You're reading from Building IoT Visualizations using Grafana Power up your IoT projects and monitor with Prometheus, LibreNMS, and Elasticsearch

Product type Paperback

Published in Jul 2022

Publisher Packt

ISBN-13 9781803236124

Length 360 pages

Edition 1st Edition

Tools

Elasticsearch

Concepts

IoT Development

Author (1):

Rodrigo Juan Hernandez

View More author details

Table of Contents (21) Chapters

Preface

1. Part 1: Meeting Grafana

2. Chapter 1: Getting Started with Grafana FREE CHAPTER

3. Chapter 2: Exploring Grafana

4. Part 2: Collecting Data from IoT Devices

5. Chapter 3: Connecting IoT Devices

6. Chapter 4: Data Sources for Grafana

7. Chapter 5: Using Time Series Databases

8. Part 3: Connecting Data Sources and Building Dashboards

9. Chapter 6: Getting Data and Building Dashboards

10. Chapter 7: Managing Plugins

11. Chapter 8: Organizing and Managing Dashboards

12. Part 4: Performing Analytics and Notifications

13. Chapter 9: Performing Analytics in Grafana

14. Chapter 10: Alerting and Notifications in Grafana

15. Part 5: Integrating Grafana with Other Platforms

16. Chapter 11: Using Grafana with Prometheus

17. Chapter 12: Using Grafana with OpenSearch

18. Chapter 13: Showing Data from LibreNMS in Grafana

19. Chapter 14: Integrations for Grafana Cloud

20. Other Books You May Enjoy

What is Prometheus?

Prometheus is an open source monitoring and alerting system. It was developed by SoundCloud in 2012, but at the time of writing, it is a standalone project. So, it is entirely maintained by the community, independently of any company.

The main features of Prometheus are as follows:

It has a multidimensional data model, with metrics pairs in key/value form.
It uses a flexible query language called PromQL.
It collects metrics using pulls over HTTP. You can also push metrics using a push gateway.
You can build dashboards using the tools provided by Prometheus. However, in this book, you will learn how to use Grafana for that purpose.

The metric definition in Prometheus is the same one that we have been using throughout this book. It consists of pairs of keys and values that are delivered in a time sequence. These metrics are stored in a time-series database.