End-to-End Observability with Grafana: A comprehensive guide to observability and performance visualization with Grafana

Description

Grafana, a popular open-source observability platform, provides robust tools for analyzing and visualizing data from diverse sources. If you are looking to unlock its full potential as a data visualization and monitoring platform, then this book is for you.

This book offers a comprehensive insight into the capabilities of Grafana and empowers you to leverage this powerful tool to its fullest extent. It provides you with the knowledge and skills necessary to create impressive visualizations, establish dashboards, and optimize monitoring processes. The book will help you delve into various aspects of Grafana, including its interface, utilizing the Graph Panel for visualizing data, connecting it to data sources, organizing dashboards, harnessing advanced features, and exploring additional functionalities like Grafana Loki for log exploration and managing authorization and authentication. Furthermore, the book explores specific use cases such as blackbox exporter, synthetic monitoring, Kubernetes monitoring, AIOps monitoring, and maximizing Grafana plugins. It concludes by presenting best practices for working with Grafana and offering insights into setting up performance testing and engineering dashboards.

By the end of the book, you will be equipped with the necessary knowledge and skills to unlock its full potential as a data visualization and monitoring platform.

What you will learn

• Learn how to create visually appealing dashboards and panels using Grafana.
• Gain the ability to track and optimize application performance, ensuring an enhanced user experience.
• Utilize Grafana to record and analyze system applications.
• Track and analyze unique metrics for customized performance monitoring insights.

Who this book is for

This book is suitable for professionals in DevSecOps, Performance Testing, Site Reliability, AIOps, MLOps, Platform, Development, and Test Engineering teams.