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Observability with Grafana

Observability with Grafana

By : Rob Chapman, Peter Holmes
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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
5
Part 2: Implement Telemetry in Grafana
10
Part 3: Grafana in Practice
15
Part 4: Advanced Applications and Best Practices of Grafana

Enhancements and custom configurations

With all observability, you need to consider your use case. This is especially important when considering Frontend Observability as you will be operating in your visitor’s browser. There are several enhancements you can make to Frontend Observability over the default implementation. However, these enhancements come with the overhead of additional configuration, additional developer effort, and a potentially greater impact on your visitor’s browser. However, they can dramatically increase the value provided by Frontend Observability instrumentation.

Let’s explore the enhancements for Frontend Observability:

  • Frontend Tracing: This provides improved correlation between real user interactions and backend events. It requires the additional OpenTelemetry SDK configurations and adds some overhead to your visitor’s browser, so consider the implications carefully and test for any impact.
  • Custom Errors: This provides...

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