Principle:Helicone Helicone Asynchronous Log Queuing
| Knowledge Sources | |
|---|---|
| Domains | LLM Observability, Message Queuing, Asynchronous Processing |
| Last Updated | 2026-02-14 00:00 GMT |
Overview
Asynchronous log queuing is the technique of publishing structured log records to a durable message queue so that expensive processing (storage, analytics, webhooks) can occur independently of the latency-sensitive request-response path.
Description
In an LLM observability proxy, the time between receiving a response from the upstream provider and returning it to the client must be minimized. However, recording the full request-response pair -- including body storage, cost computation, webhook dispatch, and analytics insertion -- can take hundreds of milliseconds or more. Asynchronous log queuing solves this by decoupling the capture of the log data from its processing.
At the proxy layer, once the response has been received (or the response stream has begun), the proxy constructs a structured log message containing the request metadata (ID, user, properties, provider, target URL, timestamps), the response metadata (status, token counts, latency, cost), and references to the request/response bodies. This message is then published to a message queue. The proxy does not wait for the queue to acknowledge the message before returning the response to the client; instead, it uses a fire-and-forget pattern (via waitUntil in edge runtimes) to ensure the publish happens in the background.
The message queue provides durability, ordering, and backpressure. If the downstream consumer (the backend log processor) is temporarily unavailable, messages accumulate in the queue rather than being lost. This decoupling also allows the proxy and the backend to scale independently.
Usage
Use asynchronous log queuing whenever a proxy or gateway must capture telemetry without adding latency to the client-facing response. This pattern is appropriate when log processing involves multiple I/O-bound operations (database writes, object storage uploads, third-party webhook calls) that should not block the response path.
Theoretical Basis
The pattern is an instance of the Producer-Consumer concurrency model, where the proxy acts as a producer emitting log events and a separate backend service acts as a consumer processing them.
The theoretical flow is:
- The proxy completes the request-response exchange with the upstream provider.
- The proxy serializes the request metadata, response metadata, and body references into a structured message envelope.
- The producer publishes the message to a durable queue (Kafka, SQS, or similar).
- The producer optionally falls back to a synchronous HTTP POST to the backend if the queue is unavailable.
- The consumer (backend) pulls messages from the queue, processes them through a handler chain, and acknowledges successful processing.
Key properties of this design:
- At-least-once delivery: Messages may be delivered more than once; consumers must be idempotent.
- Ordering: Within a partition, messages are processed in order; across partitions, ordering is best-effort.
- Backpressure: If the consumer falls behind, the queue absorbs the surplus without affecting the proxy.