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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

Simulating logs with flog

As-is, this is a fairly limited view of Loki’s capabilities, largely because we haven’t fed it some real logging to work with. Let’s fix that by first adding some live logs and then configuring Promtail to scrape them. Taking a cue from the Loki documentation, we’ll use an open source logging generator called flog to generate fake logging. Next, we’ll create a configuration file for Promtail that will scrape those logs in real time.

flog is available as a Docker container, so we just need to add it as a service to our docker-compose.yml file:

    flog:
        image: mingrammer/flog:latest
    command: -l -d 1

The service entry for flog is very simple: pull the latest image and run it with the -l command-line option for continuous looping, and -d 1 to run with a delay interval of 1 second so that we don’t overwhelm Promtail.

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