Coralogix

SRE and DevOps teams managing large microservice fleets face unsustainable manual alert configuration. A policy-driven health approach automatically enforces performance standards across all services, eliminating per-service threshold tuning. When a service breaches policy, the diagnostic workflow bridges metrics (which show 'what' is wrong) to traces and spans (which reveal 'why'). A worked example traces a latency issue in a shipping service from a high-level health policy breach down to a specific Kubernetes pod, using transaction-level breakdowns and slow-vs-healthy span comparisons to isolate the root cause. Key insight: health policies need 100% metric coverage, but troubleshooting quality depends on sampling rate—low sampling risks missing the slow traces needed to confirm a hypothesis.

Mastering the Diagnostic pivot from Health Policy to Pod

III. The Diagnostic Pivot: From Metric to Sample

IV. Deep Dive: Hypothesis Testing (The “Compare” Method)