> For the complete documentation index, see [llms.txt](https://docs.zata.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.zata.ai/manage/bucket.md). # Bucket #### Overview Buckets are the core storage containers in Zata, used to organize and store all data within the platform. A bucket acts as a logical container for objects such as files, backups, media, and application data. Each object stored in a bucket is identified by a unique object key, enabling structured and efficient data management. Zata buckets are **S3-compatible** and support standard object storage behavior, allowing seamless integration with commonly used S3 tools, SDKs, and applications. Access to buckets is managed through access keys and bucket policies, ensuring secure, controlled, and role-based data access. Buckets provide a **scalable, durable, and reliable** solution for storing and managing data across a wide range of use cases, including application storage, backups, analytics, and media management. --- # 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 dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter: ``` GET https://docs.zata.ai/manage/bucket.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal. 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.