Metric Correlation

Definition

Metric correlation relates measurements to other telemetry using shared dimensions, time windows, and optionally exemplars.

Signals

• Metrics
• Traces
• Profiles

Why use it

Investigate a latency spike by narrowing it to a service and representative requests.

Common use cases

• Compare latency with saturation
• investigate error-rate spikes
• navigate from metrics to traces.

Benefits

• Starts with inexpensive aggregate signals and adds request-level evidence.

Limitations

• Aggregation hides individual requests. An exemplar is a sample, not a complete account of the population.

Practical pattern

Align service and environment labels, compare equivalent windows, and use trace exemplars where the instrumentation and backend support them.

Supported by

Documented examples, not an exhaustive compatibility list. Features require suitable instrumentation and configuration; availability can depend on the runtime, backend, and subscription.

• Grafana with Prometheus and Tempo — Exemplars link selected metric observations to traces when enabled.

Related concepts

• Trace Correlation
• Deployment Correlation
• Root Cause Analysis

Investigation patterns

• Metrics to Traces
• Deployments to Error Rate
• Infrastructure to Applications
• Trace to Profiles

Related guides

• What is Observability?
• What is MTTR?
• Grafana: Metrics to Traces with Exemplars
• Deployments: Compare Error Rate by Version
• Troubleshoot: Exemplars Missing in Grafana

FAQ

Should trace IDs be metric labels?

No. Each trace creates a new value and excessive cardinality. Use exemplar metadata for selected trace references.