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Observability Basics for Cloud Applications

Connect logs, metrics, traces and alerts to user-facing reliability questions for a cloud service.

Introduction

Observability is the ability to ask useful questions about a running system from the signals it produces. More logs do not automatically create more understanding. Start with a user-facing reliability objective, then collect the smallest set of metrics, logs and traces that explains whether the objective is being met.

Learning objective: Define three service-level indicators and design the telemetry needed to investigate a failed request.

How the topic works

Metrics show numeric behaviour over time, logs describe discrete events and traces follow work across components. A correlation or trace identifier connects these signals. Service-level indicators might measure successful requests, latency or freshness. Alerts should fire on actionable symptoms with enough context for an operator to choose the next step.

Observability investigation

Practical workflow

  1. Choose a user journey and define success, acceptable latency and availability.
  2. Instrument request count, error rate and duration with stable labels.
  3. Create structured logs containing severity, service and correlation ID without sensitive payloads.
  4. Propagate trace context across service and database calls.
  5. Build one alert with an owner, threshold, runbook and validation test.

Tools and technologies

  • OpenTelemetry concepts or SDK
  • Azure Application Insights
  • A dashboard and alert manager

Example

A save request exceeds its latency target. The metric shows a spike, the trace isolates a slow database call and logs with the same correlation ID show a connection-pool warning. The alert links to a runbook instead of merely stating that latency is high.

Common mistakes

  • Logging every payload without a question or retention plan
  • Using unbounded labels such as user IDs in metrics
  • Alerting on noisy technical events without user impact

Security and best practice

Redact secrets and personal data, restrict telemetry access and set appropriate retention. Treat logs as sensitive records rather than harmless debugging text.

Portfolio task

Build: Instrument a sample cloud API with request IDs, duration and error metrics. Create a dashboard, simulate one failure and document the evidence path from alert to root cause.

Key takeaways

  • Start from a reliability question.
  • Correlation connects otherwise isolated signals.
  • An alert needs ownership and an actionable runbook.

Curriculum connection