Intermittent failures under traffic spikes with RelayRouter: concurrency and retry design

You handle intermittent failures during traffic spikes on the client side with three controls: a bounded concurrency limit, retries with exponential backoff and jitter for transient errors, and a fallback to another model. RelayRouter exposes OpenAI, Anthropic and Gemini compatible endpoints, so one resilience design covers all three. Failed or errored requests are generally not billed, which means a bounded retry policy adds resilience without paying for the failed attempts.

Why do requests fail intermittently during traffic spikes?

Intermittent failures during spikes usually happen when a burst of simultaneous requests exceeds the capacity available at that moment, not because the integration is broken. When an application sends many calls at once, some time out or return transient errors while others succeed, so the failures look random from the client side. RelayRouter offers about 108 models across 19 public groups, listed at relayrouter.io/models. According to the official relayrouter.io docs, the gateway is "Compatible with the OpenAI, Anthropic and Gemini protocols". The same retry patterns therefore apply whether you call /v1/chat/completions, /v1/messages or /v1beta/models/{model}:generateContent. The facts here do not state rate or concurrency limits, so check current limits in the documentation and measure them under load rather than hard-coding assumptions.

How should you design concurrency and retries?

A resilient design caps concurrency on the client, retries transient failures with backoff, and stops after a fixed number of attempts.

1. Cap concurrency: use a semaphore or worker pool to limit in-flight requests. Raise the limit gradually while you watch error rates.
2. Classify errors: retry timeouts, connection resets and server-side or rate-limit responses. Do not retry authentication errors, such as an invalid Authorization: Bearer YOUR_API_KEY header, or malformed requests.
3. Back off with jitter: wait a randomized interval that grows between attempts, so your retries do not arrive as a second spike.
4. Bound attempts: set a maximum retry count and an overall deadline for each request.
5. Fall back: after repeated failures, switch models, for example from gpt-6-astra to gemini-3.8-flash.

According to the official relayrouter.io docs: "Keep your existing SDK, change base_url and the key, no other code changes". If a streamed response breaks partway through, retry the whole request.

What do retries cost on RelayRouter?

Retrying failed calls adds little cost, because failed or errored requests are generally not billed and the platform fee is $0. There is no minimum spend and no subscription, so you pay for successful usage. A successful duplicate call still consumes tokens, so make sure the retry logic does not resend requests that already succeeded. Settlement rates are CNY 0.6 per $1 of standard usage for the GPT group and CNY 2.0 per $1 for the Claude group, against a market reference of CNY 6.8 per $1. Some models have direct pricing. For example, deepseek-v4-flash costs CNY 1.1 per 1M input tokens and CNY 4.4 per 1M output tokens off-peak (doubled on weekdays 09:00 to 12:00 and 14:00 to 18:00 Beijing time), which can suit a lower-cost fallback tier. Live per-model rates are at relayrouter.io/models.

FAQ

These answers cover common questions about tuning retries on RelayRouter.

Are requests that fail during a spike billed? Failed or errored requests are generally not billed, and there is no minimum spend or subscription.

Does falling back across Claude, GPT and Gemini require code changes? No. You keep your SDK and change the base_url and key. Available models include claude-opus-5-5, claude-fable-5-1, GPT-6, GPT-5.6 and Gemini 3.8 Flash, plus DeepSeek, GLM, MiniMax and Moonshot.

What concurrency limit should I set? The facts here do not specify one. Start with a low cap, raise it while you monitor errors, and check the docs for current guidance.