Engine default service account in the project will be used. See https://cloud.google.com/compute/docs/access/service-accounts#default_service_account Users starting the pipeline must have the `iam.serviceAccounts.actAs` permission on this service account.
"startTime": "A String", # Output only. Pipeline start time.
"state": "A String", # Output only. The detailed state of the job.
"templateMetadata": { # Pipeline template metadata if PipelineJob.template_uri is from supported template registry. Currently, the only supported registry is Artifact Registry. # Output only. Pipeline template metadata. Will fill up fields if PipelineJob.template_uri is from supported template registry.
"version": "A String", # The version_name in artifact registry. Will always be presented in output if the PipelineJob.template_uri is from supported template registry. Format is "sha256:abcdef123456...".
},
"templateUri": "A String", # A template uri from where the PipelineJob.pipeline_spec, if empty, will be downloaded. Currently, only uri from Vertex Template Registry & Gallery is supported. Reference to https://cloud.google.com/vertex-ai/docs/pipelines/create-pipeline-template.
"updateTime": "A String", # Output only. Timestamp when this PipelineJob was most recently updated.
},
"pipelineJobId": "A String", # The ID to use for the PipelineJob, which will become the final component of the PipelineJob name. If not provided, an ID will be automatically generated. This value should be less than 128 characters, and valid characters are `/a-z-/`.
},
"createTime": "A String", # Output only. Timestamp when this Schedule was created.
"cron": "A String", # Cron schedule (https://en.wikipedia.org/wiki/Cron) to launch scheduled runs. To explicitly set a timezone to the cron tab, apply a prefix in the cron tab: "CRON_TZ=${IANA_TIME_ZONE}" or "TZ=${IANA_TIME_ZONE}". The ${IANA_TIME_ZONE} may only be a valid string from IANA time zone database. For example, "CRON_TZ=America/New_York 1 * * * *", or "TZ=America/New_York 1 * * * *".
"displayName": "A String", # Required. User provided name of the Schedule. The name can be up to 128 characters long and can consist of any UTF-8 characters.
"endTime": "A String", # Optional. Timestamp after which no new runs can be scheduled. If specified, The schedule will be completed when either end_time is reached or when scheduled_run_count >= max_run_count. If not specified, new runs will keep getting scheduled until this Schedule is paused or deleted. Already scheduled runs will be allowed to complete. Unset if not specified.
"lastPauseTime": "A String", # Output only. Timestamp when this Schedule was last paused. Unset if never paused.
"lastResumeTime": "A String", # Output only. Timestamp when this Schedule was last resumed. Unset if never resumed from pause.
"lastScheduledRunResponse": { # Status of a scheduled run. # Output only. Response of the last scheduled run. This is the response for starting the scheduled requests and not the execution of the operations/jobs created by the requests (if applicable). Unset if no run has been scheduled yet.
"runResponse": "A String", # The response of the scheduled run.
"scheduledRunTime": "A String", # The scheduled run time based on the user-specified schedule.
},
"maxConcurrentRunCount": "A String", # Required. Maximum number of runs that can be started concurrently for this Schedule. This is the limit for starting the scheduled requests and not the execution of the operations/jobs created by the requests (if applicable).
"maxRunCount": "A String", # Optional. Maximum run count of the schedule. If specified, The schedule will be completed when either started_run_count >= max_run_count or when end_time is reached. If not specified, new runs will keep getting scheduled until this Schedule is paused or deleted. Already scheduled runs will be allowed to complete. Unset if not specified.
"name": "A String", # Immutable. The resource name of the Schedule.
"nextRunTime": "A String", # Output only. Timestamp when this Schedule should schedule the next run. Having a next_run_time in the past means the runs are being started behind schedule.
"startTime": "A String", # Optional. Timestamp after which the first run can be scheduled. Default to Schedule create time if not specified.
"startedRunCount": "A String", # Output only. The number of runs started by this schedule.
"state": "A String", # Output only. The state of this Schedule.
"updateTime": "A String", # Output only. Timestamp when this Schedule was updated.
}
updateMask: string, Required. The update mask applies to the resource. See google.protobuf.FieldMask.
x__xgafv: string, V1 error format.
Allowed values
1 - v1 error format
2 - v2 error format
Returns:
An object of the form:
{ # An instance of a Schedule periodically schedules runs to make API calls based on user specified time specification and API request type.
"allowQueueing": True or False, # Optional. Whether new scheduled runs can be queued when max_concurrent_runs limit is reached. If set to true, new runs will be queued instead of skipped. Default to false.
"catchUp": True or False, # Output only. Whether to backfill missed runs when the schedule is resumed from PAUSED state. If set to true, all missed runs will be scheduled. New runs will be scheduled after the backfill is complete. Default to false.
"createNotebookExecutionJobRequest": { # Request message for [NotebookService.CreateNotebookExecutionJob] # Request for NotebookService.CreateNotebookExecutionJob.
"notebookExecutionJob": { # NotebookExecutionJob represents an instance of a notebook execution. # Required. The NotebookExecutionJob to create.
"createTime": "A String", # Output only. Timestamp when this NotebookExecutionJob was created.
"customEnvironmentSpec": { # Compute configuration to use for an execution job. # The custom compute configuration for an execution job.
"machineSpec": { # Specification of a single machine. # The specification of a single machine for the execution job.
"acceleratorCount": 42, # The number of accelerators to attach to the machine.
"acceleratorType": "A String", # Immutable. The type of accelerator(s) that may be attached to the machine as per accelerator_count.
"machineType": "A String", # Immutable. The type of the machine. See the [list of machine types supported for prediction](https://cloud.google.com/vertex-ai/docs/predictions/configure-compute#machine-types) See the [list of machine types supported for custom training](https://cloud.google.com/vertex-ai/docs/training/configure-compute#machine-types). For DeployedModel this field is optional, and the default value is `n1-standard-2`. For BatchPredictionJob or as part of WorkerPoolSpec this field is required.
"reservationAffinity": { # A ReservationAffinity can be used to configure a Vertex AI resource (e.g., a DeployedModel) to draw its Compute Engine resources from a Shared Reservation, or exclusively from on-demand capacity. # Optional. Immutable. Configuration controlling how this resource pool consumes reservation.
"key": "A String", # Optional. Corresponds to the label key of a reservation resource. To target a SPECIFIC_RESERVATION by name, use `compute.googleapis.com/reservation-name` as the key and specify the name of your reservation as its value.
"reservationAffinityType": "A String", # Required. Specifies the reservation affinity type.
"values": [ # Optional. Corresponds to the label values of a reservation resource. This must be the full resource name of the reservation.
"A String",
],
},
"tpuTopology": "A String", # Immutable. The topology of the TPUs. Corresponds to the TPU topologies available from GKE. (Example: tpu_topology: "2x2x1").
},
"networkSpec": { # Network spec. # The network configuration to use for the execution job.
"enableInternetAccess": True or False, # Whether to enable public internet access. Default false.
"network": "A String", # The full name of the Google Compute Engine [network](https://cloud.google.com//compute/docs/networks-and-firewalls#networks)
"subnetwork": "A String", # The name of the subnet that this instance is in. Format: `projects/{project_id_or_number}/regions/{region}/subnetworks/{subnetwork_id}`
},
"persistentDiskSpec": { # Represents the spec of persistent disk options. # The specification of a persistent disk to attach for the execution job.
"diskSizeGb": "A String", # Size in GB of the disk (default is 100GB).
"diskType": "A String", # Type of the disk (default is "pd-standard"). Valid values: "pd-ssd" (Persistent Disk Solid State Drive) "pd-standard" (Persistent Disk Hard Disk Drive) "pd-balanced" (Balanced Persistent Disk) "pd-extreme" (Extreme Persistent Disk)
},
},
"dataformRepositorySource": { # The Dataform Repository containing the input notebook. # The Dataform Repository pointing to a single file notebook repository.
"commitSha": "A String", # The commit SHA to read repository with. If unset, the file will be read at HEAD.
"dataformRepositoryResourceName": "A String", # The resource name of the Dataform Repository. Format: `projects/{project_id}/locations/{location}/repositories/{repository_id}`
},
"directNotebookSource": { # The content of the input notebook in ipynb format. # The contents of an input notebook file.
"content": "A String", # The base64-encoded contents of the input notebook file.
},
"displayName": "A String", # The display name of the NotebookExecutionJob. The name can be up to 128 characters long and can consist of any UTF-8 characters.
"encryptionSpec": { # Represents a customer-managed encryption key spec that can be applied to a top-level resource. # Customer-managed encryption key spec for the notebook execution job. This field is auto-populated if the NotebookService.NotebookRuntimeTemplate has an encryption spec.
"kmsKeyName": "A String", # Required. The Cloud KMS resource identifier of the customer managed encryption key used to protect a resource. Has the form: `projects/my-project/locations/my-region/keyRings/my-kr/cryptoKeys/my-key`. The key needs to be in the same region as where the compute resource is created.
},
"executionTimeout": "A String", # Max running time of the execution job in seconds (default 86400s / 24 hrs).
"executionUser": "A String", # The user email to run the execution as. Only supported by Colab runtimes.
"gcsNotebookSource": { # The Cloud Storage uri for the input notebook. # The Cloud Storage url pointing to the ipynb file. Format: `gs://bucket/notebook_file.ipynb`
"generation": "A String", # The version of the Cloud Storage object to read. If unset, the current version of the object is read. See https://cloud.google.com/storage/docs/metadata#generation-number.
"uri": "A String", # The Cloud Storage uri pointing to the ipynb file. Format: `gs://bucket/notebook_file.ipynb`
},
"gcsOutputUri": "A String", # The Cloud Storage location to upload the result to. Format: `gs://bucket-name`
"jobState": "A String", # Output only. The state of the NotebookExecutionJob.
"labels": { # The labels with user-defined metadata to organize NotebookExecutionJobs. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable.
"a_key": "A String",
},
"name": "A String", # Output only. The resource name of this NotebookExecutionJob. Format: `projects/{project_id}/locations/{location}/notebookExecutionJobs/{job_id}`
"notebookRuntimeTemplateResourceName": "A String", # The NotebookRuntimeTemplate to source compute configuration from.
"scheduleResourceName": "A String", # Output only. The Schedule resource name if this job is triggered by one. Format: `projects/{project_id}/locations/{location}/schedules/{schedule_id}`
"serviceAccount": "A String", # The service account to run the execution as.
"status": { # The `Status` type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by [gRPC](https://github.com/grpc). Each `Status` message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the [API Design Guide](https://cloud.google.com/apis/design/errors). # Output only. Populated when the NotebookExecutionJob is completed. When there is an error during notebook execution, the error details are populated.
"code": 42, # The status code, which should be an enum value of google.rpc.Code.
"details": [ # A list of messages that carry the error details. There is a common set of message types for APIs to use.
{
"a_key": "", # Properties of the object. Contains field @type with type URL.
},
],
"message": "A String", # A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.
},
"updateTime": "A String", # Output only. Timestamp when this NotebookExecutionJob was most recently updated.
},
"notebookExecutionJobId": "A String", # Optional. User specified ID for the NotebookExecutionJob.
"parent": "A String", # Required. The resource name of the Location to create the NotebookExecutionJob. Format: `projects/{project}/locations/{location}`
},
"createPipelineJobRequest": { # Request message for PipelineService.CreatePipelineJob. # Request for PipelineService.CreatePipelineJob. CreatePipelineJobRequest.parent field is required (format: projects/{project}/locations/{location}).
"parent": "A String", # Required. The resource name of the Location to create the PipelineJob in. Format: `projects/{project}/locations/{location}`
"pipelineJob": { # An instance of a machine learning PipelineJob. # Required. The PipelineJob to create.
"createTime": "A String", # Output only. Pipeline creation time.
"displayName": "A String", # The display name of the Pipeline. The name can be up to 128 characters long and can consist of any UTF-8 characters.
"encryptionSpec": { # Represents a customer-managed encryption key spec that can be applied to a top-level resource. # Customer-managed encryption key spec for a pipelineJob. If set, this PipelineJob and all of its sub-resources will be secured by this key.
"kmsKeyName": "A String", # Required. The Cloud KMS resource identifier of the customer managed encryption key used to protect a resource. Has the form: `projects/my-project/locations/my-region/keyRings/my-kr/cryptoKeys/my-key`. The key needs to be in the same region as where the compute resource is created.
},
"endTime": "A String", # Output only. Pipeline end time.
"error": { # The `Status` type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by [gRPC](https://github.com/grpc). Each `Status` message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the [API Design Guide](https://cloud.google.com/apis/design/errors). # Output only. The error that occurred during pipeline execution. Only populated when the pipeline's state is FAILED or CANCELLED.
"code": 42, # The status code, which should be an enum value of google.rpc.Code.
"details": [ # A list of messages that carry the error details. There is a common set of message types for APIs to use.
{
"a_key": "", # Properties of the object. Contains field @type with type URL.
},
],
"message": "A String", # A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.
},
"jobDetail": { # The runtime detail of PipelineJob. # Output only. The details of pipeline run. Not available in the list view.
"pipelineContext": { # Instance of a general context. # Output only. The context of the pipeline.
"createTime": "A String", # Output only. Timestamp when this Context was created.
"description": "A String", # Description of the Context
"displayName": "A String", # User provided display name of the Context. May be up to 128 Unicode characters.
"etag": "A String", # An eTag used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
"labels": { # The labels with user-defined metadata to organize your Contexts. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one Context (System labels are excluded).
"a_key": "A String",
},
"metadata": { # Properties of the Context. Top level metadata keys' heading and trailing spaces will be trimmed. The size of this field should not exceed 200KB.
"a_key": "", # Properties of the object.
},
"name": "A String", # Immutable. The resource name of the Context.
"parentContexts": [ # Output only. A list of resource names of Contexts that are parents of this Context. A Context may have at most 10 parent_contexts.
"A String",
],
"schemaTitle": "A String", # The title of the schema describing the metadata. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.
"schemaVersion": "A String", # The version of the schema in schema_name to use. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.
"updateTime": "A String", # Output only. Timestamp when this Context was last updated.
},
"pipelineRunContext": { # Instance of a general context. # Output only. The context of the current pipeline run.
"createTime": "A String", # Output only. Timestamp when this Context was created.
"description": "A String", # Description of the Context
"displayName": "A String", # User provided display name of the Context. May be up to 128 Unicode characters.
"etag": "A String", # An eTag used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
"labels": { # The labels with user-defined metadata to organize your Contexts. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one Context (System labels are excluded).
"a_key": "A String",
},
"metadata": { # Properties of the Context. Top level metadata keys' heading and trailing spaces will be trimmed. The size of this field should not exceed 200KB.
"a_key": "", # Properties of the object.
},
"name": "A String", # Immutable. The resource name of the Context.
"parentContexts": [ # Output only. A list of resource names of Contexts that are parents of this Context. A Context may have at most 10 parent_contexts.
"A String",
],
"schemaTitle": "A String", # The title of the schema describing the metadata. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.
"schemaVersion": "A String", # The version of the schema in schema_name to use. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.
"updateTime": "A String", # Output only. Timestamp when this Context was last updated.
},
"taskDetails": [ # Output only. The runtime details of the tasks under the pipeline.
{ # The runtime detail of a task execution.
"createTime": "A String", # Output only. Task create time.
"endTime": "A String", # Output only. Task end time.
"error": { # The `Status` type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by [gRPC](https://github.com/grpc). Each `Status` message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the [API Design Guide](https://cloud.google.com/apis/design/errors). # Output only. The error that occurred during task execution. Only populated when the task's state is FAILED or CANCELLED.
"code": 42, # The status code, which should be an enum value of google.rpc.Code.
"details": [ # A list of messages that carry the error details. There is a common set of message types for APIs to use.
{
"a_key": "", # Properties of the object. Contains field @type with type URL.
},
],
"message": "A String", # A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.
},
"execution": { # Instance of a general execution. # Output only. The execution metadata of the task.
"createTime": "A String", # Output only. Timestamp when this Execution was created.
"description": "A String", # Description of the Execution
"displayName": "A String", # User provided display name of the Execution. May be up to 128 Unicode characters.
"etag": "A String", # An eTag used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
"labels": { # The labels with user-defined metadata to organize your Executions. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one Execution (System labels are excluded).
"a_key": "A String",
},
"metadata": { # Properties of the Execution. Top level metadata keys' heading and trailing spaces will be trimmed. The size of this field should not exceed 200KB.
"a_key": "", # Properties of the object.
},
"name": "A String", # Output only. The resource name of the Execution.
"schemaTitle": "A String", # The title of the schema describing the metadata. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.
"schemaVersion": "A String", # The version of the schema in `schema_title` to use. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.
"state": "A String", # The state of this Execution. This is a property of the Execution, and does not imply or capture any ongoing process. This property is managed by clients (such as Vertex AI Pipelines) and the system does not prescribe or check the validity of state transitions.
"updateTime": "A String", # Output only. Timestamp when this Execution was last updated.
},
"executorDetail": { # The runtime detail of a pipeline executor. # Output only. The detailed execution info.
"containerDetail": { # The detail of a container execution. It contains the job names of the lifecycle of a container execution. # Output only. The detailed info for a container executor.
"failedMainJobs": [ # Output only. The names of the previously failed CustomJob for the main container executions. The list includes the all attempts in chronological order.
"A String",
],
"failedPreCachingCheckJobs": [ # Output only. The names of the previously failed CustomJob for the pre-caching-check container executions. This job will be available if the PipelineJob.pipeline_spec specifies the `pre_caching_check` hook in the lifecycle events. The list includes the all attempts in chronological order.
"A String",
],
"mainJob": "A String", # Output only. The name of the CustomJob for the main container execution.
"preCachingCheckJob": "A String", # Output only. The name of the CustomJob for the pre-caching-check container execution. This job will be available if the PipelineJob.pipeline_spec specifies the `pre_caching_check` hook in the lifecycle events.
},
"customJobDetail": { # The detailed info for a custom job executor. # Output only. The detailed info for a custom job executor.
"failedJobs": [ # Output only. The names of the previously failed CustomJob. The list includes the all attempts in chronological order.
"A String",
],
"job": "A String", # Output only. The name of the CustomJob.
},
},
"inputs": { # Output only. The runtime input artifacts of the task.
"a_key": { # A list of artifact metadata.
"artifacts": [ # Output only. A list of artifact metadata.
{ # Instance of a general artifact.
"createTime": "A String", # Output only. Timestamp when this Artifact was created.
"description": "A String", # Description of the Artifact
"displayName": "A String", # User provided display name of the Artifact. May be up to 128 Unicode characters.
"etag": "A String", # An eTag used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
"labels": { # The labels with user-defined metadata to organize your Artifacts. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one Artifact (System labels are excluded).
"a_key": "A String",
},
"metadata": { # Properties of the Artifact. Top level metadata keys' heading and trailing spaces will be trimmed. The size of this field should not exceed 200KB.
"a_key": "", # Properties of the object.
},
"name": "A String", # Output only. The resource name of the Artifact.
"schemaTitle": "A String", # The title of the schema describing the metadata. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.
"schemaVersion": "A String", # The version of the schema in schema_name to use. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.
"state": "A String", # The state of this Artifact. This is a property of the Artifact, and does not imply or capture any ongoing process. This property is managed by clients (such as Vertex AI Pipelines), and the system does not prescribe or check the validity of state transitions.
"updateTime": "A String", # Output only. Timestamp when this Artifact was last updated.
"uri": "A String", # The uniform resource identifier of the artifact file. May be empty if there is no actual artifact file.
},
],
},
},
"outputs": { # Output only. The runtime output artifacts of the task.
"a_key": { # A list of artifact metadata.
"artifacts": [ # Output only. A list of artifact metadata.
{ # Instance of a general artifact.
"createTime": "A String", # Output only. Timestamp when this Artifact was created.
"description": "A String", # Description of the Artifact
"displayName": "A String", # User provided display name of the Artifact. May be up to 128 Unicode characters.
"etag": "A String", # An eTag used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
"labels": { # The labels with user-defined metadata to organize your Artifacts. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one Artifact (System labels are excluded).
"a_key": "A String",
},
"metadata": { # Properties of the Artifact. Top level metadata keys' heading and trailing spaces will be trimmed. The size of this field should not exceed 200KB.
"a_key": "", # Properties of the object.
},
"name": "A String", # Output only. The resource name of the Artifact.
"schemaTitle": "A String", # The title of the schema describing the metadata. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.
"schemaVersion": "A String", # The version of the schema in schema_name to use. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.
"state": "A String", # The state of this Artifact. This is a property of the Artifact, and does not imply or capture any ongoing process. This property is managed by clients (such as Vertex AI Pipelines), and the system does not prescribe or check the validity of state transitions.
"updateTime": "A String", # Output only. Timestamp when this Artifact was last updated.
"uri": "A String", # The uniform resource identifier of the artifact file. May be empty if there is no actual artifact file.
},
],
},
},
"parentTaskId": "A String", # Output only. The id of the parent task if the task is within a component scope. Empty if the task is at the root level.
"pipelineTaskStatus": [ # Output only. A list of task status. This field keeps a record of task status evolving over time.
{ # A single record of the task status.
"error": { # The `Status` type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by [gRPC](https://github.com/grpc). Each `Status` message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the [API Design Guide](https://cloud.google.com/apis/design/errors). # Output only. The error that occurred during the state. May be set when the state is any of the non-final state (PENDING/RUNNING/CANCELLING) or FAILED state. If the state is FAILED, the error here is final and not going to be retried. If the state is a non-final state, the error indicates a system-error being retried.
"code": 42, # The status code, which should be an enum value of google.rpc.Code.
"details": [ # A list of messages that carry the error details. There is a common set of message types for APIs to use.
{
"a_key": "", # Properties of the object. Contains field @type with type URL.
},
],
"message": "A String", # A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.
},
"state": "A String", # Output only. The state of the task.
"updateTime": "A String", # Output only. Update time of this status.
},
],
"startTime": "A String", # Output only. Task start time.
"state": "A String", # Output only. State of the task.
"taskId": "A String", # Output only. The system generated ID of the task.
"taskName": "A String", # Output only. The user specified name of the task that is defined in pipeline_spec.
},
],
},
"labels": { # The labels with user-defined metadata to organize PipelineJob. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels. Note there is some reserved label key for Vertex AI Pipelines. - `vertex-ai-pipelines-run-billing-id`, user set value will get overrided.
"a_key": "A String",
},
"name": "A String", # Output only. The resource name of the PipelineJob.
"network": "A String", # The full name of the Compute Engine [network](/compute/docs/networks-and-firewalls#networks) to which the Pipeline Job's workload should be peered. For example, `projects/12345/global/networks/myVPC`. [Format](/compute/docs/reference/rest/v1/networks/insert) is of the form `projects/{project}/global/networks/{network}`. Where {project} is a project number, as in `12345`, and {network} is a network name. Private services access must already be configured for the network. Pipeline job will apply the network configuration to the Google Cloud resources being launched, if applied, such as Vertex AI Training or Dataflow job. If left unspecified, the workload is not peered with any network.
"pipelineSpec": { # The spec of the pipeline.
"a_key": "", # Properties of the object.
},
"preflightValidations": True or False, # Optional. Whether to do component level validations before job creation.
"reservedIpRanges": [ # A list of names for the reserved ip ranges under the VPC network that can be used for this Pipeline Job's workload. If set, we will deploy the Pipeline Job's workload within the provided ip ranges. Otherwise, the job will be deployed to any ip ranges under the provided VPC network. Example: ['vertex-ai-ip-range'].
"A String",
],
"runtimeConfig": { # The runtime config of a PipelineJob. # Runtime config of the pipeline.
"failurePolicy": "A String", # Represents the failure policy of a pipeline. Currently, the default of a pipeline is that the pipeline will continue to run until no more tasks can be executed, also known as PIPELINE_FAILURE_POLICY_FAIL_SLOW. However, if a pipeline is set to PIPELINE_FAILURE_POLICY_FAIL_FAST, it will stop scheduling any new tasks when a task has failed. Any scheduled tasks will continue to completion.
"gcsOutputDirectory": "A String", # Required. A path in a Cloud Storage bucket, which will be treated as the root output directory of the pipeline. It is used by the system to generate the paths of output artifacts. The artifact paths are generated with a sub-path pattern `{job_id}/{task_id}/{output_key}` under the specified output directory. The service account specified in this pipeline must have the `storage.objects.get` and `storage.objects.create` permissions for this bucket.
"inputArtifacts": { # The runtime artifacts of the PipelineJob. The key will be the input artifact name and the value would be one of the InputArtifact.
"a_key": { # The type of an input artifact.
"artifactId": "A String", # Artifact resource id from MLMD. Which is the last portion of an artifact resource name: `projects/{project}/locations/{location}/metadataStores/default/artifacts/{artifact_id}`. The artifact must stay within the same project, location and default metadatastore as the pipeline.
},
},
"parameterValues": { # The runtime parameters of the PipelineJob. The parameters will be passed into PipelineJob.pipeline_spec to replace the placeholders at runtime. This field is used by pipelines built using `PipelineJob.pipeline_spec.schema_version` 2.1.0, such as pipelines built using Kubeflow Pipelines SDK 1.9 or higher and the v2 DSL.
"a_key": "",
},
"parameters": { # Deprecated. Use RuntimeConfig.parameter_values instead. The runtime parameters of the PipelineJob. The parameters will be passed into PipelineJob.pipeline_spec to replace the placeholders at runtime. This field is used by pipelines built using `PipelineJob.pipeline_spec.schema_version` 2.0.0 or lower, such as pipelines built using Kubeflow Pipelines SDK 1.8 or lower.
"a_key": { # Value is the value of the field.
"doubleValue": 3.14, # A double value.
"intValue": "A String", # An integer value.
"stringValue": "A String", # A string value.
},
},
},
"scheduleName": "A String", # Output only. The schedule resource name. Only returned if the Pipeline is created by Schedule API.
"serviceAccount": "A String", # The service account that the pipeline workload runs as. If not specified, the Compute Engine default service account in the project will be used. See https://cloud.google.com/compute/docs/access/service-accounts#default_service_account Users starting the pipeline must have the `iam.serviceAccounts.actAs` permission on this service account.
"startTime": "A String", # Output only. Pipeline start time.
"state": "A String", # Output only. The detailed state of the job.
"templateMetadata": { # Pipeline template metadata if PipelineJob.template_uri is from supported template registry. Currently, the only supported registry is Artifact Registry. # Output only. Pipeline template metadata. Will fill up fields if PipelineJob.template_uri is from supported template registry.
"version": "A String", # The version_name in artifact registry. Will always be presented in output if the PipelineJob.template_uri is from supported template registry. Format is "sha256:abcdef123456...".
},
"templateUri": "A String", # A template uri from where the PipelineJob.pipeline_spec, if empty, will be downloaded. Currently, only uri from Vertex Template Registry & Gallery is supported. Reference to https://cloud.google.com/vertex-ai/docs/pipelines/create-pipeline-template.
"updateTime": "A String", # Output only. Timestamp when this PipelineJob was most recently updated.
},
"pipelineJobId": "A String", # The ID to use for the PipelineJob, which will become the final component of the PipelineJob name. If not provided, an ID will be automatically generated. This value should be less than 128 characters, and valid characters are `/a-z-/`.
},
"createTime": "A String", # Output only. Timestamp when this Schedule was created.
"cron": "A String", # Cron schedule (https://en.wikipedia.org/wiki/Cron) to launch scheduled runs. To explicitly set a timezone to the cron tab, apply a prefix in the cron tab: "CRON_TZ=${IANA_TIME_ZONE}" or "TZ=${IANA_TIME_ZONE}". The ${IANA_TIME_ZONE} may only be a valid string from IANA time zone database. For example, "CRON_TZ=America/New_York 1 * * * *", or "TZ=America/New_York 1 * * * *".
"displayName": "A String", # Required. User provided name of the Schedule. The name can be up to 128 characters long and can consist of any UTF-8 characters.
"endTime": "A String", # Optional. Timestamp after which no new runs can be scheduled. If specified, The schedule will be completed when either end_time is reached or when scheduled_run_count >= max_run_count. If not specified, new runs will keep getting scheduled until this Schedule is paused or deleted. Already scheduled runs will be allowed to complete. Unset if not specified.
"lastPauseTime": "A String", # Output only. Timestamp when this Schedule was last paused. Unset if never paused.
"lastResumeTime": "A String", # Output only. Timestamp when this Schedule was last resumed. Unset if never resumed from pause.
"lastScheduledRunResponse": { # Status of a scheduled run. # Output only. Response of the last scheduled run. This is the response for starting the scheduled requests and not the execution of the operations/jobs created by the requests (if applicable). Unset if no run has been scheduled yet.
"runResponse": "A String", # The response of the scheduled run.
"scheduledRunTime": "A String", # The scheduled run time based on the user-specified schedule.
},
"maxConcurrentRunCount": "A String", # Required. Maximum number of runs that can be started concurrently for this Schedule. This is the limit for starting the scheduled requests and not the execution of the operations/jobs created by the requests (if applicable).
"maxRunCount": "A String", # Optional. Maximum run count of the schedule. If specified, The schedule will be completed when either started_run_count >= max_run_count or when end_time is reached. If not specified, new runs will keep getting scheduled until this Schedule is paused or deleted. Already scheduled runs will be allowed to complete. Unset if not specified.
"name": "A String", # Immutable. The resource name of the Schedule.
"nextRunTime": "A String", # Output only. Timestamp when this Schedule should schedule the next run. Having a next_run_time in the past means the runs are being started behind schedule.
"startTime": "A String", # Optional. Timestamp after which the first run can be scheduled. Default to Schedule create time if not specified.
"startedRunCount": "A String", # Output only. The number of runs started by this schedule.
"state": "A String", # Output only. The state of this Schedule.
"updateTime": "A String", # Output only. Timestamp when this Schedule was updated.
}
pause(name, body=None, x__xgafv=None)
Pauses a Schedule. Will mark Schedule.state to 'PAUSED'. If the schedule is paused, no new runs will be created. Already created runs will NOT be paused or canceled.
Args:
name: string, Required. The name of the Schedule resource to be paused. Format: `projects/{project}/locations/{location}/schedules/{schedule}` (required)
body: object, The request body.
The object takes the form of:
{ # Request message for ScheduleService.PauseSchedule.
}
x__xgafv: string, V1 error format.
Allowed values
1 - v1 error format
2 - v2 error format
Returns:
An object of the form:
{ # A generic empty message that you can re-use to avoid defining duplicated empty messages in your APIs. A typical example is to use it as the request or the response type of an API method. For instance: service Foo { rpc Bar(google.protobuf.Empty) returns (google.protobuf.Empty); }
}
resume(name, body=None, x__xgafv=None)
Resumes a paused Schedule to start scheduling new runs. Will mark Schedule.state to 'ACTIVE'. Only paused Schedule can be resumed. When the Schedule is resumed, new runs will be scheduled starting from the next execution time after the current time based on the time_specification in the Schedule. If Schedule.catchUp is set up true, all missed runs will be scheduled for backfill first.
Args:
name: string, Required. The name of the Schedule resource to be resumed. Format: `projects/{project}/locations/{location}/schedules/{schedule}` (required)
body: object, The request body.
The object takes the form of:
{ # Request message for ScheduleService.ResumeSchedule.
"catchUp": True or False, # Optional. Whether to backfill missed runs when the schedule is resumed from PAUSED state. If set to true, all missed runs will be scheduled. New runs will be scheduled after the backfill is complete. This will also update Schedule.catch_up field. Default to false.
}
x__xgafv: string, V1 error format.
Allowed values
1 - v1 error format
2 - v2 error format
Returns:
An object of the form:
{ # A generic empty message that you can re-use to avoid defining duplicated empty messages in your APIs. A typical example is to use it as the request or the response type of an API method. For instance: service Foo { rpc Bar(google.protobuf.Empty) returns (google.protobuf.Empty); }
}