> For the complete documentation index, see [llms.txt](https://developerdocs.instructure.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://developerdocs.instructure.com/services/canvas/basics/file.throttling.md). # Throttling Canvas includes a built in dynamic throttling mechanism to prevent a single user from abusing the system and causing adverse effects for others. It works by having a rate limit, and a cost for every request. Each request subtracts from your quota, and the quota is automatically replenished over time. In the event that your API request is throttled, you will receive a `429 Forbidden (Rate Limit Exceeded)` response. Your application should be prepared for this error, and retry the request at a later time. To assist applications with planning, every request will return a `X-Request-Cost` header that is a floating point number of the amount that request deducted from your remaining quota. If throttling is applicable to this request, there will also be a `X-Rate-Limit-Remaining` header of your remaining quota. Since the cost of a request is roughly based on the amount of time it takes to process, and the quota (by default) replenishes at a rate faster than real-time, any API client that makes no more than one simultaneous request is unlikely to be throttled. Parallel requests are subject to an additional pre-flight penalty to prevent a large number of incoming requests being able to bring the system down before their cost is counted against their quota. As soon as each request finishes, the pre-flight penalty is credited back to the quota, and only the actual cost of the request is counted. For applications that go through the OAuth flow and obtain an access token for each user, each access token has its own quota, and the developer need not be concerned with requests from one user causing another user to be throttled. *** This documentation is generated directly from the Canvas LMS source code, available [on Github](https://github.com/instructure/canvas-lms). --- # 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://developerdocs.instructure.com/services/canvas/basics/file.throttling.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.