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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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Concepts
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Authors (2):
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Rob Chapman Rob Chapman
Author Profile Icon Rob Chapman
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

Tracing Technicalities with Grafana Tempo

Grafana Tempo is the third telemetry storage tool from Grafana that we’ll discuss; it provides the capability to store and query trace data. This chapter will introduce the Tempo query language (TraceQL). TraceQL can be used to select and filter traces generated by your applications to gather insights from across traces; the language is very similar to LogQL and PromQL but tailored to trace data. In this chapter, we will explore the major tracing protocols and how they can be used to output traces from applications; this will help you make informed choices on which protocol to use in an application, or which protocols to support when collecting data. We’ll then explore the architecture of Tempo to understand how it can fulfill the need for a scalable platform for tracing.

We will cover the following main topics in this chapter:

  • Introducing Tempo and the TraceQL query language
  • Exploring tracing protocols
  • Understanding...
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