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Learn Grafana 10.x

Learn Grafana 10.x

By : Salituro
3 (3)
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Learn Grafana 10.x

Learn Grafana 10.x

3 (3)
By: Salituro

Overview of this book

Get ready to unlock the full potential of the open-source Grafana observability platform, ideal for analyzing and monitoring time-series data with this updated second edition. This beginners guide will help you get up to speed with Grafana’s latest features for querying, visualizing, and exploring logs and metrics, no matter where they are stored. Starting with the basics, this book demonstrates how to quickly install and set up a Grafana server using Docker. You’ll then be introduced to the main components of the Grafana interface before learning how to analyze and visualize data from sources such as InfluxDB, Telegraf, Prometheus, Logstash, and Elasticsearch. The book extensively covers key panel visualizations in Grafana, including Time Series, Stat, Table, Bar Gauge, and Text, and guides you in using Python to pipeline data, transformations to facilitate analytics, and templating to build dynamic dashboards. Exploring real-time data streaming with Telegraf, Promtail, and Loki, you’ll work with observability features like alerting rules and integration with PagerDuty and Slack. As you progress, the book addresses the administrative aspects of Grafana, from configuring users and organizations to implementing user authentication with Okta and LDAP, as well as organizing dashboards into folders, and more. By the end of this book, you’ll have gained all the knowledge you need to start building interactive dashboards.
Table of Contents (23 chapters)
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1
Part 1 – Getting Started with Grafana
5
Part 2 – Real-World Grafana
16
Part 3 – Managing Grafana

Summary

This was an extensive chapter, and we covered a lot of ground. Observability is becoming a large, important technology sector and Grafana is keeping up by making its alerting capabilities more powerful and versatile.

In this chapter, we set up monitoring for both Docker and NGINX using InfluxDB as a data source. We created alert rules to query and analyze the data from our monitoring, used expressions to reduce the data to a single value, and created expressions to evaluate that value for violating conditions that might need to trigger an alert. We integrated Grafana contact points with email, PagerDuty, and Slack to receive our alerts with messages that contain annotation data set by our alert rules evaluation behavior. We also established notification policies to route our alert messages to different contact points based on the severity derived from alert rule labels. Finally, we briefly considered how to set up mute timings for when we might want to disable certain alert...

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