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When using a Domino on-demand Ray cluster, any data that is used, created, or modified as part of the interaction needs to go into an external data store.
On-demand clusters in Domino are ephemeral. Any data that is stored on cluster local storage and not externally is lost upon termination of the workload and the cluster.

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Use Domino Datasets

When you create a Ray cluster attached to a Domino workspace or job, any Domino dataset accessible from the workspace or job is also accessible from all components of the cluster under the same dataset mount path. You can then access the files from your code using the same path regardless of whether your code runs on your workspace of job container or in a Ray task on the cluster. For example, to read a file you would use the following:

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Using S3

To access Amazon S3 (or S3 compatible object store) data with Ray you can use any of the libraries you already use (for example, boto3, s3fs, or pandas). When access happens from Ray workers, the only prerequisite is to make sure that the relevant libraries and dependencies are available on both the base cluster environment and the execution environment.

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AWS credential propagation

When AWS credential propagation is enabled for your deployment, temporary AWS credentials corresponding to the roles enabled for you in your company identity provider are automatically available on all Ray worker nodes. The credentials are automatically refreshed and available under a profile name corresponding to each role in an AWS credential file. Ray worker code can then utilize these credentials for secure access.
Last modified on September 3, 2026