What breaks when Helicone's proxy is slow or unreachable, and how do you limit the blast radius?

## Naming the dependency honestly The proxy integration's selling point is that it takes one line. The consequence is easy to under-state in an interview and expensive to under-state in production: after that one line, a third-party service is synchronously in front of every model call your application makes. Availability composes multiplicatively — your LLM feature is now up only when both the provider and the proxy are up — and latency composes additively on every request, including the tail. That is a legitimate trade for many workloads. It is not a trade you should make silently, and the interview question is whether you can articulate it and design around it. ## The three failure shapes **Hard down.** Connections refused or DNS failing. This is the kindest failure: it surfaces immediately, your error rate spikes, someone is paged, and the fix (route around it) is obvious. **Slow but up.** Requests still succeed, with extra hundreds of milliseconds or seconds added. This is the dangerous one. Nothing errors, so error-rate alerts stay quiet while user-visible latency degrades and, in a synchronous service, in-flight requests pile up and consume connections or threads. If your client has no read timeout, a hanging upstream can exhaust the pool and take down endpoints that never touch an LLM at all. **Partially degraded.** Some requests fine, some failing, often only for certain routes or regions. Retries make it worse if they are naive, because they multiply load against a struggling upstream. ## Mitigations, in the order I would apply them **1. Make the base URL configuration.** The single highest-value control. If `OPENAI_BASE_URL` (or your own equivalent setting) is read from the environment, going direct to the provider is a config change and a restart. If it is a string literal in the client constructor, it is a deploy under incident pressure. Rehearse the flip in a non-production environment so you know the app is healthy without the proxy — including that nothing else silently depends on gateway behaviour. **2. Bound every call with explicit timeouts.** Set connect and read timeouts on the HTTP client rather than inheriting a default of "forever". A bounded failure is recoverable; an unbounded one becomes a thread-pool outage. Size the read timeout against how long a legitimate completion actually takes, and remember that streaming needs a different rule — you care about time-to-first-token and inter-chunk gaps, not total duration. **3. Fall back, with a circuit breaker.** After N consecutive failures against the proxy host, trip to the provider host for a cooldown period, then probe. You lose traces while tripped, which is exactly the right thing to lose: observability should degrade before the product does. Keep the fallback dumb — one alternative host, no cascading chain. **4. Move critical paths off the request path entirely.** If a workload cannot accept the dependency at all, async logging is the structural answer: the provider call stays direct and log delivery becomes a best-effort background concern. The cost is losing gateway behaviour, so make that decision per workload rather than globally. **5. Alert on added latency, not just errors.** Compare your client-observed latency to the provider's reported processing time, or simply watch the p95 of calls through the proxy. A latency alarm catches the slow-and-up case that error-rate alarms miss by construction. **6. Consider self-hosting.** Running Helicone in your own infrastructure changes the failure domain rather than removing it — you now own the uptime — but it removes the third-party network dependency and answers the data-residency question at the same time. It is a real option for teams whose objection is governance as much as availability. ## The data-path question rides along While you are enumerating what the proxy means, do not skip what it sees. In proxy mode, full request and response bodies — prompts, retrieved documents, completions, whatever a user typed — pass through and are stored by a third party by default. For a regulated workload that consideration can outrank availability entirely, and the mitigations are different in kind: redact before you send, keep sensitive traffic off the proxy, or self-host. ## What a good answer sounds like A weak answer says "it just logs, so if it goes down we lose logs". That is true of async logging and false of the proxy, and the distinction is the entire question. A strong answer states the coupling plainly, distinguishes the hard-down case from the far more dangerous slow-and-up case, and names concrete controls — configurable base URL, bounded timeouts, circuit-broken fallback, latency alerting — while being explicit that dropping traces is the acceptable loss when the alternative is dropping traffic.