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Coursera

Introduction to Tempo for Distributed Tracing

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Overview

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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.

Syllabus

  • Module 1: Getting Started with Tempo Ingestion Foundation
    • Configure Tempo ingestion settings to route OpenTelemetry traces from Kubernetes services into multi-tenant storage backends.
  • Module 2: Trace Visualization Analysis – Application
    • Analyze trace visualizations to pinpoint inter-service latency hotspots and identify upstream service causing performance regressions.
  • Module 3: Trace-to-Logs Correlation Evaluation – Advanced Implementation
    • Evaluate trace-to-logs correlations to confirm root cause and validate remediation effectiveness during post-incident review.

Taught by

Hurix Digital

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