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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

Shaping Data with Grafana Transformations

Now that you understand how to connect data source queries to visualizations, we’re going to take a step back and look at one of the key features in Grafana’s visualization pipeline: the DataFrame. A DataFrame is an object that contains data received from a data source query and provides the source data for visualization.

In this chapter, we will learn more about DataFrames, their role in how Grafana visualizes data, and how to manipulate them using Grafana’s transformation operators. We will cover the following topics:

  • About Grafana DataFrames and transformations
  • Exploring the various transformation functions
  • Expanding analysis with a transformation
  • Chaining transformations into a visualization pipeline

First, we will answer the question of what a Grafana DataFrame is, its role, and how transformation operators affect it. Next, we will look at the most useful of the transformation operators...

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