Introduction to Tempo for Distributed Tracing

Coursera MOOC / Non-credit USD 49
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Introduction to Tempo for Distributed Tracing

About this course

Distributed tracing has become essential for troubleshooting microservices at scale – 73% of organizations struggle with service dependencies visibility. This Short Course was created to help IT Support and Operations professionals accomplish effective microservices troubleshooting through Grafana Tempo distributed tracing. By completing this course, you'll be able to configure production-ready trace ingestion pipelines, identify performance bottlenecks through trace analysis, and correlate traces with logs for rapid incident resolution. By the end of this course, you will be able to: • Apply Tempo ingestion settings to route OpenTelemetry traces from Kubernetes services into a multi-tenant storage backend • Analyze trace visualizations to pinpoint inter-service latency hotspots and identify the upstream service causing a performance regression • Evaluate trace-to-logs correlations to confirm root cause and validate remediation effectiveness during post-incident review This course is unique because you'll work with real Kubernetes environments and enterprise-grade configurations using Tempo's multi-tenant architecture. To be successful in this project, you should have background experience with Kubernetes operations and basic observability concepts.

What you'll learn

  • Configure production-ready trace ingestion pipelines
  • Identify performance bottlenecks through trace analysis
  • Correlate traces with logs to facilitate rapid incident resolution

Course objectives

  • Apply Tempo ingestion settings to manage OpenTelemetry traces
  • Analyze trace visualizations to pinpoint performance issues
  • Evaluate trace-log correlations for effective incident management

Skills you'll gain

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