> For the complete documentation index, see [llms.txt](https://docs.duplicati.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.duplicati.com/technical-details/understanding-restore/disaster-recovery.md). # Disaster Recovery This page provides an overview of how disaster recovery is possible Duplicati is designed to be very careful when making backups, ensuring that all details are correct. At the same time it is designed to be very robust when performing restores, even when the data is partially incorrect. However, in a real emergency, it is important that data can be extracted from the backup. Data should be extracted, even if this situation happens in the future where the original client can no longer run on your systems, or if large parts of the backup files are damaged. Since the core restore algorithm is quite simple, albeit a bit slow, Duplicati has both a [recovery Python script](https://github.com/duplicati/duplicati/tree/master/Tools/Commandline/RestoreFromPython) for restoring, as well as a [C# recovery tool](/duplicati-programs/command-line-interface-cli-1/recoverytool.md). Altough both are distributed as part of Duplicati, they are developed independet of the main programs. These two tools require some extra space and a manual process, but are generally much simpler in implementation, making them less prone to errors and more robust in the face of uncertain data. --- # 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.duplicati.com/technical-details/understanding-restore/disaster-recovery.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.