# Observability — what certctl emits, what it doesn't, and what survives a restart > Last reviewed: 2026-05-13 Use this when: - You're sizing certctl's observability surface against your existing metrics + tracing + logging stack and want to know exactly what drops in cleanly and what gaps you'll need to bridge. - You're investigating a "weird metric" or planning a Grafana dashboard and need the canonical list of what's exposed. - You're running multi-replica or restarting frequently and need to understand which counters reset. certctl's observability posture is deliberately minimal-but-honest: ship the surfaces an operator actually needs to wire into a Prometheus + Grafana + Loki stack, and don't make claims the implementation can't back. This document is the canonical statement of what's emitted, what's deferred, and why. ## Metrics — what's emitted certctl exposes metrics through two endpoints on the control plane: | Endpoint | Content-Type | Audience | |---|---|---| | `GET /api/v1/metrics` | `application/json` | Dashboards that prefer JSON, ad-hoc curl | | `GET /api/v1/metrics/prometheus` | `text/plain; version=0.0.4; charset=utf-8` (Prometheus exposition) | Prometheus, Grafana Agent, Datadog Agent, Victoria Metrics, any OpenMetrics-compatible scraper | The Prometheus endpoint emits standard `# HELP` / `# TYPE` / metric lines following the conventions at [prometheus.io/docs/instrumenting/exposition_formats](https://prometheus.io/docs/instrumenting/exposition_formats/). Metric names are lowercase, snake_case, and prefixed with `certctl_`. The implementation is at [`internal/api/handler/metrics.go`](../../internal/api/handler/metrics.go). ### What's covered Run the endpoint against a live deployment for the authoritative list (it expands as the service ships more metrics). At time of writing the exposition includes: - Certificate-inventory gauges: `certctl_certificate_total`, `certctl_certificate_active`, `certctl_certificate_expiring_soon`, `certctl_certificate_expired`, `certctl_certificate_revoked`. - Per-issuer-type issuance histograms: `certctl_issuance_duration_seconds{issuer_type=…}` (the 2026-05-01 issuer-coverage audit closure #4 — this is the load-bearing metric for per-issuer SLOs). - Server uptime: `certctl_uptime_seconds`. ### Prometheus library vs hand-rolled exposition (acquisition diligence) certctl writes Prometheus exposition format with `fmt.Fprintf` from the metrics handler, not via the `github.com/prometheus/client_golang` library. This is intentional for v2.x: - The metric surface is shallow (gauges + a handful of histograms with static labels). The client library's value is on the registration + thread-safe accumulation side, neither of which is load-bearing for the current surface. - The exposition output is pinned to the spec version explicitly (`version=0.0.4`) and is unit-tested against expected output at `internal/api/handler/stats_handler_test.go`. - Swapping in `client_golang` is a mechanical migration when the metric surface grows (per-connector counters + RED-method histograms on every handler are the natural next surface), but it has no operator-visible behavior change today. The migration is on the [WORKSPACE-ROADMAP.md](../../WORKSPACE-ROADMAP.md) as a v3 item. If you're an acquirer reading this: the question to ask is "does the metric surface meet our SLO needs today" — not "is the right library under the hood." If the answer to the first question is yes, the second is a refactor, not a feature gap. ## Tracing — explicitly not yet shipped certctl does **not** ship distributed tracing instrumentation today: - No OpenTelemetry SDK setup in `cmd/server/main.go`. - No OTLP exporter wired into outbound calls (issuer connectors, agent enrollment, etc.). - The `go.opentelemetry.io/otel` packages that appear in [`go.mod`](../../go.mod) are indirect-only — they're transitive dependencies of `coreos/go-oidc` and similar. This is honest: there is no in-process tracing surface to monitor, correlate, or sample. If your environment requires end-to-end traces across the certctl control plane + agents + issuer backends, this is a gap you would close on the certctl side as part of a v3 work item. Until then: - Structured logs include a `request_id` you can correlate across the server log stream. See [`internal/api/middleware/request_id.go`](../../internal/api/middleware/request_id.go). - The Prometheus histogram `certctl_issuance_duration_seconds{issuer_type=…}` carries the same per-issuer latency signal a trace span would, just without the per-request fan-out. OpenTelemetry instrumentation is tracked in [WORKSPACE-ROADMAP.md](../../WORKSPACE-ROADMAP.md) as a v3 item. ## Logging certctl emits structured JSON logs to stdout via the stdlib `log/slog` package. Every line carries `time`, `level`, `msg`, and — where relevant — `request_id`, `actor_id`, and a contextual subject (`certificate_id`, `issuer_id`, `agent_id`, etc.). Log level is controlled by `CERTCTL_LOG_LEVEL` (`debug` / `info` / `warn` / `error`); defaults to `info`. There is no in-process log ingest — operators are expected to collect from container stdout into their existing log pipeline (Loki, CloudWatch Logs, Datadog, ELK, Splunk, etc.). No log line contains private-key material, bearer tokens, OIDC client secrets, or session cookies. The break-glass login path explicitly scrubs the password before it reaches the audit subsystem (see [`docs/operator/auth-threat-model.md`](auth-threat-model.md) § "Break-glass token leak"). ## Rate-limit behavior under restarts and replicas Where rate limits exist, they are **per-process, in-memory, reset-on-restart, and not shared across replicas**. This matters for multi-replica deployments and for any compliance posture that asks "what limits apply globally vs per-pod." ### Inventory | Limiter | Scope | Window | Cap | Survives restart? | Shared across replicas? | |---|---|---|---|---|---| | Break-glass login (per source-IP) | `internal/api/handler/auth_breakglass.go` | 60s | 5 attempts | No | No | | SCEP/Intune per-device challenge | `internal/scep/intune/` | 60s | configurable (`*_PER_MINUTE`) | No | No | | EST per-principal CSR enrollment | `internal/est/` | 60s | configurable | No | No | | EST HTTP-Basic source-IP failed-auth | `internal/est/` | 60s | configurable | No | No | | ACME per-account orders / key-change / challenge-respond | `internal/service/acme.go` | 1h | configurable | No | No | All five use the shared `internal/ratelimit/sliding_window.go` primitive. Buckets live in a single per-process map guarded by a mutex; the package-level cap prevents unbounded growth under adversarial key cardinality (default 100,000 keys; oldest-by-newest- timestamp evicted under pressure). ### Implications for multi-replica deployments - **Effective per-replica cap is the documented cap.** A 2-replica deployment lets through up to 2× the per-key window cap before either replica rejects. - **Restart resets the bucket.** A `kubectl rollout restart` empties the in-memory windows on every replica. An attacker who notices this could in principle re-issue burst attempts after every roll; the threat model accepts this because rollouts are operator-driven and the relevant endpoints already require credentials. - **No cross-replica fan-out.** Rate-limit decisions on replica A are not visible to replica B. Sticky-session ingress routing (with `service.spec.sessionAffinity: ClientIP` on Kubernetes or the equivalent on your load balancer) tightens the effective cap to per-replica + per-source-IP rather than per-replica + per-source-IP for whichever pod the request happened to land on. If your threat model requires globally-enforced rate limits across replicas, the implementation surface is roughly: swap the per-process map for a database-backed sliding window (or a Redis-backed equivalent if you already run Redis). This is on the [WORKSPACE-ROADMAP.md](../../WORKSPACE-ROADMAP.md) as a v3 item; nothing in the certctl threat model today requires it. ### Where these numbers live The configurable caps are exposed as `CERTCTL_*_PER_MINUTE` / `CERTCTL_ACME_*_PER_HOUR` env vars — see the [security posture](security.md) doc for the operator-facing configuration surface. The hard-coded ones (break-glass 5/min) are intentionally non-configurable as a defense-in-depth measure; the auth subsystem owns that policy decision. ## Performance harness scope The load-test harness at [`deploy/test/loadtest/`](../../deploy/test/loadtest/) covers the API-tier hot paths (issuance acceptance + cert list). It does NOT load-test issuer-connector round-trips (you'd be load- testing someone else's API), full multi-RTT ACME enrollment flows, bulk-revoke / bulk-renew admin paths, or scheduler concurrency under bulk renewal. Each exclusion is justified in [`deploy/test/loadtest/README.md`](../../deploy/test/loadtest/README.md) under "What it explicitly does NOT measure." If your evaluation requires a benchmark on one of those exclusions, the right next step is a follow-up scenario in that directory. The per-component benchmarks ship in-tree as Go `Benchmark*` functions: - `internal/auth/session/bench_test.go` — session signing + validation steady state and cold-process timing. - `internal/auth/oidc/bench_test.go` — OIDC verify steady state. - `internal/auth/oidc/bench_keycloak_test.go` — OIDC cold-cache timing (gated `//go:build integration`). Authoritative benchmark numbers + threshold contracts: [`docs/operator/auth-benchmarks.md`](auth-benchmarks.md) (auth subsystem) and [`docs/operator/performance-baselines.md`](performance-baselines.md) (general API tier). ## Related reading - [`docs/operator/security.md`](security.md) — the broader hardening posture; this document is its observability subset. - [`docs/operator/performance-baselines.md`](performance-baselines.md) — operator-runnable benchmarks against the API tier - [`docs/operator/auth-benchmarks.md`](auth-benchmarks.md) — session + OIDC validation timings + threshold contracts - [`deploy/test/loadtest/README.md`](../../deploy/test/loadtest/README.md) — k6 load-test harness scope + threshold contract - [`docs/operator/runbooks/postgres-backup.md`](runbooks/postgres-backup.md) — operator-run backup recipe (separate file because it's a procedural runbook, not an observability claim)