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Google Cloud Native v0.32.0 published on Wednesday, Nov 29, 2023 by Pulumi
pulumi/pulumi-google-native

google-native.aiplatform/v1.Schedule

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Google Cloud Native is in preview. Google Cloud Classic is fully supported.

Google Cloud Native v0.32.0 published on Wednesday, Nov 29, 2023 by Pulumi
pulumi/pulumi-google-native

    Creates a Schedule.

    Create Schedule Resource

    Resources are created with functions called constructors. To learn more about declaring and configuring resources, see Resources.

    Constructor syntax

    new Schedule(name: string, args: ScheduleArgs, opts?: CustomResourceOptions);
    @overload
def Schedule(resource_name: str,
             args: ScheduleArgs,
             opts: Optional[ResourceOptions] = None)

@overload
def Schedule(resource_name: str,
             opts: Optional[ResourceOptions] = None,
             display_name: Optional[str] = None,
             max_concurrent_run_count: Optional[str] = None,
             allow_queueing: Optional[bool] = None,
             create_pipeline_job_request: Optional[GoogleCloudAiplatformV1CreatePipelineJobRequestArgs] = None,
             cron: Optional[str] = None,
             end_time: Optional[str] = None,
             location: Optional[str] = None,
             max_run_count: Optional[str] = None,
             name: Optional[str] = None,
             project: Optional[str] = None,
             start_time: Optional[str] = None)
    func NewSchedule(ctx *Context, name string, args ScheduleArgs, opts ...ResourceOption) (*Schedule, error)
    public Schedule(string name, ScheduleArgs args, CustomResourceOptions? opts = null)
    public Schedule(String name, ScheduleArgs args)
public Schedule(String name, ScheduleArgs args, CustomResourceOptions options)

    type: google-native:aiplatform/v1:Schedule
properties: # The arguments to resource properties.
options: # Bag of options to control resource's behavior.

    Parameters

    name string
    The unique name of the resource.
    args ScheduleArgs
    The arguments to resource properties.
    opts CustomResourceOptions
    Bag of options to control resource's behavior.
    resource_name str
    The unique name of the resource.
    args ScheduleArgs
    The arguments to resource properties.
    opts ResourceOptions
    Bag of options to control resource's behavior.
    ctx Context
    Context object for the current deployment.
    name string
    The unique name of the resource.
    args ScheduleArgs
    The arguments to resource properties.
    opts ResourceOption
    Bag of options to control resource's behavior.
    name string
    The unique name of the resource.
    args ScheduleArgs
    The arguments to resource properties.
    opts CustomResourceOptions
    Bag of options to control resource's behavior.
    name String
    The unique name of the resource.
    args ScheduleArgs
    The arguments to resource properties.
    options CustomResourceOptions
    Bag of options to control resource's behavior.

    Constructor example

    The following reference example uses placeholder values for all input properties.

    var scheduleResource = new GoogleNative.Aiplatform.V1.Schedule("scheduleResource", new()
{
    DisplayName = "string",
    MaxConcurrentRunCount = "string",
    AllowQueueing = false,
    CreatePipelineJobRequest = new GoogleNative.Aiplatform.V1.Inputs.GoogleCloudAiplatformV1CreatePipelineJobRequestArgs
    {
        Parent = "string",
        PipelineJob = new GoogleNative.Aiplatform.V1.Inputs.GoogleCloudAiplatformV1PipelineJobArgs
        {
            DisplayName = "string",
            EncryptionSpec = new GoogleNative.Aiplatform.V1.Inputs.GoogleCloudAiplatformV1EncryptionSpecArgs
            {
                KmsKeyName = "string",
            },
            Labels = 
            {
                { "string", "string" },
            },
            Network = "string",
            PipelineSpec = 
            {
                { "string", "string" },
            },
            ReservedIpRanges = new[]
            {
                "string",
            },
            RuntimeConfig = new GoogleNative.Aiplatform.V1.Inputs.GoogleCloudAiplatformV1PipelineJobRuntimeConfigArgs
            {
                GcsOutputDirectory = "string",
                FailurePolicy = GoogleNative.Aiplatform.V1.GoogleCloudAiplatformV1PipelineJobRuntimeConfigFailurePolicy.PipelineFailurePolicyUnspecified,
                InputArtifacts = 
                {
                    { "string", "string" },
                },
                ParameterValues = 
                {
                    { "string", "string" },
                },
            },
            ServiceAccount = "string",
            TemplateUri = "string",
        },
        PipelineJobId = "string",
    },
    Cron = "string",
    EndTime = "string",
    Location = "string",
    MaxRunCount = "string",
    Name = "string",
    Project = "string",
    StartTime = "string",
});

    example, err := aiplatform.NewSchedule(ctx, "scheduleResource", &aiplatform.ScheduleArgs{
	DisplayName:           pulumi.String("string"),
	MaxConcurrentRunCount: pulumi.String("string"),
	AllowQueueing:         pulumi.Bool(false),
	CreatePipelineJobRequest: &aiplatform.GoogleCloudAiplatformV1CreatePipelineJobRequestArgs{
		Parent: pulumi.String("string"),
		PipelineJob: &aiplatform.GoogleCloudAiplatformV1PipelineJobArgs{
			DisplayName: pulumi.String("string"),
			EncryptionSpec: &aiplatform.GoogleCloudAiplatformV1EncryptionSpecArgs{
				KmsKeyName: pulumi.String("string"),
			},
			Labels: pulumi.StringMap{
				"string": pulumi.String("string"),
			},
			Network: pulumi.String("string"),
			PipelineSpec: pulumi.StringMap{
				"string": pulumi.String("string"),
			},
			ReservedIpRanges: pulumi.StringArray{
				pulumi.String("string"),
			},
			RuntimeConfig: &aiplatform.GoogleCloudAiplatformV1PipelineJobRuntimeConfigArgs{
				GcsOutputDirectory: pulumi.String("string"),
				FailurePolicy:      aiplatform.GoogleCloudAiplatformV1PipelineJobRuntimeConfigFailurePolicyPipelineFailurePolicyUnspecified,
				InputArtifacts: pulumi.StringMap{
					"string": pulumi.String("string"),
				},
				ParameterValues: pulumi.StringMap{
					"string": pulumi.String("string"),
				},
			},
			ServiceAccount: pulumi.String("string"),
			TemplateUri:    pulumi.String("string"),
		},
		PipelineJobId: pulumi.String("string"),
	},
	Cron:        pulumi.String("string"),
	EndTime:     pulumi.String("string"),
	Location:    pulumi.String("string"),
	MaxRunCount: pulumi.String("string"),
	Name:        pulumi.String("string"),
	Project:     pulumi.String("string"),
	StartTime:   pulumi.String("string"),
})

    var scheduleResource = new Schedule("scheduleResource", ScheduleArgs.builder()
    .displayName("string")
    .maxConcurrentRunCount("string")
    .allowQueueing(false)
    .createPipelineJobRequest(GoogleCloudAiplatformV1CreatePipelineJobRequestArgs.builder()
        .parent("string")
        .pipelineJob(GoogleCloudAiplatformV1PipelineJobArgs.builder()
            .displayName("string")
            .encryptionSpec(GoogleCloudAiplatformV1EncryptionSpecArgs.builder()
                .kmsKeyName("string")
                .build())
            .labels(Map.of("string", "string"))
            .network("string")
            .pipelineSpec(Map.of("string", "string"))
            .reservedIpRanges("string")
            .runtimeConfig(GoogleCloudAiplatformV1PipelineJobRuntimeConfigArgs.builder()
                .gcsOutputDirectory("string")
                .failurePolicy("PIPELINE_FAILURE_POLICY_UNSPECIFIED")
                .inputArtifacts(Map.of("string", "string"))
                .parameterValues(Map.of("string", "string"))
                .build())
            .serviceAccount("string")
            .templateUri("string")
            .build())
        .pipelineJobId("string")
        .build())
    .cron("string")
    .endTime("string")
    .location("string")
    .maxRunCount("string")
    .name("string")
    .project("string")
    .startTime("string")
    .build());

    schedule_resource = google_native.aiplatform.v1.Schedule("scheduleResource",
    display_name="string",
    max_concurrent_run_count="string",
    allow_queueing=False,
    create_pipeline_job_request={
        "parent": "string",
        "pipeline_job": {
            "display_name": "string",
            "encryption_spec": {
                "kms_key_name": "string",
            },
            "labels": {
                "string": "string",
            },
            "network": "string",
            "pipeline_spec": {
                "string": "string",
            },
            "reserved_ip_ranges": ["string"],
            "runtime_config": {
                "gcs_output_directory": "string",
                "failure_policy": google_native.aiplatform.v1.GoogleCloudAiplatformV1PipelineJobRuntimeConfigFailurePolicy.PIPELINE_FAILURE_POLICY_UNSPECIFIED,
                "input_artifacts": {
                    "string": "string",
                },
                "parameter_values": {
                    "string": "string",
                },
            },
            "service_account": "string",
            "template_uri": "string",
        },
        "pipeline_job_id": "string",
    },
    cron="string",
    end_time="string",
    location="string",
    max_run_count="string",
    name="string",
    project="string",
    start_time="string")

    const scheduleResource = new google_native.aiplatform.v1.Schedule("scheduleResource", {
    displayName: "string",
    maxConcurrentRunCount: "string",
    allowQueueing: false,
    createPipelineJobRequest: {
        parent: "string",
        pipelineJob: {
            displayName: "string",
            encryptionSpec: {
                kmsKeyName: "string",
            },
            labels: {
                string: "string",
            },
            network: "string",
            pipelineSpec: {
                string: "string",
            },
            reservedIpRanges: ["string"],
            runtimeConfig: {
                gcsOutputDirectory: "string",
                failurePolicy: google_native.aiplatform.v1.GoogleCloudAiplatformV1PipelineJobRuntimeConfigFailurePolicy.PipelineFailurePolicyUnspecified,
                inputArtifacts: {
                    string: "string",
                },
                parameterValues: {
                    string: "string",
                },
            },
            serviceAccount: "string",
            templateUri: "string",
        },
        pipelineJobId: "string",
    },
    cron: "string",
    endTime: "string",
    location: "string",
    maxRunCount: "string",
    name: "string",
    project: "string",
    startTime: "string",
});

    type: google-native:aiplatform/v1:Schedule
properties:
    allowQueueing: false
    createPipelineJobRequest:
        parent: string
        pipelineJob:
            displayName: string
            encryptionSpec:
                kmsKeyName: string
            labels:
                string: string
            network: string
            pipelineSpec:
                string: string
            reservedIpRanges:
                - string
            runtimeConfig:
                failurePolicy: PIPELINE_FAILURE_POLICY_UNSPECIFIED
                gcsOutputDirectory: string
                inputArtifacts:
                    string: string
                parameterValues:
                    string: string
            serviceAccount: string
            templateUri: string
        pipelineJobId: string
    cron: string
    displayName: string
    endTime: string
    location: string
    maxConcurrentRunCount: string
    maxRunCount: string
    name: string
    project: string
    startTime: string

    Schedule Resource Properties

    To learn more about resource properties and how to use them, see Inputs and Outputs in the Architecture and Concepts docs.

    Inputs

    In Python, inputs that are objects can be passed either as argument classes or as dictionary literals.

    The Schedule resource accepts the following input properties:

    DisplayName string
    User provided name of the Schedule. The name can be up to 128 characters long and can consist of any UTF-8 characters.
    MaxConcurrentRunCount string
    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).
    AllowQueueing bool
    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.
    CreatePipelineJobRequest Pulumi.GoogleNative.Aiplatform.V1.Inputs.GoogleCloudAiplatformV1CreatePipelineJobRequest
    Request for PipelineService.CreatePipelineJob. CreatePipelineJobRequest.parent field is required (format: projects/{project}/locations/{location}).
    Cron 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 * * * *".
    EndTime 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.
    Location string
    MaxRunCount 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 string
    Immutable. The resource name of the Schedule.
    Project string
    StartTime string
    Optional. Timestamp after which the first run can be scheduled. Default to Schedule create time if not specified.
    DisplayName string
    User provided name of the Schedule. The name can be up to 128 characters long and can consist of any UTF-8 characters.
    MaxConcurrentRunCount string
    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).
    AllowQueueing bool
    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.
    CreatePipelineJobRequest GoogleCloudAiplatformV1CreatePipelineJobRequestArgs
    Request for PipelineService.CreatePipelineJob. CreatePipelineJobRequest.parent field is required (format: projects/{project}/locations/{location}).
    Cron 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 * * * *".
    EndTime 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.
    Location string
    MaxRunCount 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 string
    Immutable. The resource name of the Schedule.
    Project string
    StartTime string
    Optional. Timestamp after which the first run can be scheduled. Default to Schedule create time if not specified.
    displayName String
    User provided name of the Schedule. The name can be up to 128 characters long and can consist of any UTF-8 characters.
    maxConcurrentRunCount String
    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).
    allowQueueing Boolean
    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.
    createPipelineJobRequest GoogleCloudAiplatformV1CreatePipelineJobRequest
    Request for PipelineService.CreatePipelineJob. CreatePipelineJobRequest.parent field is required (format: projects/{project}/locations/{location}).
    cron 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 * * * *".
    endTime 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.
    location String
    maxRunCount 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 String
    Immutable. The resource name of the Schedule.
    project String
    startTime String
    Optional. Timestamp after which the first run can be scheduled. Default to Schedule create time if not specified.
    displayName string
    User provided name of the Schedule. The name can be up to 128 characters long and can consist of any UTF-8 characters.
    maxConcurrentRunCount string
    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).
    allowQueueing boolean
    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.
    createPipelineJobRequest GoogleCloudAiplatformV1CreatePipelineJobRequest
    Request for PipelineService.CreatePipelineJob. CreatePipelineJobRequest.parent field is required (format: projects/{project}/locations/{location}).
    cron 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 * * * *".
    endTime 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.
    location string
    maxRunCount 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 string
    Immutable. The resource name of the Schedule.
    project string
    startTime string
    Optional. Timestamp after which the first run can be scheduled. Default to Schedule create time if not specified.
    display_name str
    User provided name of the Schedule. The name can be up to 128 characters long and can consist of any UTF-8 characters.
    max_concurrent_run_count str
    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).
    allow_queueing bool
    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.
    create_pipeline_job_request GoogleCloudAiplatformV1CreatePipelineJobRequestArgs
    Request for PipelineService.CreatePipelineJob. CreatePipelineJobRequest.parent field is required (format: projects/{project}/locations/{location}).
    cron str
    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 * * * *".
    end_time str
    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.
    location str
    max_run_count str
    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 str
    Immutable. The resource name of the Schedule.
    project str
    start_time str
    Optional. Timestamp after which the first run can be scheduled. Default to Schedule create time if not specified.
    displayName String
    User provided name of the Schedule. The name can be up to 128 characters long and can consist of any UTF-8 characters.
    maxConcurrentRunCount String
    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).
    allowQueueing Boolean
    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.
    createPipelineJobRequest Property Map
    Request for PipelineService.CreatePipelineJob. CreatePipelineJobRequest.parent field is required (format: projects/{project}/locations/{location}).
    cron 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 * * * *".
    endTime 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.
    location String
    maxRunCount 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 String
    Immutable. The resource name of the Schedule.
    project String
    startTime String
    Optional. Timestamp after which the first run can be scheduled. Default to Schedule create time if not specified.

    Outputs

    All input properties are implicitly available as output properties. Additionally, the Schedule resource produces the following output properties:

    CatchUp bool
    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.
    CreateTime string
    Timestamp when this Schedule was created.
    Id string
    The provider-assigned unique ID for this managed resource.
    LastPauseTime string
    Timestamp when this Schedule was last paused. Unset if never paused.
    LastResumeTime string
    Timestamp when this Schedule was last resumed. Unset if never resumed from pause.
    LastScheduledRunResponse Pulumi.GoogleNative.Aiplatform.V1.Outputs.GoogleCloudAiplatformV1ScheduleRunResponseResponse
    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.
    NextRunTime string
    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.
    StartedRunCount string
    The number of runs started by this schedule.
    State string
    The state of this Schedule.
    UpdateTime string
    Timestamp when this Schedule was updated.
    CatchUp bool
    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.
    CreateTime string
    Timestamp when this Schedule was created.
    Id string
    The provider-assigned unique ID for this managed resource.
    LastPauseTime string
    Timestamp when this Schedule was last paused. Unset if never paused.
    LastResumeTime string
    Timestamp when this Schedule was last resumed. Unset if never resumed from pause.
    LastScheduledRunResponse GoogleCloudAiplatformV1ScheduleRunResponseResponse
    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.
    NextRunTime string
    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.
    StartedRunCount string
    The number of runs started by this schedule.
    State string
    The state of this Schedule.
    UpdateTime string
    Timestamp when this Schedule was updated.
    catchUp Boolean
    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.
    createTime String
    Timestamp when this Schedule was created.
    id String
    The provider-assigned unique ID for this managed resource.
    lastPauseTime String
    Timestamp when this Schedule was last paused. Unset if never paused.
    lastResumeTime String
    Timestamp when this Schedule was last resumed. Unset if never resumed from pause.
    lastScheduledRunResponse GoogleCloudAiplatformV1ScheduleRunResponseResponse
    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.
    nextRunTime String
    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.
    startedRunCount String
    The number of runs started by this schedule.
    state String
    The state of this Schedule.
    updateTime String
    Timestamp when this Schedule was updated.
    catchUp boolean
    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.
    createTime string
    Timestamp when this Schedule was created.
    id string
    The provider-assigned unique ID for this managed resource.
    lastPauseTime string
    Timestamp when this Schedule was last paused. Unset if never paused.
    lastResumeTime string
    Timestamp when this Schedule was last resumed. Unset if never resumed from pause.
    lastScheduledRunResponse GoogleCloudAiplatformV1ScheduleRunResponseResponse
    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.
    nextRunTime string
    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.
    startedRunCount string
    The number of runs started by this schedule.
    state string
    The state of this Schedule.
    updateTime string
    Timestamp when this Schedule was updated.
    catch_up bool
    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.
    create_time str
    Timestamp when this Schedule was created.
    id str
    The provider-assigned unique ID for this managed resource.
    last_pause_time str
    Timestamp when this Schedule was last paused. Unset if never paused.
    last_resume_time str
    Timestamp when this Schedule was last resumed. Unset if never resumed from pause.
    last_scheduled_run_response GoogleCloudAiplatformV1ScheduleRunResponseResponse
    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.
    next_run_time str
    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.
    started_run_count str
    The number of runs started by this schedule.
    state str
    The state of this Schedule.
    update_time str
    Timestamp when this Schedule was updated.
    catchUp Boolean
    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.
    createTime String
    Timestamp when this Schedule was created.
    id String
    The provider-assigned unique ID for this managed resource.
    lastPauseTime String
    Timestamp when this Schedule was last paused. Unset if never paused.
    lastResumeTime String
    Timestamp when this Schedule was last resumed. Unset if never resumed from pause.
    lastScheduledRunResponse Property Map
    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.
    nextRunTime String
    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.
    startedRunCount String
    The number of runs started by this schedule.
    state String
    The state of this Schedule.
    updateTime String
    Timestamp when this Schedule was updated.

    Supporting Types

    GoogleCloudAiplatformV1ContextResponse, GoogleCloudAiplatformV1ContextResponseArgs

    CreateTime string
    Timestamp when this Context was created.
    Description string
    Description of the Context
    DisplayName string
    User provided display name of the Context. May be up to 128 Unicode characters.
    Etag string
    An eTag used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
    Labels Dictionary<string, string>
    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).
    Metadata Dictionary<string, string>
    Properties of the Context. Top level metadata keys' heading and trailing spaces will be trimmed. The size of this field should not exceed 200KB.
    Name string
    Immutable. The resource name of the Context.
    ParentContexts List<string>
    A list of resource names of Contexts that are parents of this Context. A Context may have at most 10 parent_contexts.
    SchemaTitle 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 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 string
    Timestamp when this Context was last updated.
    CreateTime string
    Timestamp when this Context was created.
    Description string
    Description of the Context
    DisplayName string
    User provided display name of the Context. May be up to 128 Unicode characters.
    Etag string
    An eTag used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
    Labels map[string]string
    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).
    Metadata map[string]string
    Properties of the Context. Top level metadata keys' heading and trailing spaces will be trimmed. The size of this field should not exceed 200KB.
    Name string
    Immutable. The resource name of the Context.
    ParentContexts []string
    A list of resource names of Contexts that are parents of this Context. A Context may have at most 10 parent_contexts.
    SchemaTitle 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 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 string
    Timestamp when this Context was last updated.
    createTime String
    Timestamp when this Context was created.
    description String
    Description of the Context
    displayName String
    User provided display name of the Context. May be up to 128 Unicode characters.
    etag String
    An eTag used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
    labels Map<String,String>
    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).
    metadata Map<String,String>
    Properties of the Context. Top level metadata keys' heading and trailing spaces will be trimmed. The size of this field should not exceed 200KB.
    name String
    Immutable. The resource name of the Context.
    parentContexts List<String>
    A list of resource names of Contexts that are parents of this Context. A Context may have at most 10 parent_contexts.
    schemaTitle 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 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 String
    Timestamp when this Context was last updated.
    createTime string
    Timestamp when this Context was created.
    description string
    Description of the Context
    displayName string
    User provided display name of the Context. May be up to 128 Unicode characters.
    etag string
    An eTag used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
    labels {[key: string]: string}
    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).
    metadata {[key: string]: string}
    Properties of the Context. Top level metadata keys' heading and trailing spaces will be trimmed. The size of this field should not exceed 200KB.
    name string
    Immutable. The resource name of the Context.
    parentContexts string[]
    A list of resource names of Contexts that are parents of this Context. A Context may have at most 10 parent_contexts.
    schemaTitle 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 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 string
    Timestamp when this Context was last updated.
    create_time str
    Timestamp when this Context was created.
    description str
    Description of the Context
    display_name str
    User provided display name of the Context. May be up to 128 Unicode characters.
    etag str
    An eTag used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
    labels Mapping[str, str]
    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).
    metadata Mapping[str, str]
    Properties of the Context. Top level metadata keys' heading and trailing spaces will be trimmed. The size of this field should not exceed 200KB.
    name str
    Immutable. The resource name of the Context.
    parent_contexts Sequence[str]
    A list of resource names of Contexts that are parents of this Context. A Context may have at most 10 parent_contexts.
    schema_title str
    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.
    schema_version str
    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.
    update_time str
    Timestamp when this Context was last updated.
    createTime String
    Timestamp when this Context was created.
    description String
    Description of the Context
    displayName String
    User provided display name of the Context. May be up to 128 Unicode characters.
    etag String
    An eTag used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
    labels Map<String>
    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).
    metadata Map<String>
    Properties of the Context. Top level metadata keys' heading and trailing spaces will be trimmed. The size of this field should not exceed 200KB.
    name String
    Immutable. The resource name of the Context.
    parentContexts List<String>
    A list of resource names of Contexts that are parents of this Context. A Context may have at most 10 parent_contexts.
    schemaTitle 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 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 String
    Timestamp when this Context was last updated.

    GoogleCloudAiplatformV1CreatePipelineJobRequest, GoogleCloudAiplatformV1CreatePipelineJobRequestArgs

    Parent string
    The resource name of the Location to create the PipelineJob in. Format: projects/{project}/locations/{location}
    PipelineJob Pulumi.GoogleNative.Aiplatform.V1.Inputs.GoogleCloudAiplatformV1PipelineJob
    The PipelineJob to create.
    PipelineJobId 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-/.
    Parent string
    The resource name of the Location to create the PipelineJob in. Format: projects/{project}/locations/{location}
    PipelineJob GoogleCloudAiplatformV1PipelineJob
    The PipelineJob to create.
    PipelineJobId 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-/.
    parent String
    The resource name of the Location to create the PipelineJob in. Format: projects/{project}/locations/{location}
    pipelineJob GoogleCloudAiplatformV1PipelineJob
    The PipelineJob to create.
    pipelineJobId 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-/.
    parent string
    The resource name of the Location to create the PipelineJob in. Format: projects/{project}/locations/{location}
    pipelineJob GoogleCloudAiplatformV1PipelineJob
    The PipelineJob to create.
    pipelineJobId 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-/.
    parent str
    The resource name of the Location to create the PipelineJob in. Format: projects/{project}/locations/{location}
    pipeline_job GoogleCloudAiplatformV1PipelineJob
    The PipelineJob to create.
    pipeline_job_id str
    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-/.
    parent String
    The resource name of the Location to create the PipelineJob in. Format: projects/{project}/locations/{location}
    pipelineJob Property Map
    The PipelineJob to create.
    pipelineJobId 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-/.

    GoogleCloudAiplatformV1CreatePipelineJobRequestResponse, GoogleCloudAiplatformV1CreatePipelineJobRequestResponseArgs

    Parent string
    The resource name of the Location to create the PipelineJob in. Format: projects/{project}/locations/{location}
    PipelineJob Pulumi.GoogleNative.Aiplatform.V1.Inputs.GoogleCloudAiplatformV1PipelineJobResponse
    The PipelineJob to create.
    PipelineJobId 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-/.
    Parent string
    The resource name of the Location to create the PipelineJob in. Format: projects/{project}/locations/{location}
    PipelineJob GoogleCloudAiplatformV1PipelineJobResponse
    The PipelineJob to create.
    PipelineJobId 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-/.
    parent String
    The resource name of the Location to create the PipelineJob in. Format: projects/{project}/locations/{location}
    pipelineJob GoogleCloudAiplatformV1PipelineJobResponse
    The PipelineJob to create.
    pipelineJobId 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-/.
    parent string
    The resource name of the Location to create the PipelineJob in. Format: projects/{project}/locations/{location}
    pipelineJob GoogleCloudAiplatformV1PipelineJobResponse
    The PipelineJob to create.
    pipelineJobId 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-/.
    parent str
    The resource name of the Location to create the PipelineJob in. Format: projects/{project}/locations/{location}
    pipeline_job GoogleCloudAiplatformV1PipelineJobResponse
    The PipelineJob to create.
    pipeline_job_id str
    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-/.
    parent String
    The resource name of the Location to create the PipelineJob in. Format: projects/{project}/locations/{location}
    pipelineJob Property Map
    The PipelineJob to create.
    pipelineJobId 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-/.

    GoogleCloudAiplatformV1EncryptionSpec, GoogleCloudAiplatformV1EncryptionSpecArgs

    KmsKeyName string
    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.
    KmsKeyName string
    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.
    kmsKeyName String
    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.
    kmsKeyName string
    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.
    kms_key_name str
    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.
    kmsKeyName String
    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.

    GoogleCloudAiplatformV1EncryptionSpecResponse, GoogleCloudAiplatformV1EncryptionSpecResponseArgs

    KmsKeyName string
    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.
    KmsKeyName string
    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.
    kmsKeyName String
    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.
    kmsKeyName string
    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.
    kms_key_name str
    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.
    kmsKeyName String
    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.

    GoogleCloudAiplatformV1ExecutionResponse, GoogleCloudAiplatformV1ExecutionResponseArgs

    CreateTime string
    Timestamp when this Execution was created.
    Description string
    Description of the Execution
    DisplayName string
    User provided display name of the Execution. May be up to 128 Unicode characters.
    Etag string
    An eTag used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
    Labels Dictionary<string, string>
    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).
    Metadata Dictionary<string, string>
    Properties of the Execution. Top level metadata keys' heading and trailing spaces will be trimmed. The size of this field should not exceed 200KB.
    Name string
    The resource name of the Execution.
    SchemaTitle 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 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 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 string
    Timestamp when this Execution was last updated.
    CreateTime string
    Timestamp when this Execution was created.
    Description string
    Description of the Execution
    DisplayName string
    User provided display name of the Execution. May be up to 128 Unicode characters.
    Etag string
    An eTag used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
    Labels map[string]string
    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).
    Metadata map[string]string
    Properties of the Execution. Top level metadata keys' heading and trailing spaces will be trimmed. The size of this field should not exceed 200KB.
    Name string
    The resource name of the Execution.
    SchemaTitle 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 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 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 string
    Timestamp when this Execution was last updated.
    createTime String
    Timestamp when this Execution was created.
    description String
    Description of the Execution
    displayName String
    User provided display name of the Execution. May be up to 128 Unicode characters.
    etag String
    An eTag used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
    labels Map<String,String>
    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).
    metadata Map<String,String>
    Properties of the Execution. Top level metadata keys' heading and trailing spaces will be trimmed. The size of this field should not exceed 200KB.
    name String
    The resource name of the Execution.
    schemaTitle 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 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 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 String
    Timestamp when this Execution was last updated.
    createTime string
    Timestamp when this Execution was created.
    description string
    Description of the Execution
    displayName string
    User provided display name of the Execution. May be up to 128 Unicode characters.
    etag string
    An eTag used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
    labels {[key: string]: string}
    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).
    metadata {[key: string]: string}
    Properties of the Execution. Top level metadata keys' heading and trailing spaces will be trimmed. The size of this field should not exceed 200KB.
    name string
    The resource name of the Execution.
    schemaTitle 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 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 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 string
    Timestamp when this Execution was last updated.
    create_time str
    Timestamp when this Execution was created.
    description str
    Description of the Execution
    display_name str
    User provided display name of the Execution. May be up to 128 Unicode characters.
    etag str
    An eTag used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
    labels Mapping[str, str]
    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).
    metadata Mapping[str, str]
    Properties of the Execution. Top level metadata keys' heading and trailing spaces will be trimmed. The size of this field should not exceed 200KB.
    name str
    The resource name of the Execution.
    schema_title str
    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.
    schema_version str
    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 str
    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.
    update_time str
    Timestamp when this Execution was last updated.
    createTime String
    Timestamp when this Execution was created.
    description String
    Description of the Execution
    displayName String
    User provided display name of the Execution. May be up to 128 Unicode characters.
    etag String
    An eTag used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
    labels Map<String>
    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).
    metadata Map<String>
    Properties of the Execution. Top level metadata keys' heading and trailing spaces will be trimmed. The size of this field should not exceed 200KB.
    name String
    The resource name of the Execution.
    schemaTitle 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 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 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 String
    Timestamp when this Execution was last updated.

    GoogleCloudAiplatformV1PipelineJob, GoogleCloudAiplatformV1PipelineJobArgs

    DisplayName 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 Pulumi.GoogleNative.Aiplatform.V1.Inputs.GoogleCloudAiplatformV1EncryptionSpec
    Customer-managed encryption key spec for a pipelineJob. If set, this PipelineJob and all of its sub-resources will be secured by this key.
    Labels Dictionary<string, string>
    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.
    Network string
    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.
    PipelineSpec Dictionary<string, string>
    The spec of the pipeline.
    ReservedIpRanges List<string>
    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'].
    RuntimeConfig Pulumi.GoogleNative.Aiplatform.V1.Inputs.GoogleCloudAiplatformV1PipelineJobRuntimeConfig
    Runtime config of the pipeline.
    ServiceAccount 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.
    TemplateUri 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.
    DisplayName 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 GoogleCloudAiplatformV1EncryptionSpec
    Customer-managed encryption key spec for a pipelineJob. If set, this PipelineJob and all of its sub-resources will be secured by this key.
    Labels map[string]string
    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.
    Network string
    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.
    PipelineSpec map[string]string
    The spec of the pipeline.
    ReservedIpRanges []string
    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'].
    RuntimeConfig GoogleCloudAiplatformV1PipelineJobRuntimeConfig
    Runtime config of the pipeline.
    ServiceAccount 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.
    TemplateUri 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.
    displayName 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 GoogleCloudAiplatformV1EncryptionSpec
    Customer-managed encryption key spec for a pipelineJob. If set, this PipelineJob and all of its sub-resources will be secured by this key.
    labels Map<String,String>
    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.
    network String
    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.
    pipelineSpec Map<String,String>
    The spec of the pipeline.
    reservedIpRanges List<String>
    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'].
    runtimeConfig GoogleCloudAiplatformV1PipelineJobRuntimeConfig
    Runtime config of the pipeline.
    serviceAccount 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.
    templateUri 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.
    displayName 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 GoogleCloudAiplatformV1EncryptionSpec
    Customer-managed encryption key spec for a pipelineJob. If set, this PipelineJob and all of its sub-resources will be secured by this key.
    labels {[key: string]: string}
    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.
    network string
    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.
    pipelineSpec {[key: string]: string}
    The spec of the pipeline.
    reservedIpRanges string[]
    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'].
    runtimeConfig GoogleCloudAiplatformV1PipelineJobRuntimeConfig
    Runtime config of the pipeline.
    serviceAccount 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.
    templateUri 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.
    display_name str
    The display name of the Pipeline. The name can be up to 128 characters long and can consist of any UTF-8 characters.
    encryption_spec GoogleCloudAiplatformV1EncryptionSpec
    Customer-managed encryption key spec for a pipelineJob. If set, this PipelineJob and all of its sub-resources will be secured by this key.
    labels Mapping[str, str]
    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.
    network str
    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.
    pipeline_spec Mapping[str, str]
    The spec of the pipeline.
    reserved_ip_ranges Sequence[str]
    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'].
    runtime_config GoogleCloudAiplatformV1PipelineJobRuntimeConfig
    Runtime config of the pipeline.
    service_account str
    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.
    template_uri str
    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.
    displayName 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 Property Map
    Customer-managed encryption key spec for a pipelineJob. If set, this PipelineJob and all of its sub-resources will be secured by this key.
    labels Map<String>
    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.
    network String
    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.
    pipelineSpec Map<String>
    The spec of the pipeline.
    reservedIpRanges List<String>
    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'].
    runtimeConfig Property Map
    Runtime config of the pipeline.
    serviceAccount 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.
    templateUri 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.

    GoogleCloudAiplatformV1PipelineJobDetailResponse, GoogleCloudAiplatformV1PipelineJobDetailResponseArgs

    PipelineContext GoogleCloudAiplatformV1ContextResponse
    The context of the pipeline.
    PipelineRunContext GoogleCloudAiplatformV1ContextResponse
    The context of the current pipeline run.
    TaskDetails []GoogleCloudAiplatformV1PipelineTaskDetailResponse
    The runtime details of the tasks under the pipeline.
    pipelineContext GoogleCloudAiplatformV1ContextResponse
    The context of the pipeline.
    pipelineRunContext GoogleCloudAiplatformV1ContextResponse
    The context of the current pipeline run.
    taskDetails List<GoogleCloudAiplatformV1PipelineTaskDetailResponse>
    The runtime details of the tasks under the pipeline.
    pipelineContext GoogleCloudAiplatformV1ContextResponse
    The context of the pipeline.
    pipelineRunContext GoogleCloudAiplatformV1ContextResponse
    The context of the current pipeline run.
    taskDetails GoogleCloudAiplatformV1PipelineTaskDetailResponse[]
    The runtime details of the tasks under the pipeline.
    pipeline_context GoogleCloudAiplatformV1ContextResponse
    The context of the pipeline.
    pipeline_run_context GoogleCloudAiplatformV1ContextResponse
    The context of the current pipeline run.
    task_details Sequence[GoogleCloudAiplatformV1PipelineTaskDetailResponse]
    The runtime details of the tasks under the pipeline.
    pipelineContext Property Map
    The context of the pipeline.
    pipelineRunContext Property Map
    The context of the current pipeline run.
    taskDetails List<Property Map>
    The runtime details of the tasks under the pipeline.

    GoogleCloudAiplatformV1PipelineJobResponse, GoogleCloudAiplatformV1PipelineJobResponseArgs

    CreateTime string
    Pipeline creation time.
    DisplayName 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 Pulumi.GoogleNative.Aiplatform.V1.Inputs.GoogleCloudAiplatformV1EncryptionSpecResponse
    Customer-managed encryption key spec for a pipelineJob. If set, this PipelineJob and all of its sub-resources will be secured by this key.
    EndTime string
    Pipeline end time.
    Error Pulumi.GoogleNative.Aiplatform.V1.Inputs.GoogleRpcStatusResponse
    The error that occurred during pipeline execution. Only populated when the pipeline's state is FAILED or CANCELLED.
    JobDetail Pulumi.GoogleNative.Aiplatform.V1.Inputs.GoogleCloudAiplatformV1PipelineJobDetailResponse
    The details of pipeline run. Not available in the list view.
    Labels Dictionary<string, string>
    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.
    Name string
    The resource name of the PipelineJob.
    Network string
    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.
    PipelineSpec Dictionary<string, string>
    The spec of the pipeline.
    ReservedIpRanges List<string>
    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'].
    RuntimeConfig Pulumi.GoogleNative.Aiplatform.V1.Inputs.GoogleCloudAiplatformV1PipelineJobRuntimeConfigResponse
    Runtime config of the pipeline.
    ScheduleName string
    The schedule resource name. Only returned if the Pipeline is created by Schedule API.
    ServiceAccount 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 string
    Pipeline start time.
    State string
    The detailed state of the job.
    TemplateMetadata Pulumi.GoogleNative.Aiplatform.V1.Inputs.GoogleCloudAiplatformV1PipelineTemplateMetadataResponse
    Pipeline template metadata. Will fill up fields if PipelineJob.template_uri is from supported template registry.
    TemplateUri 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 string
    Timestamp when this PipelineJob was most recently updated.
    CreateTime string
    Pipeline creation time.
    DisplayName 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 GoogleCloudAiplatformV1EncryptionSpecResponse
    Customer-managed encryption key spec for a pipelineJob. If set, this PipelineJob and all of its sub-resources will be secured by this key.
    EndTime string
    Pipeline end time.
    Error GoogleRpcStatusResponse
    The error that occurred during pipeline execution. Only populated when the pipeline's state is FAILED or CANCELLED.
    JobDetail GoogleCloudAiplatformV1PipelineJobDetailResponse
    The details of pipeline run. Not available in the list view.
    Labels map[string]string
    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.
    Name string
    The resource name of the PipelineJob.
    Network string
    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.
    PipelineSpec map[string]string
    The spec of the pipeline.
    ReservedIpRanges []string
    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'].
    RuntimeConfig GoogleCloudAiplatformV1PipelineJobRuntimeConfigResponse
    Runtime config of the pipeline.
    ScheduleName string
    The schedule resource name. Only returned if the Pipeline is created by Schedule API.
    ServiceAccount 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 string
    Pipeline start time.
    State string
    The detailed state of the job.
    TemplateMetadata GoogleCloudAiplatformV1PipelineTemplateMetadataResponse
    Pipeline template metadata. Will fill up fields if PipelineJob.template_uri is from supported template registry.
    TemplateUri 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 string
    Timestamp when this PipelineJob was most recently updated.
    createTime String
    Pipeline creation time.
    displayName 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 GoogleCloudAiplatformV1EncryptionSpecResponse
    Customer-managed encryption key spec for a pipelineJob. If set, this PipelineJob and all of its sub-resources will be secured by this key.
    endTime String
    Pipeline end time.
    error GoogleRpcStatusResponse
    The error that occurred during pipeline execution. Only populated when the pipeline's state is FAILED or CANCELLED.
    jobDetail GoogleCloudAiplatformV1PipelineJobDetailResponse
    The details of pipeline run. Not available in the list view.
    labels Map<String,String>
    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.
    name String
    The resource name of the PipelineJob.
    network String
    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.
    pipelineSpec Map<String,String>
    The spec of the pipeline.
    reservedIpRanges List<String>
    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'].
    runtimeConfig GoogleCloudAiplatformV1PipelineJobRuntimeConfigResponse
    Runtime config of the pipeline.
    scheduleName String
    The schedule resource name. Only returned if the Pipeline is created by Schedule API.
    serviceAccount 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 String
    Pipeline start time.
    state String
    The detailed state of the job.
    templateMetadata GoogleCloudAiplatformV1PipelineTemplateMetadataResponse
    Pipeline template metadata. Will fill up fields if PipelineJob.template_uri is from supported template registry.
    templateUri 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 String
    Timestamp when this PipelineJob was most recently updated.
    createTime string
    Pipeline creation time.
    displayName 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 GoogleCloudAiplatformV1EncryptionSpecResponse
    Customer-managed encryption key spec for a pipelineJob. If set, this PipelineJob and all of its sub-resources will be secured by this key.
    endTime string
    Pipeline end time.
    error GoogleRpcStatusResponse
    The error that occurred during pipeline execution. Only populated when the pipeline's state is FAILED or CANCELLED.
    jobDetail GoogleCloudAiplatformV1PipelineJobDetailResponse
    The details of pipeline run. Not available in the list view.
    labels {[key: string]: string}
    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.
    name string
    The resource name of the PipelineJob.
    network string
    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.
    pipelineSpec {[key: string]: string}
    The spec of the pipeline.
    reservedIpRanges string[]
    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'].
    runtimeConfig GoogleCloudAiplatformV1PipelineJobRuntimeConfigResponse
    Runtime config of the pipeline.
    scheduleName string
    The schedule resource name. Only returned if the Pipeline is created by Schedule API.
    serviceAccount 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 string
    Pipeline start time.
    state string
    The detailed state of the job.
    templateMetadata GoogleCloudAiplatformV1PipelineTemplateMetadataResponse
    Pipeline template metadata. Will fill up fields if PipelineJob.template_uri is from supported template registry.
    templateUri 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 string
    Timestamp when this PipelineJob was most recently updated.
    create_time str
    Pipeline creation time.
    display_name str
    The display name of the Pipeline. The name can be up to 128 characters long and can consist of any UTF-8 characters.
    encryption_spec GoogleCloudAiplatformV1EncryptionSpecResponse
    Customer-managed encryption key spec for a pipelineJob. If set, this PipelineJob and all of its sub-resources will be secured by this key.
    end_time str
    Pipeline end time.
    error GoogleRpcStatusResponse
    The error that occurred during pipeline execution. Only populated when the pipeline's state is FAILED or CANCELLED.
    job_detail GoogleCloudAiplatformV1PipelineJobDetailResponse
    The details of pipeline run. Not available in the list view.
    labels Mapping[str, str]
    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.
    name str
    The resource name of the PipelineJob.
    network str
    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.
    pipeline_spec Mapping[str, str]
    The spec of the pipeline.
    reserved_ip_ranges Sequence[str]
    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'].
    runtime_config GoogleCloudAiplatformV1PipelineJobRuntimeConfigResponse
    Runtime config of the pipeline.
    schedule_name str
    The schedule resource name. Only returned if the Pipeline is created by Schedule API.
    service_account str
    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.
    start_time str
    Pipeline start time.
    state str
    The detailed state of the job.
    template_metadata GoogleCloudAiplatformV1PipelineTemplateMetadataResponse
    Pipeline template metadata. Will fill up fields if PipelineJob.template_uri is from supported template registry.
    template_uri str
    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.
    update_time str
    Timestamp when this PipelineJob was most recently updated.
    createTime String
    Pipeline creation time.
    displayName 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 Property Map
    Customer-managed encryption key spec for a pipelineJob. If set, this PipelineJob and all of its sub-resources will be secured by this key.
    endTime String
    Pipeline end time.
    error Property Map
    The error that occurred during pipeline execution. Only populated when the pipeline's state is FAILED or CANCELLED.
    jobDetail Property Map
    The details of pipeline run. Not available in the list view.
    labels Map<String>
    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.
    name String
    The resource name of the PipelineJob.
    network String
    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.
    pipelineSpec Map<String>
    The spec of the pipeline.
    reservedIpRanges List<String>
    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'].
    runtimeConfig Property Map
    Runtime config of the pipeline.
    scheduleName String
    The schedule resource name. Only returned if the Pipeline is created by Schedule API.
    serviceAccount 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 String
    Pipeline start time.
    state String
    The detailed state of the job.
    templateMetadata Property Map
    Pipeline template metadata. Will fill up fields if PipelineJob.template_uri is from supported template registry.
    templateUri 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 String
    Timestamp when this PipelineJob was most recently updated.

    GoogleCloudAiplatformV1PipelineJobRuntimeConfig, GoogleCloudAiplatformV1PipelineJobRuntimeConfigArgs

    GcsOutputDirectory string
    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.
    FailurePolicy Pulumi.GoogleNative.Aiplatform.V1.GoogleCloudAiplatformV1PipelineJobRuntimeConfigFailurePolicy
    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.
    InputArtifacts Dictionary<string, string>
    The runtime artifacts of the PipelineJob. The key will be the input artifact name and the value would be one of the InputArtifact.
    ParameterValues Dictionary<string, string>
    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.
    Parameters Dictionary<string, string>
    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.

    Deprecated: 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.

    GcsOutputDirectory string
    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.
    FailurePolicy GoogleCloudAiplatformV1PipelineJobRuntimeConfigFailurePolicy
    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.
    InputArtifacts map[string]string
    The runtime artifacts of the PipelineJob. The key will be the input artifact name and the value would be one of the InputArtifact.
    ParameterValues map[string]string
    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.
    Parameters map[string]string
    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.

    Deprecated: 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.

    gcsOutputDirectory String
    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.
    failurePolicy GoogleCloudAiplatformV1PipelineJobRuntimeConfigFailurePolicy
    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.
    inputArtifacts Map<String,String>
    The runtime artifacts of the PipelineJob. The key will be the input artifact name and the value would be one of the InputArtifact.
    parameterValues Map<String,String>
    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.
    parameters Map<String,String>
    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.

    Deprecated: 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.

    gcsOutputDirectory string
    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.
    failurePolicy GoogleCloudAiplatformV1PipelineJobRuntimeConfigFailurePolicy
    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.
    inputArtifacts {[key: string]: string}
    The runtime artifacts of the PipelineJob. The key will be the input artifact name and the value would be one of the InputArtifact.
    parameterValues {[key: string]: string}
    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.
    parameters {[key: string]: string}
    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.

    Deprecated: 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.

    gcs_output_directory str
    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.
    failure_policy GoogleCloudAiplatformV1PipelineJobRuntimeConfigFailurePolicy
    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.
    input_artifacts Mapping[str, str]
    The runtime artifacts of the PipelineJob. The key will be the input artifact name and the value would be one of the InputArtifact.
    parameter_values Mapping[str, str]
    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.
    parameters Mapping[str, str]
    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.

    Deprecated: 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.

    gcsOutputDirectory String
    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.
    failurePolicy "PIPELINE_FAILURE_POLICY_UNSPECIFIED" | "PIPELINE_FAILURE_POLICY_FAIL_SLOW" | "PIPELINE_FAILURE_POLICY_FAIL_FAST"
    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.
    inputArtifacts Map<String>
    The runtime artifacts of the PipelineJob. The key will be the input artifact name and the value would be one of the InputArtifact.
    parameterValues Map<String>
    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.
    parameters Map<String>
    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.

    Deprecated: 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.

    GoogleCloudAiplatformV1PipelineJobRuntimeConfigFailurePolicy, GoogleCloudAiplatformV1PipelineJobRuntimeConfigFailurePolicyArgs

    PipelineFailurePolicyUnspecified
    PIPELINE_FAILURE_POLICY_UNSPECIFIEDDefault value, and follows fail slow behavior.
    PipelineFailurePolicyFailSlow
    PIPELINE_FAILURE_POLICY_FAIL_SLOWIndicates that the pipeline should continue to run until all possible tasks have been scheduled and completed.
    PipelineFailurePolicyFailFast
    PIPELINE_FAILURE_POLICY_FAIL_FASTIndicates that the pipeline should stop scheduling new tasks after a task has failed.
    GoogleCloudAiplatformV1PipelineJobRuntimeConfigFailurePolicyPipelineFailurePolicyUnspecified
    PIPELINE_FAILURE_POLICY_UNSPECIFIEDDefault value, and follows fail slow behavior.
    GoogleCloudAiplatformV1PipelineJobRuntimeConfigFailurePolicyPipelineFailurePolicyFailSlow
    PIPELINE_FAILURE_POLICY_FAIL_SLOWIndicates that the pipeline should continue to run until all possible tasks have been scheduled and completed.
    GoogleCloudAiplatformV1PipelineJobRuntimeConfigFailurePolicyPipelineFailurePolicyFailFast
    PIPELINE_FAILURE_POLICY_FAIL_FASTIndicates that the pipeline should stop scheduling new tasks after a task has failed.
    PipelineFailurePolicyUnspecified
    PIPELINE_FAILURE_POLICY_UNSPECIFIEDDefault value, and follows fail slow behavior.
    PipelineFailurePolicyFailSlow
    PIPELINE_FAILURE_POLICY_FAIL_SLOWIndicates that the pipeline should continue to run until all possible tasks have been scheduled and completed.
    PipelineFailurePolicyFailFast
    PIPELINE_FAILURE_POLICY_FAIL_FASTIndicates that the pipeline should stop scheduling new tasks after a task has failed.
    PipelineFailurePolicyUnspecified
    PIPELINE_FAILURE_POLICY_UNSPECIFIEDDefault value, and follows fail slow behavior.
    PipelineFailurePolicyFailSlow
    PIPELINE_FAILURE_POLICY_FAIL_SLOWIndicates that the pipeline should continue to run until all possible tasks have been scheduled and completed.
    PipelineFailurePolicyFailFast
    PIPELINE_FAILURE_POLICY_FAIL_FASTIndicates that the pipeline should stop scheduling new tasks after a task has failed.
    PIPELINE_FAILURE_POLICY_UNSPECIFIED
    PIPELINE_FAILURE_POLICY_UNSPECIFIEDDefault value, and follows fail slow behavior.
    PIPELINE_FAILURE_POLICY_FAIL_SLOW
    PIPELINE_FAILURE_POLICY_FAIL_SLOWIndicates that the pipeline should continue to run until all possible tasks have been scheduled and completed.
    PIPELINE_FAILURE_POLICY_FAIL_FAST
    PIPELINE_FAILURE_POLICY_FAIL_FASTIndicates that the pipeline should stop scheduling new tasks after a task has failed.
    "PIPELINE_FAILURE_POLICY_UNSPECIFIED"
    PIPELINE_FAILURE_POLICY_UNSPECIFIEDDefault value, and follows fail slow behavior.
    "PIPELINE_FAILURE_POLICY_FAIL_SLOW"
    PIPELINE_FAILURE_POLICY_FAIL_SLOWIndicates that the pipeline should continue to run until all possible tasks have been scheduled and completed.
    "PIPELINE_FAILURE_POLICY_FAIL_FAST"
    PIPELINE_FAILURE_POLICY_FAIL_FASTIndicates that the pipeline should stop scheduling new tasks after a task has failed.

    GoogleCloudAiplatformV1PipelineJobRuntimeConfigResponse, GoogleCloudAiplatformV1PipelineJobRuntimeConfigResponseArgs

    FailurePolicy 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 string
    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 Dictionary<string, string>
    The runtime artifacts of the PipelineJob. The key will be the input artifact name and the value would be one of the InputArtifact.
    ParameterValues Dictionary<string, string>
    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.
    Parameters Dictionary<string, string>
    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.

    Deprecated: 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.

    FailurePolicy 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 string
    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 map[string]string
    The runtime artifacts of the PipelineJob. The key will be the input artifact name and the value would be one of the InputArtifact.
    ParameterValues map[string]string
    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.
    Parameters map[string]string
    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.

    Deprecated: 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.

    failurePolicy 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 String
    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 Map<String,String>
    The runtime artifacts of the PipelineJob. The key will be the input artifact name and the value would be one of the InputArtifact.
    parameterValues Map<String,String>
    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.
    parameters Map<String,String>
    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.

    Deprecated: 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.

    failurePolicy 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 string
    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 {[key: string]: string}
    The runtime artifacts of the PipelineJob. The key will be the input artifact name and the value would be one of the InputArtifact.
    parameterValues {[key: string]: string}
    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.
    parameters {[key: string]: string}
    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.

    Deprecated: 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.

    failure_policy str
    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.
    gcs_output_directory str
    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.
    input_artifacts Mapping[str, str]
    The runtime artifacts of the PipelineJob. The key will be the input artifact name and the value would be one of the InputArtifact.
    parameter_values Mapping[str, str]
    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.
    parameters Mapping[str, str]
    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.

    Deprecated: 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.

    failurePolicy 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 String
    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 Map<String>
    The runtime artifacts of the PipelineJob. The key will be the input artifact name and the value would be one of the InputArtifact.
    parameterValues Map<String>
    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.
    parameters Map<String>
    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.

    Deprecated: 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.

    GoogleCloudAiplatformV1PipelineTaskDetailPipelineTaskStatusResponse, GoogleCloudAiplatformV1PipelineTaskDetailPipelineTaskStatusResponseArgs

    Error Pulumi.GoogleNative.Aiplatform.V1.Inputs.GoogleRpcStatusResponse
    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.
    State string
    The state of the task.
    UpdateTime string
    Update time of this status.
    Error GoogleRpcStatusResponse
    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.
    State string
    The state of the task.
    UpdateTime string
    Update time of this status.
    error GoogleRpcStatusResponse
    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.
    state String
    The state of the task.
    updateTime String
    Update time of this status.
    error GoogleRpcStatusResponse
    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.
    state string
    The state of the task.
    updateTime string
    Update time of this status.
    error GoogleRpcStatusResponse
    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.
    state str
    The state of the task.
    update_time str
    Update time of this status.
    error Property Map
    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.
    state String
    The state of the task.
    updateTime String
    Update time of this status.

    GoogleCloudAiplatformV1PipelineTaskDetailResponse, GoogleCloudAiplatformV1PipelineTaskDetailResponseArgs

    CreateTime string
    Task create time.
    EndTime string
    Task end time.
    Error Pulumi.GoogleNative.Aiplatform.V1.Inputs.GoogleRpcStatusResponse
    The error that occurred during task execution. Only populated when the task's state is FAILED or CANCELLED.
    Execution Pulumi.GoogleNative.Aiplatform.V1.Inputs.GoogleCloudAiplatformV1ExecutionResponse
    The execution metadata of the task.
    ExecutorDetail Pulumi.GoogleNative.Aiplatform.V1.Inputs.GoogleCloudAiplatformV1PipelineTaskExecutorDetailResponse
    The detailed execution info.
    Inputs Dictionary<string, string>
    The runtime input artifacts of the task.
    Outputs Dictionary<string, string>
    The runtime output artifacts of the task.
    ParentTaskId string
    The id of the parent task if the task is within a component scope. Empty if the task is at the root level.
    PipelineTaskStatus List<Pulumi.GoogleNative.Aiplatform.V1.Inputs.GoogleCloudAiplatformV1PipelineTaskDetailPipelineTaskStatusResponse>
    A list of task status. This field keeps a record of task status evolving over time.
    StartTime string
    Task start time.
    State string
    State of the task.
    TaskId string
    The system generated ID of the task.
    TaskName string
    The user specified name of the task that is defined in pipeline_spec.
    CreateTime string
    Task create time.
    EndTime string
    Task end time.
    Error GoogleRpcStatusResponse
    The error that occurred during task execution. Only populated when the task's state is FAILED or CANCELLED.
    Execution GoogleCloudAiplatformV1ExecutionResponse
    The execution metadata of the task.
    ExecutorDetail GoogleCloudAiplatformV1PipelineTaskExecutorDetailResponse
    The detailed execution info.
    Inputs map[string]string
    The runtime input artifacts of the task.
    Outputs map[string]string
    The runtime output artifacts of the task.
    ParentTaskId string
    The id of the parent task if the task is within a component scope. Empty if the task is at the root level.
    PipelineTaskStatus []GoogleCloudAiplatformV1PipelineTaskDetailPipelineTaskStatusResponse
    A list of task status. This field keeps a record of task status evolving over time.
    StartTime string
    Task start time.
    State string
    State of the task.
    TaskId string
    The system generated ID of the task.
    TaskName string
    The user specified name of the task that is defined in pipeline_spec.
    createTime String
    Task create time.
    endTime String
    Task end time.
    error GoogleRpcStatusResponse
    The error that occurred during task execution. Only populated when the task's state is FAILED or CANCELLED.
    execution GoogleCloudAiplatformV1ExecutionResponse
    The execution metadata of the task.
    executorDetail GoogleCloudAiplatformV1PipelineTaskExecutorDetailResponse
    The detailed execution info.
    inputs Map<String,String>
    The runtime input artifacts of the task.
    outputs Map<String,String>
    The runtime output artifacts of the task.
    parentTaskId String
    The id of the parent task if the task is within a component scope. Empty if the task is at the root level.
    pipelineTaskStatus List<GoogleCloudAiplatformV1PipelineTaskDetailPipelineTaskStatusResponse>
    A list of task status. This field keeps a record of task status evolving over time.
    startTime String
    Task start time.
    state String
    State of the task.
    taskId String
    The system generated ID of the task.
    taskName String
    The user specified name of the task that is defined in pipeline_spec.
    createTime string
    Task create time.
    endTime string
    Task end time.
    error GoogleRpcStatusResponse
    The error that occurred during task execution. Only populated when the task's state is FAILED or CANCELLED.
    execution GoogleCloudAiplatformV1ExecutionResponse
    The execution metadata of the task.
    executorDetail GoogleCloudAiplatformV1PipelineTaskExecutorDetailResponse
    The detailed execution info.
    inputs {[key: string]: string}
    The runtime input artifacts of the task.
    outputs {[key: string]: string}
    The runtime output artifacts of the task.
    parentTaskId string
    The id of the parent task if the task is within a component scope. Empty if the task is at the root level.
    pipelineTaskStatus GoogleCloudAiplatformV1PipelineTaskDetailPipelineTaskStatusResponse[]
    A list of task status. This field keeps a record of task status evolving over time.
    startTime string
    Task start time.
    state string
    State of the task.
    taskId string
    The system generated ID of the task.
    taskName string
    The user specified name of the task that is defined in pipeline_spec.
    create_time str
    Task create time.
    end_time str
    Task end time.
    error GoogleRpcStatusResponse
    The error that occurred during task execution. Only populated when the task's state is FAILED or CANCELLED.
    execution GoogleCloudAiplatformV1ExecutionResponse
    The execution metadata of the task.
    executor_detail GoogleCloudAiplatformV1PipelineTaskExecutorDetailResponse
    The detailed execution info.
    inputs Mapping[str, str]
    The runtime input artifacts of the task.
    outputs Mapping[str, str]
    The runtime output artifacts of the task.
    parent_task_id str
    The id of the parent task if the task is within a component scope. Empty if the task is at the root level.
    pipeline_task_status Sequence[GoogleCloudAiplatformV1PipelineTaskDetailPipelineTaskStatusResponse]
    A list of task status. This field keeps a record of task status evolving over time.
    start_time str
    Task start time.
    state str
    State of the task.
    task_id str
    The system generated ID of the task.
    task_name str
    The user specified name of the task that is defined in pipeline_spec.
    createTime String
    Task create time.
    endTime String
    Task end time.
    error Property Map
    The error that occurred during task execution. Only populated when the task's state is FAILED or CANCELLED.
    execution Property Map
    The execution metadata of the task.
    executorDetail Property Map
    The detailed execution info.
    inputs Map<String>
    The runtime input artifacts of the task.
    outputs Map<String>
    The runtime output artifacts of the task.
    parentTaskId String
    The id of the parent task if the task is within a component scope. Empty if the task is at the root level.
    pipelineTaskStatus List<Property Map>
    A list of task status. This field keeps a record of task status evolving over time.
    startTime String
    Task start time.
    state String
    State of the task.
    taskId String
    The system generated ID of the task.
    taskName String
    The user specified name of the task that is defined in pipeline_spec.

    GoogleCloudAiplatformV1PipelineTaskExecutorDetailContainerDetailResponse, GoogleCloudAiplatformV1PipelineTaskExecutorDetailContainerDetailResponseArgs

    FailedMainJobs List<string>
    The names of the previously failed CustomJob for the main container executions. The list includes the all attempts in chronological order.
    FailedPreCachingCheckJobs List<string>
    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.
    MainJob string
    The name of the CustomJob for the main container execution.
    PreCachingCheckJob string
    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.
    FailedMainJobs []string
    The names of the previously failed CustomJob for the main container executions. The list includes the all attempts in chronological order.
    FailedPreCachingCheckJobs []string
    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.
    MainJob string
    The name of the CustomJob for the main container execution.
    PreCachingCheckJob string
    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.
    failedMainJobs List<String>
    The names of the previously failed CustomJob for the main container executions. The list includes the all attempts in chronological order.
    failedPreCachingCheckJobs List<String>
    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.
    mainJob String
    The name of the CustomJob for the main container execution.
    preCachingCheckJob String
    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.
    failedMainJobs string[]
    The names of the previously failed CustomJob for the main container executions. The list includes the all attempts in chronological order.
    failedPreCachingCheckJobs string[]
    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.
    mainJob string
    The name of the CustomJob for the main container execution.
    preCachingCheckJob string
    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.
    failed_main_jobs Sequence[str]
    The names of the previously failed CustomJob for the main container executions. The list includes the all attempts in chronological order.
    failed_pre_caching_check_jobs Sequence[str]
    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.
    main_job str
    The name of the CustomJob for the main container execution.
    pre_caching_check_job str
    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.
    failedMainJobs List<String>
    The names of the previously failed CustomJob for the main container executions. The list includes the all attempts in chronological order.
    failedPreCachingCheckJobs List<String>
    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.
    mainJob String
    The name of the CustomJob for the main container execution.
    preCachingCheckJob String
    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.

    GoogleCloudAiplatformV1PipelineTaskExecutorDetailCustomJobDetailResponse, GoogleCloudAiplatformV1PipelineTaskExecutorDetailCustomJobDetailResponseArgs

    FailedJobs List<string>
    The names of the previously failed CustomJob. The list includes the all attempts in chronological order.
    Job string
    The name of the CustomJob.
    FailedJobs []string
    The names of the previously failed CustomJob. The list includes the all attempts in chronological order.
    Job string
    The name of the CustomJob.
    failedJobs List<String>
    The names of the previously failed CustomJob. The list includes the all attempts in chronological order.
    job String
    The name of the CustomJob.
    failedJobs string[]
    The names of the previously failed CustomJob. The list includes the all attempts in chronological order.
    job string
    The name of the CustomJob.
    failed_jobs Sequence[str]
    The names of the previously failed CustomJob. The list includes the all attempts in chronological order.
    job str
    The name of the CustomJob.
    failedJobs List<String>
    The names of the previously failed CustomJob. The list includes the all attempts in chronological order.
    job String
    The name of the CustomJob.

    GoogleCloudAiplatformV1PipelineTaskExecutorDetailResponse, GoogleCloudAiplatformV1PipelineTaskExecutorDetailResponseArgs

    containerDetail Property Map
    The detailed info for a container executor.
    customJobDetail Property Map
    The detailed info for a custom job executor.

    GoogleCloudAiplatformV1PipelineTemplateMetadataResponse, GoogleCloudAiplatformV1PipelineTemplateMetadataResponseArgs

    Version 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...".
    Version 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...".
    version 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...".
    version 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...".
    version str
    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...".
    version 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...".

    GoogleCloudAiplatformV1ScheduleRunResponseResponse, GoogleCloudAiplatformV1ScheduleRunResponseResponseArgs

    RunResponse string
    The response of the scheduled run.
    ScheduledRunTime string
    The scheduled run time based on the user-specified schedule.
    RunResponse string
    The response of the scheduled run.
    ScheduledRunTime string
    The scheduled run time based on the user-specified schedule.
    runResponse String
    The response of the scheduled run.
    scheduledRunTime String
    The scheduled run time based on the user-specified schedule.
    runResponse string
    The response of the scheduled run.
    scheduledRunTime string
    The scheduled run time based on the user-specified schedule.
    run_response str
    The response of the scheduled run.
    scheduled_run_time str
    The scheduled run time based on the user-specified schedule.
    runResponse String
    The response of the scheduled run.
    scheduledRunTime String
    The scheduled run time based on the user-specified schedule.

    GoogleRpcStatusResponse, GoogleRpcStatusResponseArgs

    Code int
    The status code, which should be an enum value of google.rpc.Code.
    Details List<ImmutableDictionary<string, string>>
    A list of messages that carry the error details. There is a common set of message types for APIs to use.
    Message 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.
    Code int
    The status code, which should be an enum value of google.rpc.Code.
    Details []map[string]string
    A list of messages that carry the error details. There is a common set of message types for APIs to use.
    Message 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.
    code Integer
    The status code, which should be an enum value of google.rpc.Code.
    details List<Map<String,String>>
    A list of messages that carry the error details. There is a common set of message types for APIs to use.
    message 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.
    code number
    The status code, which should be an enum value of google.rpc.Code.
    details {[key: string]: string}[]
    A list of messages that carry the error details. There is a common set of message types for APIs to use.
    message 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.
    code int
    The status code, which should be an enum value of google.rpc.Code.
    details Sequence[Mapping[str, str]]
    A list of messages that carry the error details. There is a common set of message types for APIs to use.
    message str
    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.
    code Number
    The status code, which should be an enum value of google.rpc.Code.
    details List<Map<String>>
    A list of messages that carry the error details. There is a common set of message types for APIs to use.
    message 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.

    Package Details

    Repository
    Google Cloud Native pulumi/pulumi-google-native
    License
    Apache-2.0
    google-native logo

    Google Cloud Native is in preview. Google Cloud Classic is fully supported.

    Google Cloud Native v0.32.0 published on Wednesday, Nov 29, 2023 by Pulumi
    pulumi/pulumi-google-native