> For the complete documentation index, see [llms.txt](https://docs.release.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.release.com/guides-and-examples/advanced-guides/data/cloud-provided.md). # Cloud-provided data Release's [Instant Datasets](https://github.com/releasehub-com/docs/blob/main/advanced/data/broken-reference/README.md) is a feature that is currently limited to MySQL and Postgres databases. If your ephemeral environments rely on cloud database services such as [Amazon DynamoDB](https://aws.amazon.com/dynamodb/) or [Azure Cosmos DB](https://azure.microsoft.com/en-us/services/cosmos-db/), you are responsible for creating and maintaining the data that is associated with them. There are a number of ways you can do this: ### Data automation In the data automation approach to managing your data, one of the first steps in deploying an ephemeral environment would be to run Terraform or Pulumi to create the cloud resource and populate the data. Once this is done, you will be able to use this resource in your other services. ### Data pooling In the data pooling approach to managing your data, you would pre-create some number (N) of databases and create an [environment handle](/reference-documentation/account-settings/environment-handles.md) to round-robin distribute the environment variables that reference these databases to environments. When an environment is created, it "checks out" a handle and uses the associated credentials. You are responsible for the automation required to routinely reset the data in these databases on some periodic basis so that they are usable over time. --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation by asking a question. Perform an HTTP GET request on the following URL with the `ask` and `goal` query parameters: ``` GET https://docs.release.com/guides-and-examples/advanced-guides/data/cloud-provided.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is what the user is ultimately trying to achieve, the reason they need the answer. Sharing it helps GitBook give you a better, more relevant answer. A goal is most helpful when it describes the outcome the user wants rather than restating the question. For example, with `ask=how do I create an API token`, a goal like `automate deployments from our CI pipeline` lets GitBook tailor the answer to that use case. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.