| name | reviewing-observability-and-operability |
| description | Reviews changes for production operability: structured logs with consistent fields and correlation/trace IDs, right log levels with no PII, context-rich errors that wrap rather than swallow, golden-signal instrumentation and propagated trace context, liveness/readiness checks, kill switches for risky changes, graceful shutdown, and metric cardinality discipline. Use when reviewing logging, metrics, tracing, alerts, health checks, feature flags, or deploy/rollback paths. |
| provenance | {"taxonomy_version":"v0.9","built_from":[{"category":16,"source":"docs/research/cluster-4-runtime.md#16","hash":"a1b7c3b359329ad08a45a9425bc6d5e84aa0260976e7209d3fe96c94e8cb8397"}]} |
reviewing-observability-and-operability
Can you debug this in production at 3am? Logs, traces, health checks, kill switches, rollback.
When to use
Reviews changes for production operability: structured logs with consistent fields and correlation/trace IDs, right log levels with no PII, context-rich errors that wrap rather than swallow, golden-signal instrumentation and propagated trace context, liveness/readiness checks, kill switches for risky changes, graceful shutdown, and metric cardinality discipline. Use when reviewing logging, metrics, tracing, alerts, health checks, feature flags, or deploy/rollback paths.
Shape: diff — design-capable. Also works on design docs and plans: apply the same checks to the proposed states, data flows, and failure paths before any code exists. When the design doc is specifically a decision record (an ADR, RFC, or adoption/deprecation plan), also run the shared decision-record checklist on top of this lens's own topical checks: is the rationale actually recorded (not just the outcome); are the stated assumptions still current; is there a revisit-trigger; is an exit, rollback, or sunset path defined; were real alternatives weighed, not just the chosen option justified after the fact? A gap here is this lens's finding, reported the same way as a topical one — not a separate report.
Reviewer discipline
Report only real problems. If the code correctly handles the case, reply "No findings" and stop — do not invent issues. This guards against false positives on correct code; still report every genuine issue you do find, with its full detail.
Defects are the default; improvements are opt-in. By default this lens is defect-only: do not suggest changes to code that is already correct. When the team has opted up into improvement suggestions, a finding on already-correct code is admissible only as nit-severity, route: implementer (the author applies, defers, or ignores), and must clear the non-configurable anti-churn floor: it must genuinely improve — never offer a merely equivalent alternative — and must converge (once a dimension is as good as you can confidently make it, stop; never oscillate A→B then B→A, never re-order to an equivalent state). Defects keep the strict bar above regardless of this setting.
Team preferences. If the reviewed repo has .code-quality-atlas/preferences.md, apply it before reporting: a repo's .code-quality-atlas/preferences.md may set/tune this lens's thresholds or selection, and — being preference-tier — may suppress one of its findings outright (it never surfaces). Its improvement-valence directive is also what decides whether the "opted up" improvement-suggestion behavior above is active for this review. Absent the file, apply this lens's defaults exactly as written above.
Pre-existing defects in touched code are surfaceable, not yours to fix. When you notice a genuine defect this change did not introduce but that sits in the code this PR actually touches — the edited function or immediately adjacent lines — you may surface it, tagged "pre-existing — not introduced by this change." Like improvements it is opt-in and default-quiet (off unless the team opts up), route: implementer, and non-blocking: it informs the author's fix-now / file-a-ticket / ignore call and never sets this PR's verdict, because the diff did not cause it. Stay scoped to code the change touches — a repo-wide hunt is the audits' job, not this review — and never let it expand the PR's scope.
Top checks
The head of the full checklist — enough for a first pass without opening any reference file:
- Are logs structured (key-value/JSON) with consistent fields (timestamp, level, service, request/trace ID) rather than interpolated prose? Can you grep/query by field in production?
- Is the log level appropriate (no INFO spam in hot loops; real failures at ERROR; nothing security/PII-sensitive logged at any level)? Is there a correlation/trace ID threaded through so one request's logs are linkable?
- Do new failure paths emit a context-rich error (what operation, which inputs/IDs — non-sensitive, the wrapped cause) rather than a bare
error/stack with no story? Errors should wrap, not swallow, and not be both logged and rethrown (double-logging).
- For any new meaningful operation: is it instrumented with at least one of the four golden signals (latency histogram, error counter, throughput)? Are spans created and trace context propagated across service/async boundaries?
- Does a new service/endpoint expose liveness and readiness checks, and do readiness checks actually reflect dependency health (DB/cache reachable) without being so strict they flap?
- Risky/irreversible behavior change: is it behind a feature flag or kill switch so it can be disabled in prod without a redeploy? Is there a documented rollback?
- Startup/shutdown: does the service start only after dependencies are ready, and on shutdown drain in-flight work, stop accepting new requests, flush logs/metrics, and close connections (handle SIGTERM)? (Graceful shutdown.)
- Is there an SLI/SLO implied by this change, and is the data to measure it being emitted (good-event and total-event counts)? Don't alert on causes you can fix later; alert on user-facing symptoms.
Mechanizing these checks
Where a finding here is one a tool can catch deterministically, surface that as an advisory route: implementer note next to the finding: the hand review caught it this time, and wiring the matching tool from reference/tool-rules.md into CI gates it going forward. This is a suggestion to mechanize, not a defect — it never blocks a verdict, and it falls away on a repo that already runs the tool.
Process notes. If this lens misfired on this change — flagged correct code, missed an obvious issue squarely in its own scope, or its checklist didn't fit the change shape — say so in one line under synthesizing-review-findings's Process notes appendix; that is not a defect finding. Say nothing if the lens worked as intended — never invent a process note to fill the section.
Going deeper
- reference/heuristics.md — the full checklist; open it when the change sits squarely in this lens's domain.
- examples.md — concrete good/bad findings, and the output format to match.
- reference/tool-rules.md — static-analysis rules covering the mechanical subset; for wiring up linters, not needed for the judgment review itself.
- reference/sources.md — the research behind each check; for provenance, not needed during a review.
