Observability Tracing and Monitoring
Run Replay
Domain: Observability, Tracing & Monitoring
Status: Implementation guidance / design checklist
Applicability: Depends on product architecture and risk
Concept
Separate deterministic event replay from LLM re-execution, which may produce different outputs.
Recommended Practices
- Specify which events and dimensions of Run Replay operators must inspect to diagnose incidents.
- Correlate traces by run ID; redact secrets; sample responsibly; define useful dashboards and alert thresholds.
- Define an owner, API/schema contract, failure response, and acceptance criteria for run replay.
- Add automated positive, negative, boundary, and permission tests for run replay; review metrics in staging and production.
Example Use Cases
- Incident investigators reconstruct the exact actions taken during a failed run.
- Apply run replay in a high-volume enterprise workflow while recording the user, project scope, input contract, and observable outcome.
Common Implementation Pitfalls
- Claiming byte-for-byte reproducibility without pinning state, responses, and versions.
- No documented fallback, operational owner, or signal showing when run replay is failing.
- Testing only happy paths while ignoring missing data, revoked access, malformed outputs, and partial outages.
Production Readiness Checklist
- An accountable owner and technical contract for run replay are documented.
- At least one successful and one failing end-to-end scenario is reproducible.
- Access controls, retention, and audit requirements are verified where relevant.
- Release monitoring includes a measurable success or failure signal for this capability.
Design Questions
- What concrete risk or business requirement requires Run Replay?
- What happens when it is unavailable, wrong, stale, or slow?
- How is its success evaluated against a trusted reference or observed outcome?
- Who can change its configuration, and how are changes released and rolled back?