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When an LLM gateway starts failing, first determine whether the problem is a quota or rate limit, a timeout or interrupted stream, an unexpected retry or provider switch, or gateway overload. Those patterns lead to different fixes. A 429 is not always the same limit, a timeout can stop a stream that is still producing tokens, and a successful final response can hide failed provider attempts.
These are four useful on-call patterns, not a statistically proven ranking of the most frequent incidents. Status codes and retry behavior vary by gateway and provider; treat the behaviors below as product-specific where noted.
Why am I getting 429 errors from my LLM gateway?
A 429 can come from several different gates: an organization request limit, a provider or model cap, a spending limit, or the upstream provider’s own rate limit. Don’t assume which one from the status code alone. Preserve the response body and headers, then check the gateway’s documentation for how it identifies each limit. LLMGateway, for example, treats upstream rate limits as provider errors that may qualify for retry or fallback, depending on routing configuration and available providers. Its rate-limit documentation distinguishes these from its documented HTTP 529 transient-overload response.
Once you identify the limiting gate, match the mitigation to it:
- For burst-related limits, smooth traffic or reduce concurrency rather than repeatedly resending requests at full speed.
- When a valid
Retry-Afterheader is present, honor it. If it is absent or invalid, use bounded exponential backoff with jitter. - Keep both the number of retries and the total time spent retrying bounded. OpenAI’s API rate-limit troubleshooting guidance also recommends limiting retries and total retry time.
- For a spending or account limit, retrying won’t create more quota; confirm the affected account or limit before changing traffic behavior.
Why did my streaming response time out?
A timeout may be a total-duration limit rather than an idle timer. That means it can terminate a generation even while tokens are still arriving. LLMGateway documents a 504 timeout response and applies its timeout limit per upstream attempt. A retry or provider fallback starts another attempt window, so elapsed end-to-end time can exceed the limit for any one attempt. See LLMGateway’s request-timeout documentation for its behavior.
First establish whether the request failed before the client received output or the stream stopped after output began. That boundary matters: once partial output has been delivered, a later failure may not be recoverable by transparently replaying the request.
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For useful diagnosis, retain or derive these fields where your gateway makes them available:
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- Provider, model, and time to first token
- Whether the stream terminated and whether a final stream chunk arrived
- Retry count and whether any output had already reached the client
Why did the gateway retry or switch providers?
Retries and fallback depend on the failure class and routing mode; they are not a blanket response to every failed request. LLMGateway’s routing documentation describes retries for selected provider- or gateway-side failures, including certain 5xx responses, timeouts, connection failures, upstream 429s, and some provider account or mapping problems. It says genuine client errors such as invalid requests are not retried. The routing documentation also notes two important boundaries: sticky routing can bypass cross-provider fallback, and an error after streaming output has reached the client ends the stream rather than transparently replaying the request.
To find out what actually happened, reconstruct the provider hops and inspect attempt-level errors alongside the final client result. Record the error classification, selected provider, retry count, credential source if exposed, and whether output had been committed. A request can succeed after a fallback even while the original provider continues to fail.
What does a 529 gateway-overloaded error mean?
In LLMGateway’s documented behavior, HTTP 529 signals transient gateway overload and is distinct from a quota-related 429. The documentation describes honoring Retry-After for this overload response. This is that vendor’s implementation—not a universal guarantee that every gateway uses 529 the same way. Check the gateway’s own documentation and response details before interpreting the code. LLMGateway’s rate-limit documentation explains its distinction.
Overload can coincide with slow upstreams and a buildup of in-flight inference calls. Correlate overload responses with active requests, upstream latency, concurrency, and provider-specific error rates. Adding unbounded retries can increase pressure; reduce or shape traffic, investigate slow upstreams, and keep retry counts and total retry time bounded.
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How to triage an LLM gateway incident
- Preserve the original response. Capture the status, error body, headers, request ID, model, provider mapping, and timestamp before a retry or configuration change obscures the evidence.
- Classify the failure. Separate invalid client input from a gateway-enforced limit or overload, an upstream provider error, a timeout, or a stream interruption.
- Reconstruct every attempt. Distinguish the final client response from individual provider attempts, and note whether output reached the client before the failure.
- Compare the affected route. Compare the failing provider/model mapping with viable alternatives, and group errors by type as well as by mapping. LLMGateway’s incident views document error counts and rates, upstream-versus-gateway split, status, stream state, and retry details: Airside for Providers.
- Apply a bounded mitigation. Reduce bursts or concurrency, honor retry guidance, adjust routing only when a viable alternative exists, or roll back a recent configuration change. Then reassess both success rate and latency.
How to compare routes during an incident
When more than one provider or route is viable, compare the factors that affect this failure rather than switching blindly. These are diagnostic axes, not a tested vendor ranking.
- Error class and observed availability
- Latency and timeout behavior
- Rate-limit and quota headroom
- Streaming and tool compatibility
- Fallback eligibility and retry boundaries
- Visibility into provider hops and individual attempts
Gateway behavior is implementation-specific. For example, Cloudflare’s official AI Gateway request-handling documentation describes routing, timeouts, retries, rate limiting, and budget limiting; consult the documentation for the gateway you operate before applying another product’s behavior to it.
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