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What API rate limiting does
Rate limiting controls how many requests a caller or resource can make during a period. The policy must define both the counting window or refill behavior and how the system identifies the caller. Those choices are implementation-specific: RFC 6585, section 4, does not prescribe a single caller-identification or counting method.
A common model is the token bucket. The bucket refills at a configured rate, and each request consumes a token. Its capacity determines how much traffic can arrive in a burst before requests are throttled. Rate and burst therefore describe different behavior: the rate governs sustained traffic, while capacity permits short spikes.
Choose between application code and a managed policy
| Decision point | Hand-built middleware or library | Managed gateway policy |
|---|---|---|
| Configuration scope | Defined by the application; it can reflect app-specific logic. | Can be configured at gateway-supported scopes, such as routes, methods, stages, or caller keys, depending on the provider and API type. |
| Burst behavior | Depends on the algorithm you implement or library you select. A token bucket supports bursts up to its capacity. | AWS API Gateway documents token-bucket throttling with rate and burst settings. |
| Counter sharing | An in-process counter may differ across application instances if requests are distributed among them. | The cited AWS and Azure documentation describes gateway policies but does not establish a neutral, cross-provider guarantee about counter sharing. |
| Response and retry guidance | Your implementation must return an appropriate response and decide whether to include retry guidance. | HTTP 429 behavior and retry metadata depend on the gateway and policy configuration. |
| Limit enforcement | Depends on your implementation and deployment. | AWS describes its throttling values as best-effort targets, not guaranteed hard ceilings. |
For a small, single-service application, middleware or a language library can be a reasonable fit, particularly when the desired policy is tightly coupled to application logic. If the application runs multiple instances, consider whether their counters need to be coordinated; separate in-process counters can produce different effective behavior from a centrally managed gateway. AWS recommends considering token-bucket libraries when API Gateway is not used, but the cited guidance does not evaluate particular libraries.
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A managed gateway is useful when a team wants policy configured centrally rather than embedded in each service. AWS API Gateway and Azure API Management are examples, not interchangeable products: their scopes, field names, and guarantees differ.
Where gateway limits can apply
AWS API Gateway REST APIs
AWS documents throttling at regional, account, API stage, method, and per-client usage-plan levels for REST APIs. Its documented precedence is per-client or per-method usage-plan limit, then per-method stage limit, account limit, and AWS regional throttle. A more specific setting does not eliminate the broader limits above it. In this model, the rate is the token refill rate per second and burst is the bucket capacity. See AWS’s REST API throttling documentation for the scope and precedence details.
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AWS API Gateway HTTP APIs
HTTP APIs support route-level throttling configuration. AWS characterizes these throttling settings as best-effort targets: traffic can exceed the configured rate or burst in some cases. Treat the values as operational controls to test, not as a promise of an exact maximum. The HTTP API throttling documentation includes a route-level configuration example and CLI command.
Azure API Management
Azure API Management’s rate-limit-by-key policy lets you specify the number of calls, a renewal period, and a counter key. Optional settings include an increment condition or count and metadata such as retry-after and remaining calls. The policy reference’s example allows 10 calls per 60 seconds using the caller’s IP as the key; that is an example, not a recommended default. The reference, dated November 14, 2025, documents a maximum renewal period of 300 seconds for this policy. Review the Azure policy reference for its exact fields and behavior.
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How to configure a limit safely
- Choose the scope. Decide whether the limit applies to the whole API, a route or method, or an identified caller. Confirm how the gateway identifies callers and how overlapping limits interact.
- Set sustained rate and burst separately. For a token bucket, choose the refill rate and capacity based on expected traffic and backend tolerance. Do not treat the burst allowance as a sustainable request rate.
- Configure the matching policy. In AWS API Gateway, use the supported stage, method, route, or usage-plan settings for the API type and scope you chose. In Azure API Management, configure the relevant
rate-limit-by-keyvalues, including the counter key. These are vendor-specific settings rather than universal form-field names. - Define the client response. When a caller exceeds its limit, return HTTP 429. RFC 6585 says the response representation should explain the condition and may include
Retry-After. Clients should respect that guidance instead of retrying immediately. The RFC also says caches must not store 429 responses. - Load-test and document the result. Test proposed limits under representative traffic and record the values and conditions you tested before raising them. AWS’s guidance recommends testing and documenting intended limits; this is especially important where configured gateway values are best-effort targets.
What to do when a rate limit is reached
HTTP status 429 means the caller sent too many requests in a given amount of time. The definition comes from RFC 6585, published by the IETF in April 2012. A server may include Retry-After to indicate when the client should try again. A well-behaved client should wait accordingly rather than retrying in a tight loop, which can add load while the service is already throttling traffic.
For traffic that should be delayed rather than rejected, AWS reliability guidance discusses buffering with services such as SQS or Kinesis. For rate rules aimed at specific consumers, it also describes AWS WAF as an option. These approaches address different needs: throttling controls admission, while buffering can smooth work over time.
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Which approach should you use?
- Use application-level limiting when the policy is simple, belongs to one service, and you can account for how counters behave across instances.
- Use a managed gateway policy when centralized configuration or limits at route, method, stage, or caller-key scope are important.
- Add buffering when the system can accept work for later processing instead of requiring each request to be handled immediately.
- Verify the guarantee you need. A best-effort throttle target is not the same as a hard capacity boundary. If exceeding the configured target would be unsafe, test the behavior and design an additional safeguard.
There is no neutral benchmark in the cited documentation that establishes one approach as faster or more reliable across vendors. Compare the actual scope, burst behavior, counter behavior, response metadata, visibility, and enforcement characteristics of the implementation you plan to deploy.
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