Data Monitoring / Alerting & Observability Design
Observability: High-cardinality labels
Per-user or per-request labels make metric storage grow rapidly. Measure distinct label combinations and series creation rate.
Environment and inputs: Platform-neutral monitoring design with Prometheus and OpenTelemetry examples; syntax and signal availability depend on the deployed stack.
Failure scenario
Per-user or per-request labels make metric storage grow rapidly. Confirm the cause before choosing a fix.
Evidence to collect
Measure distinct label combinations and series creation rate. Record the time, affected scope and a healthy comparison interval.
Fix the confirmed cause
Use bounded operational dimensions and move detailed identifiers to an appropriate log or trace path. Write the expected result first. Change one relevant setting at a time.
Check the result and hand over
Repeat the check for high-cardinality labels using the same scope and a representative interval. Check that the symptom is resolved, expected records are present and downstream results are correct. If coverage, correctness or latency worsens, restore the recorded configuration through the agreed rollback process.
Scope and precautions
Prefer read-only access and limit queries to the relevant period or dataset. This example has not been tested on your systems. Test changes in an approved environment. Keep credentials and sensitive data out of shared evidence.