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Observability with Grafana

Observability with Grafana

By : Rob Chapman, Peter Holmes
4 (4)
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Observability with Grafana

Observability with Grafana

4 (4)
By: Rob Chapman, Peter Holmes

Overview of this book

To overcome application monitoring and observability challenges, Grafana Labs offers a modern, highly scalable, cost-effective Loki, Grafana, Tempo, and Mimir (LGTM) stack along with Prometheus for the collection, visualization, and storage of telemetry data. Beginning with an overview of observability concepts, this book teaches you how to instrument code and monitor systems in practice using standard protocols and Grafana libraries. As you progress, you’ll create a free Grafana cloud instance and deploy a demo application to a Kubernetes cluster to delve into the implementation of the LGTM stack. You’ll learn how to connect Grafana Cloud to AWS, GCP, and Azure to collect infrastructure data, build interactive dashboards, make use of service level indicators and objectives to produce great alerts, and leverage the AI & ML capabilities to keep your systems healthy. You’ll also explore real user monitoring with Faro and performance monitoring with Pyroscope and k6. Advanced concepts like architecting a Grafana installation, using automation and infrastructure as code tools for DevOps processes, troubleshooting strategies, and best practices to avoid common pitfalls will also be covered. After reading this book, you’ll be able to use the Grafana stack to deliver amazing operational results for the systems your organization uses.
Table of Contents (22 chapters)
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1
Part 1: Get Started with Grafana and Observability
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5
Part 2: Implement Telemetry in Grafana
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10
Part 3: Grafana in Practice
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15
Part 4: Advanced Applications and Best Practices of Grafana
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Chapter 13: Application Performance with Grafana Pyroscope and k6
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Index
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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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