Telemetry

What it is

Telemetry is the data that a system automatically generates about its own operation — metrics, logs, events, traces, and usage signals — that is collected for monitoring, analysis, and diagnosis. It is the raw material of continuous feedback and observability.

Why it exists

Systems are too complex to debug by guessing. Telemetry gives you an observable system: instead of wondering why a service is slow or failing, you collect structured data from it so you can measure, query, alert, and diagnose from real evidence.

Key ideas

• Kinds of telemetry:
  • Metrics — numeric, time-series measurements (CPU, latency, request count).
  • Logs — text/diagnostic events, often queryable with KQL.
  • Traces — end-to-end request/dependency paths (distributed tracing).
  • Usage/analytics telemetry — how users interact (page views, features used).
• Two planes in Azure: infrastructure/platform telemetry via Azure Monitor; application telemetry via Application Insights.
• Telemetry must be instrumented (app code, SDK, or built-in source), collected, stored, and acted on to be useful.

Exam notes

• Remember the telemetry sinks in Azure Monitor: Metrics, Activity Log, and Log Analytics (logs) — each holds a different kind of data.
• Differentiate infrastructure telemetry (Azure Monitor) from application telemetry (Application Insights).
• Telemetry is only valuable when it feeds alerts, dashboards, or a feedback loop — not when it just sits in a store.
• Know that Application Insights data is stored in a Log Analytics workspace and is KQL-queryable.

Related

continuous-feedback · azure-monitor · application-insights · azure-monitor-metrics · log-analytics · alerting · feedback-loop

📘 Source: Microsoft Learn — Telemetry