Chapter 5 · Implement an Instrumentation Strategy·v2.0.0·Updated 6/3/2026·~10 min

What's changed: Deepened AZ-400 Chapter 5 (added comparison tables, scenarios, FAQs, exam traps, deep-dive paragraphs to each section; localized figures to Japanese)

5.1Designing Logging and Metrics

Key points

Understand observability foundations—Azure Monitor, Log Analytics (KQL), metrics, distributed tracing, and structured logs. Aggregate telemetry and make system state visible.

The final DevOps pillar is instrumentation. Aggregate logs, metrics, and traces to make state visible.

5.1.1Aggregating telemetry

Diagram of Azure instrumentation: from apps/infrastructure, the three pillars of telemetry—metrics (numeric time series), logs (structured logs aggregated into a Log Analytics workspace, analyzed with KQL), and distributed traces (request paths and latency)—are aggregated into Azure Monitor, visualized on dashboards, and fed to downstream alerts and feedback. — Aggregating telemetry

Azure Monitor: the observability hub aggregating metrics/logs/traces.
Log Analytics: a workspace aggregating logs, analyzed with KQL.
Metrics: numeric time series; the basis for threshold monitoring and autoscale.
Structured logs/traces: searchable structured logs and distributed traces across services for root cause.

Exam point

Common on AZ-400: monitoring hub = Azure Monitor, log aggregation + KQL = Log Analytics, numeric time series = metrics, cross-service latency tracing = distributed traces. Integrating the three pillars (metrics/logs/traces) speeds root-cause analysis.

Continue reading — free sign-up

You're reading the free preview. Sign up free to read this section in full, plus every chapter (including 4+) and all questions.

Get started free Log in