jnaapti

AI curriculum

Course outline for Observability Engineering

Troubleshooting requires evidence across service boundaries. Instrument a small application and connect logs, metrics, and traces to explicit reliability objectives.

Technology
AI Operations, Evaluation and Observability
Duration
4 hours
Modules
2 · 2 hours each
Level
Prerequisites listed

About Observability Engineering

Troubleshooting requires evidence across service boundaries. Instrument a small application and connect logs, metrics, and traces to explicit reliability objectives.

Observability Engineering Course Objectives

  • Instrument a service with useful telemetry.
  • Correlate logs, metrics, and distributed traces.
  • Define an SLO and inspect relevant signals.

Pre-requisites

  • Basic application development or operations experience.
  • Familiarity with HTTP services and command-line tools.

Lab Setup

  • Computer with a local application runtime and container support.
  • Use local OpenTelemetry, Prometheus, and Grafana tooling with synthetic traffic; hosted monitoring is not required.

Detailed Course Outline

Proposed modules

Module 1: Telemetry foundations

  • Logs
  • Metrics
  • Traces
  • OpenTelemetry

Practical outcome: Instrument a request path with correlated telemetry.

Module 2: Operational interpretation

  • Prometheus
  • Grafana
  • Distributed tracing
  • SLOs

Practical outcome: Build a dashboard and trace a failing request.

Practical exercise

  • Diagnose an injected service failure and explain its effect on a sample SLO.

How we train

Contact us for full course details, including duration, delivery options and lab requirements.

Ask about exercises, instructor feedback and the prior knowledge you need. Tool-specific courses marked provisional may become modules in a broader course.

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