Class PipelineJob (3.56.0)

An instance of a machine learning PipelineJob.

Protobuf type google.cloud.aiplatform.v1beta1.PipelineJob

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.

map<string, string> labels = 11;

Output only. Pipeline creation time.

.google.protobuf.Timestamp create_time = 3 [(.google.api.field_behavior) = OUTPUT_ONLY];

Output only. Pipeline creation time.

.google.protobuf.Timestamp create_time = 3 [(.google.api.field_behavior) = OUTPUT_ONLY];

The display name of the Pipeline. The name can be up to 128 characters long and can consist of any UTF-8 characters.

string display_name = 2;

The display name of the Pipeline. The name can be up to 128 characters long and can consist of any UTF-8 characters.

string display_name = 2;

Customer-managed encryption key spec for a pipelineJob. If set, this PipelineJob and all of its sub-resources will be secured by this key.

.google.cloud.aiplatform.v1beta1.EncryptionSpec encryption_spec = 16;

Customer-managed encryption key spec for a pipelineJob. If set, this PipelineJob and all of its sub-resources will be secured by this key.

.google.cloud.aiplatform.v1beta1.EncryptionSpec encryption_spec = 16;

Output only. Pipeline end time.

.google.protobuf.Timestamp end_time = 5 [(.google.api.field_behavior) = OUTPUT_ONLY];

Output only. Pipeline end time.

.google.protobuf.Timestamp end_time = 5 [(.google.api.field_behavior) = OUTPUT_ONLY];

Output only. The error that occurred during pipeline execution. Only populated when the pipeline's state is FAILED or CANCELLED.

.google.rpc.Status error = 10 [(.google.api.field_behavior) = OUTPUT_ONLY];

Output only. The error that occurred during pipeline execution. Only populated when the pipeline's state is FAILED or CANCELLED.

.google.rpc.Status error = 10 [(.google.api.field_behavior) = OUTPUT_ONLY];

Output only. The details of pipeline run. Not available in the list view.

.google.cloud.aiplatform.v1beta1.PipelineJobDetail job_detail = 9 [(.google.api.field_behavior) = OUTPUT_ONLY];

Output only. The details of pipeline run. Not available in the list view.

.google.cloud.aiplatform.v1beta1.PipelineJobDetail job_detail = 9 [(.google.api.field_behavior) = OUTPUT_ONLY];

Use #getLabelsMap() instead.

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.

map<string, string> labels = 11;

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.

map<string, string> labels = 11;

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.

map<string, string> labels = 11;

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.

map<string, string> labels = 11;

Output only. The resource name of the PipelineJob.

string name = 1 [(.google.api.field_behavior) = OUTPUT_ONLY];

Output only. The resource name of the PipelineJob.

string name = 1 [(.google.api.field_behavior) = OUTPUT_ONLY];

The full name of the Compute Engine network to which the Pipeline Job's workload should be peered. For example, projects/12345/global/networks/myVPC. Format 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.

string network = 18 [(.google.api.resource_reference) = { ... }

The full name of the Compute Engine network to which the Pipeline Job's workload should be peered. For example, projects/12345/global/networks/myVPC. Format 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.

string network = 18 [(.google.api.resource_reference) = { ... }

Optional. The original pipeline job id if this pipeline job is a rerun of a previous pipeline job.

int64 original_pipeline_job_id = 29 [(.google.api.field_behavior) = OPTIONAL];

The spec of the pipeline.

.google.protobuf.Struct pipeline_spec = 7;

The spec of the pipeline.

.google.protobuf.Struct pipeline_spec = 7;

Optional. The rerun configs for each task in the pipeline job. By default, the rerun will:

1. Use the same input artifacts as the original run.
2. Use the same input parameters as the original run.
3. Skip all the tasks that are already succeeded in the original run.
4. Rerun all the tasks that are not succeeded in the original run. By providing this field, users can override the default behavior and specify the rerun config for each task.

repeated .google.cloud.aiplatform.v1beta1.PipelineTaskRerunConfig pipeline_task_rerun_configs = 30 [(.google.api.field_behavior) = OPTIONAL];

Optional. The rerun configs for each task in the pipeline job. By default, the rerun will:

1. Use the same input artifacts as the original run.
2. Use the same input parameters as the original run.
3. Skip all the tasks that are already succeeded in the original run.
4. Rerun all the tasks that are not succeeded in the original run. By providing this field, users can override the default behavior and specify the rerun config for each task.

repeated .google.cloud.aiplatform.v1beta1.PipelineTaskRerunConfig pipeline_task_rerun_configs = 30 [(.google.api.field_behavior) = OPTIONAL];

Optional. The rerun configs for each task in the pipeline job. By default, the rerun will:

1. Use the same input artifacts as the original run.
2. Use the same input parameters as the original run.
3. Skip all the tasks that are already succeeded in the original run.
4. Rerun all the tasks that are not succeeded in the original run. By providing this field, users can override the default behavior and specify the rerun config for each task.

repeated .google.cloud.aiplatform.v1beta1.PipelineTaskRerunConfig pipeline_task_rerun_configs = 30 [(.google.api.field_behavior) = OPTIONAL];

Optional. The rerun configs for each task in the pipeline job. By default, the rerun will:

1. Use the same input artifacts as the original run.
2. Use the same input parameters as the original run.
3. Skip all the tasks that are already succeeded in the original run.
4. Rerun all the tasks that are not succeeded in the original run. By providing this field, users can override the default behavior and specify the rerun config for each task.

repeated .google.cloud.aiplatform.v1beta1.PipelineTaskRerunConfig pipeline_task_rerun_configs = 30 [(.google.api.field_behavior) = OPTIONAL];

Optional. The rerun configs for each task in the pipeline job. By default, the rerun will:

1. Use the same input artifacts as the original run.
2. Use the same input parameters as the original run.
3. Skip all the tasks that are already succeeded in the original run.
4. Rerun all the tasks that are not succeeded in the original run. By providing this field, users can override the default behavior and specify the rerun config for each task.

repeated .google.cloud.aiplatform.v1beta1.PipelineTaskRerunConfig pipeline_task_rerun_configs = 30 [(.google.api.field_behavior) = OPTIONAL];

Optional. Whether to do component level validations before job creation.

bool preflight_validations = 26 [(.google.api.field_behavior) = OPTIONAL];

Optional. Configuration for PSC-I for PipelineJob.

.google.cloud.aiplatform.v1beta1.PscInterfaceConfig psc_interface_config = 31 [(.google.api.field_behavior) = OPTIONAL];

Optional. Configuration for PSC-I for PipelineJob.

.google.cloud.aiplatform.v1beta1.PscInterfaceConfig psc_interface_config = 31 [(.google.api.field_behavior) = OPTIONAL];

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'].

repeated string reserved_ip_ranges = 25;

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'].

repeated string reserved_ip_ranges = 25;

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'].

repeated string reserved_ip_ranges = 25;

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'].

repeated string reserved_ip_ranges = 25;

Runtime config of the pipeline.

.google.cloud.aiplatform.v1beta1.PipelineJob.RuntimeConfig runtime_config = 12;

Runtime config of the pipeline.

.google.cloud.aiplatform.v1beta1.PipelineJob.RuntimeConfig runtime_config = 12;

Output only. Reserved for future use.

bool satisfies_pzi = 28 [(.google.api.field_behavior) = OUTPUT_ONLY];

Output only. Reserved for future use.

bool satisfies_pzs = 27 [(.google.api.field_behavior) = OUTPUT_ONLY];

Output only. The schedule resource name. Only returned if the Pipeline is created by Schedule API.

string schedule_name = 22 [(.google.api.field_behavior) = OUTPUT_ONLY];

Output only. The schedule resource name. Only returned if the Pipeline is created by Schedule API.

string schedule_name = 22 [(.google.api.field_behavior) = OUTPUT_ONLY];

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.

string service_account = 17;

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.

string service_account = 17;

Output only. Pipeline start time.

.google.protobuf.Timestamp start_time = 4 [(.google.api.field_behavior) = OUTPUT_ONLY];

Output only. Pipeline start time.

.google.protobuf.Timestamp start_time = 4 [(.google.api.field_behavior) = OUTPUT_ONLY];

Output only. The detailed state of the job.

.google.cloud.aiplatform.v1beta1.PipelineState state = 8 [(.google.api.field_behavior) = OUTPUT_ONLY];

Output only. The detailed state of the job.

.google.cloud.aiplatform.v1beta1.PipelineState state = 8 [(.google.api.field_behavior) = OUTPUT_ONLY];

Output only. Pipeline template metadata. Will fill up fields if PipelineJob.template_uri is from supported template registry.

.google.cloud.aiplatform.v1beta1.PipelineTemplateMetadata template_metadata = 20 [(.google.api.field_behavior) = OUTPUT_ONLY];

Output only. Pipeline template metadata. Will fill up fields if PipelineJob.template_uri is from supported template registry.

.google.cloud.aiplatform.v1beta1.PipelineTemplateMetadata template_metadata = 20 [(.google.api.field_behavior) = OUTPUT_ONLY];

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.

string template_uri = 19;

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.

string template_uri = 19;

Output only. Timestamp when this PipelineJob was most recently updated.

.google.protobuf.Timestamp update_time = 6 [(.google.api.field_behavior) = OUTPUT_ONLY];

Output only. Timestamp when this PipelineJob was most recently updated.

.google.protobuf.Timestamp update_time = 6 [(.google.api.field_behavior) = OUTPUT_ONLY];

Output only. Pipeline creation time.

.google.protobuf.Timestamp create_time = 3 [(.google.api.field_behavior) = OUTPUT_ONLY];

Customer-managed encryption key spec for a pipelineJob. If set, this PipelineJob and all of its sub-resources will be secured by this key.

.google.cloud.aiplatform.v1beta1.EncryptionSpec encryption_spec = 16;

Output only. Pipeline end time.

.google.protobuf.Timestamp end_time = 5 [(.google.api.field_behavior) = OUTPUT_ONLY];

Output only. The error that occurred during pipeline execution. Only populated when the pipeline's state is FAILED or CANCELLED.

.google.rpc.Status error = 10 [(.google.api.field_behavior) = OUTPUT_ONLY];

Output only. The details of pipeline run. Not available in the list view.

.google.cloud.aiplatform.v1beta1.PipelineJobDetail job_detail = 9 [(.google.api.field_behavior) = OUTPUT_ONLY];

The spec of the pipeline.

.google.protobuf.Struct pipeline_spec = 7;

Optional. Configuration for PSC-I for PipelineJob.

.google.cloud.aiplatform.v1beta1.PscInterfaceConfig psc_interface_config = 31 [(.google.api.field_behavior) = OPTIONAL];

Runtime config of the pipeline.

.google.cloud.aiplatform.v1beta1.PipelineJob.RuntimeConfig runtime_config = 12;

Output only. Pipeline start time.

.google.protobuf.Timestamp start_time = 4 [(.google.api.field_behavior) = OUTPUT_ONLY];

Output only. Pipeline template metadata. Will fill up fields if PipelineJob.template_uri is from supported template registry.

.google.cloud.aiplatform.v1beta1.PipelineTemplateMetadata template_metadata = 20 [(.google.api.field_behavior) = OUTPUT_ONLY];

Output only. Timestamp when this PipelineJob was most recently updated.

.google.protobuf.Timestamp update_time = 6 [(.google.api.field_behavior) = OUTPUT_ONLY];