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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

Displaying histogram data with the bar chart visualization

It turns out the answer to the first question is yes. Again, we can leverage transformations to shape our data in a way that makes it compatible with the bar chart. At this point, we’re going to break away from the pattern we’ve followed in this chapter in order to demonstrate a better workflow practice than simply creating the bare minimum to illustrate a concept.

The goal is to set up a visualization pipeline, both the Query and the Transform, to maximize our flexibility as we perform analysis. This way, if we want to produce multiple panels with different slices of data or different metrics, we don’t have to create entirely new panels each time. Follow these steps:

  1. Create a new bar chart visualization panel.
  2. Add the following query (raw editor): SELECT "magnitude", "cdi", "mmi", "sig", "depth" FROM "event" WHERE $timeFilter GROUP...

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