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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
Author Profile Icon Rob Chapman
Rob Chapman
Peter Holmes Peter Holmes
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Peter Holmes
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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

Introducing Tempo and the TraceQL query language

Tempo and TraceQL are the newest of the tools and query languages we will explore in depth in this book. Like LogQL, TraceQL was built using PromQL as an inspiration and offers developers and operators a familiar set of filtering, aggregation, and mathematical tools that aid in the observability flow between metrics, logs, and traces.

Let’s have a quick look at how Tempo sees trace data:

  • Trace collection: Introduced in Chapter 2, a trace (or distributed trace) is a collection of data that represents a request propagating through a system. Traces are often collected from multiple applications. Spans are sent by each application to some form of collection architecture and, ultimately, to Tempo for storage and querying.
  • Trace fields: The following diagram introduces a simplified structure of a trace, similar to the simplified structure of logs, seen in Chapter 4, and traces, seen in Chapter 5:
Figure 6.1 – A simplified view of a trace containing four spans ...
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