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Runtime Environments in Anyscale Production Jobs and Services

The usage of runtime_env differs slightly when using Anyscale Production Jobs and Services as opposed to Ray Job Submission and all other Ray applications.

Differences for runtime_env with Anyscale Production Jobs and Services

  • The py_modules field only supports Remote URIs. It does not support local directories or '.whl' files.
  • The working_dir field does not support local .zip files. (Note however that .zip files hosted remotely as Remote URIs are still supported.)
  • The working_dir field supports local directories. However, if a local path is specified, the field upload_path must also be included in the runtime_env definition. The value of upload_path should be the path to a remote bucket in Amazon S3 or Google Cloud Storage; e.g. runtime_env = {"working_dir": "/User/code", "upload_path": "s3://my-bucket/subdir"}. The cluster running the job must have permissions to download from the bucket or URL. See Cloud Access Overview, or Using a Local Directory with Anyscale Jobs and Services on GCP if using GCP.

Like all Ray applications, Ray Job Submission and Ray Serve can be used on Anyscale with runtime_env behavior exactly as in OSS Ray. (For Ray Job Submission, you will need to set the environment variable RAY_ADDRESS to the address of your Anyscale cluster; e.g. anyscale://my-cluster.)

The differences above only apply to Anyscale Production Jobs and Services.