 build to finish. More information: Build Timeout.We can register the image builder and use it in our active stack:

zenml image-builder register <IMAGE_BUILDER_NAME> \

--flavor=gcp \

--cloud_builder_image=<BUILDER_IMAGE_NAME> \

--network=<DOCKER_NETWORK> \

--build_timeout=<BUILD_TIMEOUT_IN_SECONDS>

# Register and activate a stack with the new image builder

zenml stack register <STACK_NAME> -i <IMAGE_BUILDER_NAME> ... --set

You also need to set up authentication required to access the Cloud Build GCP services.

Authentication Methods

Integrating and using a GCP Image Builder in your pipelines is not possible without employing some form of authentication. If you're looking for a quick way to get started locally, you can use the Local Authentication method. However, the recommended way to authenticate to the GCP cloud platform is through a GCP Service Connector. This is particularly useful if you are configuring ZenML stacks that combine the GCP Image Builder with other remote stack components also running in GCP.

This method uses the implicit GCP authentication available in the environment where the ZenML code is running. On your local machine, this is the quickest way to configure a GCP Image Builder. You don't need to supply credentials explicitly when you register the GCP Image Builder, as it leverages the local credentials and configuration that the Google Cloud CLI stores on your local machine. However, you will need to install and set up the Google Cloud CLI on your machine as a prerequisite, as covered in the Google Cloud documentation , before you register the GCP Image Builder.

Stacks using the GCP Image Builder set up with local authentication are not portable across environments. To make ZenML pipelines fully portable, it is recommended to use a GCP Service Connector to authenticate your GCP Image Builder to the GCP cloud platform.