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Telemetry signals

Telemetry signals are the data your systems generate to help you understand what’s happening inside your applications and infrastructure. Grafana Cloud supports four telemetry signals that work together to give you complete observability:

SignalWhat it capturesBest for
MetricsNumeric measurements over timeTrends, alerts, and aggregated views
LogsTimestamped text records of eventsError details, audit trails, and debugging
TracesEnd-to-end request flows across servicesRequest paths and latency breakdown
ProfilesCode-level performance dataCPU bottlenecks and memory allocation issues

Each signal answers different questions about your system’s behavior. Metrics tell you something is wrong, logs provide the details of what happened, traces show you the path a request took, and profiles reveal where your code spends time.

Why telemetry signals matter

Modern applications are distributed across multiple services, containers, and infrastructure layers. When problems occur, you need visibility into every layer to find the root cause quickly.

Telemetry signals provide this visibility by capturing data at different levels of granularity:

  • Metrics: give you the high-level view of system health and alert you when thresholds are breached.
  • Logs: capture the specific events and error messages that explain what went wrong.
  • Traces: connect the dots across services to show how a single request moved through your system.
  • Profiles: pinpoint the exact functions or queries causing performance issues.

Without telemetry signals, you’re guessing at causes instead of following evidence to solutions.

Benefits of using signals together

The real power of telemetry comes from using all four signals together. Grafana Cloud lets you correlate signals so you can move seamlessly from one to another during an investigation.

BenefitHow it helps
Faster root cause analysisJump from a metric alert to the related logs and traces without manually matching timestamps
Complete visibilitySee the full picture from infrastructure metrics to application code performance
Reduced context switchingQuery all signals in one place instead of jumping between disconnected tools
Proactive problem detectionCombine signals to identify issues before they affect users

When your signals share common labels like service and environment, you can click through from a latency spike in metrics to the specific slow trace, and then to the profile showing which function caused the delay.

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