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The Vertex AI Pipelines Template Gallery contains Google-authored pipeline templates and components, which you can use to create pipeline runs or embed in your own pipelines.
Create a pipeline run from the Template Gallery
Use the following instructions to create a pipeline run from a Google-authored template from the Template Gallery. Alternatively, you can create your own custom pipeline template and then create a pipeline run based on it. For more information about creating and using a custom pipeline template, see Create, upload, and use a pipeline template.
Console
Use the following instructions to create a pipeline run from the Template Gallery:
In the Google Cloud console, in the Vertex AI section, go
to the Template Gallery tab on the Pipelines page.
Optional: To filter the list of pipeline templates, in the left pane,
select the filter criteria. For example, to show only pipeline templates,
select Templates under Type.
On the card corresponding to the template that you want to use, click
Create run to open the Create pipeline run page.
In the Run details section, do the following:
Optional: Modify the default Run name that uniquely identifies the pipeline run.
Optional: To schedule recurring pipeline runs, specify the Run schedule, as follows:
Select Recurring.
Under Start time, specify when the schedule becomes active.
To schedule the first run to occur immediately after schedule creation, select Immediately.
To schedule the first run to occur at a specific time and date, select On.
In the Frequency field, specify the frequency to schedule and execute the
pipeline runs, using a cron schedule expression based on
unix-cron.
Under Ends, specify when the schedule ends.
To indicate that the schedule creates pipeline runs indefinitely, select Never.
To indicate that the schedule ends on a specific date and time, select On, and specify the end date and time for the schedule.
Optional: To specify that the pipeline run uses a custom service account, a
customer-managed encryption key (CMEK), or a peered VPC network, click
Advanced options, and then follow these instructions:
To specify a service account, select a service account from the
Service account drop-down list.
If you don't specify a service account,
Vertex AI Pipelines runs your pipeline using the default
Compute Engine service account.
To use a CMEK, select Use a customer-managed encryption key. The Select a customer-managed key drop-down list appears. In the Select a customer-managed key drop-down list, select the key that you want to use.
To use a peered VPC network in this pipeline run, enter the VPC
network name in the Peered VPC network box.
Click Continue.
In the Runtime configuration section, configure the pipeline run, as follows:
Under Cloud storage location, click Browse to select the
Cloud Storage bucket for storing the pipeline output artifacts,
and then click Select.
Optional: To configure the failure policy and the cache for the pipeline
run, click Advanced options, and then use the following instructions:
To configure the pipeline to continue scheduling tasks after one task
fails, select Run all steps to completion. This option is selected,
by default.
To configure the pipeline to fail after one task fails, select
Fail this run as soon as one step fails.
Under Caching configuration, specify the cache configuration for the
entire pipeline.
To use the task-level cache configuration for task in the pipeline,
select Do not override task-level cache configuration.
To turn on caching for all the tasks in the pipeline and override any
task-level cache configuration, select
Enable read from cache for all steps (fastest).
To turn off caching for all the tasks in the pipeline and override any
task-level cache configuration, select
Disable read from cache for all steps (fastest).
Optional: If your pipeline has parameters, under Pipeline parameters, specify
your pipeline run parameters.
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Hard to understand","hardToUnderstand","thumb-down"],["Incorrect information or sample code","incorrectInformationOrSampleCode","thumb-down"],["Missing the information/samples I need","missingTheInformationSamplesINeed","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2025-09-03 UTC."],[],[],null,["# Use a prebuilt template from the Template Gallery\n\nThe Vertex AI Pipelines **Template Gallery** contains Google-authored and components, which you can use to create pipeline runs or embed in your own pipelines.\n| **Note:** The **Template Gallery** contains pipeline templates and components that are generally available (GA) as well as templates in preview. To understand the terms of service of each template, refer to its associated documentation. For more information, see the [launch stage descriptions](/products#product-launch-stages).\n\nCreate a pipeline run from the Template Gallery\n-----------------------------------------------\n\nUse the following instructions to create a pipeline run from a Google-authored template from the **Template Gallery** . Alternatively, you can create your own custom pipeline template and then create a pipeline run based on it. For more information about creating and using a custom pipeline template, see [Create, upload, and use a pipeline template](/vertex-ai/docs/pipelines/create-pipeline-template). \n\n### Console\n\n| **Note:** These instructions describe how to create a pipeline run using the default interface of the **Create pipeline run** page, which includes the **Run details** and the **Runtime configuration** sections. For some templates from the **Template gallery** , this page has additional sections. For example, the **AutoML for Tabular Classification / Regression** template also includes the **Training Method** , **Training options** , and **Compute and pricing** sections.\n\nUse the following instructions to create a pipeline run from the **Template Gallery**:\n\n1. In the Google Cloud console, in the **Vertex AI** section, go\n to the **Template Gallery** tab on the **Pipelines** page.\n\n [Go to Template Gallery](https://console.cloud.google.com/vertex-ai/pipelines/vertex-ai-templates)\n2. Optional: To filter the list of pipeline templates, in the left pane,\n select the filter criteria. For example, to show only pipeline templates,\n select **Templates** under **Type**.\n\n3. On the card corresponding to the template that you want to use, click\n **Create run** to open the **Create pipeline run** page.\n\n4. In the **Run details** section, do the following:\n\n 1. Optional: Modify the default **Run name** that uniquely identifies the pipeline run.\n\n 2. Optional: To schedule recurring pipeline runs, specify the **Run schedule**, as follows:\n\n 1. Select **Recurring**.\n\n 2. Under **Start time**, specify when the schedule becomes active.\n\n - To schedule the first run to occur immediately after schedule creation, select **Immediately**.\n\n - To schedule the first run to occur at a specific time and date, select **On**.\n\n 3. In the **Frequency** field, specify the frequency to schedule and execute the\n pipeline runs, using a cron schedule expression based on\n [unix-cron](https://man7.org/linux/man-pages/man5/crontab.5.html).\n\n 4. Under **Ends**, specify when the schedule ends.\n\n - To indicate that the schedule creates pipeline runs indefinitely, select **Never**.\n\n - To indicate that the schedule ends on a specific date and time, select **On**, and specify the end date and time for the schedule.\n\n 5. Optional: To specify that the pipeline run uses a custom service account, a\n customer-managed encryption key (CMEK), or a peered VPC network, click\n **Advanced options**, and then follow these instructions:\n\n - To specify a service account, select a service account from the\n **Service account** drop-down list.\n\n If you don't specify a service account,\n Vertex AI Pipelines runs your pipeline using the default\n Compute Engine service account.\n\n Learn more about [configuring a service account for use with\n Vertex AI Pipelines](/vertex-ai/docs/pipelines/configure-project#service-account).\n - To use a CMEK, select **Use a customer-managed encryption key** . The **Select a customer-managed key** drop-down list appears. In the **Select a customer-managed key** drop-down list, select the key that you want to use.\n\n - To use a peered VPC network in this pipeline run, enter the VPC\n network name in the **Peered VPC network** box.\n\n 3. Click **Continue**.\n\n5. In the **Runtime configuration** section, configure the pipeline run, as follows:\n\n 1. Under **Cloud storage location** , click **Browse** to select the\n Cloud Storage bucket for storing the pipeline output artifacts,\n and then click **Select**.\n\n 2. Optional: To configure the failure policy and the cache for the pipeline\n run, click **Advanced options**, and then use the following instructions:\n\n - Under **Failure policy** , specify the failure policy for the entire\n pipeline. [Learn more about pipeline failure policies.](/vertex-ai/docs/pipelines/configure-failure-policy)\n\n - To configure the pipeline to continue scheduling tasks after one task\n fails, select **Run all steps to completion**. This option is selected,\n by default.\n\n - To configure the pipeline to fail after one task fails, select\n **Fail this run as soon as one step fails**.\n\n - Under **Caching configuration**, specify the cache configuration for the\n entire pipeline.\n\n - To use the task-level cache configuration for task in the pipeline,\n select **Do not override task-level cache configuration**.\n\n - To turn on caching for all the tasks in the pipeline and override any\n task-level cache configuration, select\n **Enable read from cache for all steps (fastest)**.\n\n - To turn off caching for all the tasks in the pipeline and override any\n task-level cache configuration, select\n **Disable read from cache for all steps (fastest)**.\n\n 3. Optional: If your pipeline has parameters, under **Pipeline parameters**, specify\n your pipeline run parameters.\n\n6. To create your pipeline run, click **Submit**."]]
