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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

Extracting and Visualizing Data with InfluxDB and Grafana

In the previous chapter, we concentrated our efforts on understanding how a data source is primary to the Grafana visualization workflow. We launched a Prometheus Docker container along with a Grafana server, scraped data from both applications, and then configured a Grafana data source to connect to the Prometheus server. Finally, we used the Explore module to get a feel for how to make various queries to the data source and get immediate feedback in the graph display.

While Explore is a powerful mechanism for browsing a data source, it is somewhat limited in functionality compared to the time series visualization This is not surprising as it’s mostly intended to support ad hoc, transient queries with more permanent graphs living on a dashboard. Those graphs have the advantage of providing several significant features that benefit presentation and alerting.

With that in mind, we’re going to take what we...

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