LLM Gateway Observability
Logs Tell What; Traces Explain WhyLLM Gateway
Trace Every Decision
Trace client, route, provider, stream, and response to resolve incidents faster.
Published: March 21, 2026 · By the QVeris Team
TL;DR
Join identity, payload metadata, route policy, provider, model, guardrail, stream, usage, latency, cost and error spans.
Group requests, tool calls, feedback and user outcomes without losing per-request provenance.
Compare eligible candidates, selected route, fallback reasons and outcomes over time by workload and policy version.
Redaction, sampling, retention, access, regional storage, export and deletion determine whether rich telemetry is safe and useful.
Observability products emphasize different questions
Gateway suites combine routing controls with traffic evidence. Observability-first platforms center traces, sessions, prompts, evaluations, and feedback. General telemetry stacks accept OpenTelemetry signals but need AI-specific semantic conventions and product workflows.
Separate four questions that dashboards often mix together. Operations asks whether requests are succeeding within latency and capacity targets. Finance asks which tenant, route, model, cache, tool, and retry created the charge. AI quality asks whether the final result met a workload rubric. Governance asks who was allowed to send which data through which provider, region, and retention policy. One trace can connect the evidence, but each question needs its own fields and access controls.
No dashboard can compensate for missing identifiers or transformations. Capture trace context at the client, preserve it through every proxy and provider adapter, record the frozen candidate set and route decision before execution, attach native provider request IDs to every attempt, and correlate user-visible outcomes after the response. Record transformations without storing raw sensitive prompts by default.
Observability approaches
| Approach | Best fit | Verify before choosing |
|---|---|---|
| Gateway-integrated evidence | One system owns routing and records selected provider, fallback, guardrails, usage and cost. | Verify export, retention, session grouping, evaluations, feedback and independence from the synchronous path. |
| Observability-first platform | Deep developer workflows for requests, traces, sessions, prompts, scores, cost and feedback. | Clarify how routing policy and gateway decisions are captured and whether another proxy adds duplicate retries. |
| OpenTelemetry pipeline | Vendor-neutral collection into existing metrics, logs and traces with enterprise operations. | Define AI semantic fields, sensitive-data policy, evaluation joins and product-specific incident views. |
| Warehouse analytics | Flexible long-term analysis across usage, cost, experiments, quality and business outcomes. | Streaming diagnosis may be slow; preserve request-level IDs, schema, freshness and source-of-truth rules. |
| Application-only logging | Fast to start and fully customized for one product. | Provider changes, sessions, tools, fallback and cross-team governance become fragmented as the stack grows. |
Four evidence contracts
Trace, request, session, tenant, user, workload, experiment, prompt/version and policy identifiers.
Eligible candidates, scores, selected model/provider/endpoint, route reason, retries, fallback, cache and guardrails.
TTFT, total latency, stream events, input/output/reasoning/cache tokens, native usage, normalized cost and provider receipt.
Schema validity, tool success, evaluation, feedback, business result, sampling, redaction, retention, access and deletion.
Use the broken-session test
Choose a representative multi-step session and define what an on-call engineer must reconstruct: user-visible failure, tenant, policy version, eligible candidates, chosen route, every provider attempt, transformation, tool call, usage, charge, and final recovery. Then inject failures without giving the engineer application logs or database access. The observability system passes only if the evidence is sufficient to explain and verify the outcome.
- Instrument one workload end to end and verify trace continuity across client, gateway, provider, tool layer, and application response.
- Inject timeout, 429, 5xx, malformed or interrupted stream, guardrail denial, schema failure, provider fallback, and duplicate retry.
- Test telemetry loss, exporter backpressure, sampling, and storage outage; the request path must have a defined safe behavior.
- Give engineers only the observability system and time detection, reconstruction, root cause, mitigation, and verified recovery.
- Reconcile request counts, token and tool usage, retries, cache events, and cost against provider records and invoices.
- Test role-based access, prompt and secret redaction, regional storage, export, retention, deletion, and access review.
Capture decisions before effects
Create spans for authentication, eligibility, scoring, route decision, provider attempt, stream, guardrail and response. Freeze policy inputs and candidate scores at decision time. Carry trace context through provider metadata where supported and map native request IDs back into the gateway trace. Send telemetry asynchronously with bounded buffers and a safe failure mode.
Production rule: if the evidence cannot reproduce why a route happened, the system is monitoring traffic but not observing decisions.
Extend traces from inference into external action
Gateway traces explain the model call. QVeris adds search_id, execution_id, capability contract, estimated cost, downstream latency and result for external APIs and tools. Propagate one workflow trace so the team can connect reasoning evidence to action evidence.
Continue with related implementation guides
Use these adjacent guides to compare the next architectural decision, implementation boundary, or operating control without starting the research again.
FAQ
At minimum identity, trace, route policy, model/provider, attempts, errors, latency, usage and cost—with governed payload handling.
Use logs for discrete events and traces for causality across components and attempts. Metrics summarize fleet behavior.
Only under explicit data classification, redaction, consent, access, regional, retention and deletion policy.