When would you choose Helicone's async logging over its proxy integration?
answer
- one mode sits in the path
- the other logs after the fact
- latency and uptime versus lost logs
- behaviour changes need in-path interception
- cache and policy imply proxy mode
basics
~20 sAsync logging keeps the provider call direct and ships the log separately, so Helicone adds no latency and cannot take your feature down. Choose it when the request path must stay untouched; choose the proxy when you want gateway behaviour, not just logs.
solid answer
~50 sHelicone offers two integration modes with the same dashboard behind them. In **proxy** mode you point the client's base URL at Helicone, and every provider call physically flows through Helicone — one extra hop, one extra dependency, and full visibility for free. In **async logging** mode your application calls the provider directly, exactly as before, and afterwards sends a log record to Helicone out of band (the `helicone-async` package wraps that for Python). The tradeoff is clean: async removes Helicone from the critical path, so its latency and availability stop mattering, but you now own log delivery — a dropped or failed log is simply a missing trace — and you lose anything that has to *act* on the request in flight. Gateway features such as caching, rate-limit policies and retries only exist in proxy mode, because changing the response requires being the one who answers it. I default to the proxy for internal and mid-tier traffic, and to async logging for latency-critical or high-availability paths.
go deeper
Know that Helicone has two integration styles and that only one of them puts Helicone between your app and the provider. Be able to say which one adds latency.
Explain the tradeoff in both directions: in-path means added latency and a new dependency, out-of-path means you own log delivery and can lose traces. Say clearly which features require interception.
Pick a mode per workload and defend it — async for user-facing latency-critical paths, proxy where gateway behaviour pays for itself — and describe how you would detect the silent failure of each.
Frame it as a dependency and data-governance decision for the whole fleet: what may transit a third party, what uptime your LLM features inherit, and whether observability is allowed to be able to fail the product.
## Two modes, one backend Helicone's product is the dashboard: requests, prompts, completions, latency, token counts, cost, sliced by whatever metadata you attached. There are two ways to get data into it, and interviewers ask about the choice because it is a real architectural decision rather than a config preference. **Proxy mode.** You change your client's base URL to Helicone's proxy host and add the `Helicone-Auth` header. Helicone receives the request, forwards it to the provider, receives the provider's response, logs the whole exchange, and returns the response to you. **Async logging mode.** You leave the client pointed at the provider. Your application makes the call exactly as it did before. Afterwards — outside the response path, ideally on a background task or queue — it sends a record of what happened to Helicone's logging endpoint. The `helicone-async` package exists to do that wrapping for you so you are not hand-building payloads at every call site. ## What each mode costs you The proxy's costs are all about being in the path: - **Latency.** One extra network hop on every call. Small relative to a model response, but not zero, and it is paid on the p99 too. - **Availability coupling.** If the proxy is unreachable or slow, your feature is unreachable or slow. Your LLM feature's uptime is now the product of the provider's uptime and Helicone's. - **Data flow.** Full request and response bodies — prompts, completions, anything a user typed — transit a third party's infrastructure by default. For some workloads that alone decides the question. Async logging's costs are all about owning delivery: - **You must send the log.** More integration work than a URL swap, and the record has to include what the dashboard needs: model, token usage, timings, status. If your code does not capture usage, the cost column suffers. - **Logs can be lost.** Fire-and-forget means a crash, a network blip or a full queue silently drops a trace. Observability degrades quietly, which is the failure mode you least like. - **No gateway behaviour.** This is the decisive one. ## Why gateway features need the proxy Logging is passive: it only has to *observe* what happened, so it can happen after the fact. Anything that changes the outcome of a call has to happen instead of the call — returning a stored response, refusing a request that breaches a quota, transparently retrying a provider failure. That can only be done by whoever is answering the request, which in async mode is the provider, not Helicone. So the moment your requirement list includes cache hits or policy enforcement, async logging is off the table and the availability conversation becomes unavoidable. The corollary matters too: if all you want is visibility and cost attribution, you do not have to accept a request-path dependency to get it. ## Choosing in practice A workable rule of thumb: - **Latency-critical, user-facing, or high-availability paths** — async logging. The observability layer must not be able to fail the product. - **Internal tools, batch jobs, evaluation runs, early-stage products** — proxy. The integration cost is minutes, and you get the gateway behaviour that actually saves money. - **Regulated or sensitive workloads** — neither by default; decide first what may leave your network at all, then choose between async logging with redacted payloads and a self-hosted deployment. Mixing modes across services is legitimate, and Helicone does not care: both modes land in the same project, so a request logged asynchronously and a request proxied appear side by side, filterable by the same custom properties. What differs is only how the row got there. ## The honest failure story The strongest answer names both failure stories rather than one. With the proxy, the failure is loud: calls fail or hang and someone pages you. With async logging, the failure is silent: traffic is healthy, but your traces have holes and you only discover it when you go looking during an incident. Neither is free; you pick which failure you would rather have, and you monitor for the one you chose.
- You switch a service from proxy to async logging. What stops working?Anything that had to alter the request or response in flight — served cache hits, quota enforcement, transparent retries — because your app now talks to the provider directly and Helicone only hears about the call afterwards. Plain logging, cost attribution, custom properties and session grouping all keep working, since they are properties of the log record rather than of interception.
- How do you keep async logging from adding latency of its own?Send the log off the response path: hand it to a background task, a local queue or a worker, and never block the user's response on the logging call succeeding. Bound the work with a short timeout and drop rather than retry indefinitely. Then monitor the drop rate, because a silently failing logger looks exactly like healthy traffic.
- Can both modes feed the same Helicone project?Yes. The mode is only how a record arrives; both land in the same project and are filterable by the same custom properties and user IDs. That makes a gradual migration practical — move the latency-critical service to async logging while the rest of the fleet stays proxied, and the dashboards stay coherent throughout.
saying these in an interview costs you the question
- Claiming async logging still gives you cache hits
- Saying the proxy adds no latency at all
- Treating dropped async logs as impossible
- Believing the two modes need separate Helicone projects
- Choosing the proxy for a latency-critical path without discussing uptime