Data Monitoring / Alerting & Observability Design
Observability: Sampling coverage limitations
Sampled traces show no errors while aggregate failures rise. Compare sampling policy with error counts and retained trace populations.
Environment and inputs: Platform-neutral monitoring design with Prometheus and OpenTelemetry examples; syntax and signal availability depend on the deployed stack.
Failure scenario
Sampled traces show no errors while aggregate failures rise. Confirm the cause before choosing a fix.
Evidence to collect
Compare sampling policy with error counts and retained trace populations. Record the time, affected scope and a healthy comparison interval.
Fix the confirmed cause
Use sampling suited to the diagnostic requirement and disclose the missing population. Write the expected result first. Change one relevant setting at a time.
Check the result and hand over
Repeat the check for sampling coverage limitations 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.