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Connecting machine learning to your existing cloud infrastructure. |
Aqueduct comes prepackaged with a large suite of resources which connect you to your data or compute systems.
With these resources, you can automatically run your machine learning workloads on any cloud infrastructure that you have and plumb them with your existing data. Our documentation is separated into:
- data-systems: Connectors to databases and storage systems.
- compute-systems: Connectors to cloud compute engines like Kubernetes and Databricks.
- container-registries: Container registries from which to pull custom Docker images to be used by Aqueduct operators.
We're constantly working to add support for new systems, so if there's something you'd like to see, let us know on our community Slack or on GitHub.
For more on how to configure and manage your resources, see guide.md.