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You can customize the runtime environment of user code in Dataflow
pipelines by supplying a custom container image. Custom containers are
supported for pipelines that use DataflowRunner v2.
When Dataflow starts up worker VMs, it uses Docker container
images to launch containerized SDK processes on the workers. By default, a
pipeline uses a prebuiltApache Beam image.
However, you can provide a custom container image for your Dataflow job.
When you specify a custom container image, Dataflow launches workers
that pull the specified image.
You might use a custom container for the following reasons:
Preinstall pipeline dependencies to reduce worker start time.
Preinstall pipeline dependencies that are not available in
public repositories.
Preinstall pipeline dependencies when access to public repositories is
turned off. Access might be turned off for security reasons.
[[["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 2025-09-04 UTC."],[[["\u003cp\u003eDataflow pipelines using Runner v2 support the use of custom container images to customize the runtime environment of user code.\u003c/p\u003e\n"],["\u003cp\u003eBy default, Dataflow pipelines use prebuilt Apache Beam images, but users can specify their own custom container images for their Dataflow jobs.\u003c/p\u003e\n"],["\u003cp\u003eCustom containers allow users to preinstall pipeline dependencies, including those not in public repositories, and to manage dependencies when access to public repositories is restricted.\u003c/p\u003e\n"],["\u003cp\u003eUsing custom containers also allows you to prestage large files and launch third-party software to customize the execution environment.\u003c/p\u003e\n"],["\u003cp\u003eThe main use cases of custom containers are to reduce worker start time, customize the environment, and to manage dependencies.\u003c/p\u003e\n"]]],[],null,["# Use custom containers in Dataflow\n\nYou can customize the runtime environment of user code in Dataflow\npipelines by supplying a custom container image. Custom containers are\nsupported for pipelines that use Dataflow\n[Runner v2](/dataflow/docs/runner-v2).\n\nWhen Dataflow starts up worker VMs, it uses Docker container\nimages to launch containerized SDK processes on the workers. By default, a\npipeline uses a prebuilt\n[Apache Beam image](https://hub.docker.com/search?q=apache%2Fbeam&type=image).\nHowever, you can provide a custom container image for your Dataflow job.\nWhen you specify a custom container image, Dataflow launches workers\nthat pull the specified image.\n\nYou might use a custom container for the following reasons:\n\n- Preinstall pipeline dependencies to reduce worker start time.\n- Preinstall pipeline dependencies that are not available in public repositories.\n- Preinstall pipeline dependencies when access to public repositories is turned off. Access might be turned off for security reasons.\n- Prestage large files to reduce worker start time.\n- Launch third-party software in the background.\n- Customize the execution environment.\n\nFor more information about custom containers in Apache Beam, see the\n[Apache Beam custom container guide](https://beam.apache.org/documentation/runtime/environments/).\nFor examples of Python pipelines that use custom containers, see\n[Dataflow custom containers](https://github.com/GoogleCloudPlatform/python-docs-samples/tree/main/dataflow/custom-containers).\n\nNext steps\n----------\n\n- [Build custom container images](/dataflow/docs/guides/build-container-image)\n- [Build multi-architecture container images](/dataflow/docs/guides/multi-architecture-container)\n- [Run a Dataflow job in a custom container](/dataflow/docs/guides/run-custom-container)\n- [Troubleshoot custom containers](/dataflow/docs/guides/troubleshoot-custom-container)"]]
