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Observability with Grafana

You're reading from   Observability with Grafana Monitor, control, and visualize your Kubernetes and cloud platforms using the LGTM stack

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Product type Paperback
Published in Jan 2024
Publisher Packt
ISBN-13 9781803248004
Length 356 pages
Edition 1st Edition
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Authors (2):
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Rob Chapman Rob Chapman
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Rob Chapman
Peter Holmes Peter Holmes
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Peter Holmes
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Toc

Table of Contents (22) Chapters Close

Preface 1. Part 1: Get Started with Grafana and Observability
2. Chapter 1: Introducing Observability and the Grafana Stack FREE CHAPTER 3. Chapter 2: Instrumenting Applications and Infrastructure 4. Chapter 3: Setting Up a Learning Environment with Demo Applications 5. Part 2: Implement Telemetry in Grafana
6. Chapter 4: Looking at Logs with Grafana Loki 7. Chapter 5: Monitoring with Metrics Using Grafana Mimir and Prometheus 8. Chapter 6: Tracing Technicalities with Grafana Tempo 9. Chapter 7: Interrogating Infrastructure with Kubernetes, AWS, GCP, and Azure 10. Part 3: Grafana in Practice
11. Chapter 8: Displaying Data with Dashboards 12. Chapter 9: Managing Incidents Using Alerts 13. Chapter 10: Automation with Infrastructure as Code 14. Chapter 11: Architecting an Observability Platform 15. Part 4: Advanced Applications and Best Practices of Grafana
16. Chapter 12: Real User Monitoring with Grafana 17. Chapter 13: Application Performance with Grafana Pyroscope and k6 18. Chapter 14: Supporting DevOps Processes with Observability 19. Chapter 15: Troubleshooting, Implementing Best Practices, and More with Grafana 20. Index 21. Other Books You May Enjoy

Summary

In this chapter, you learned how to use TraceQL to query trace data stored in Tempo, which will help you build queries for dashboards using this rich data source. You have explored the Tempo user interface, so you will be confident in moving around the interface. Combined with the skills learned in Chapters 4 and 5 you will be confident in moving between log, metric, and trace data in Grafana to be able to observe the systems you work with.

We took a detailed look at the different protocols and libraries you can use when instrumenting an application, and we saw the levels of support those tools have across different programming languages. We also explored the HTTP headers that are used to propagate trace data between applications. This will help you choose the best way to instrument an application and how to work with applications that are already instrumented with tracing.

Finally, we looked at the Tempo architecture and how it can horizontally scale to support your...

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