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Learn Grafana 10.x - Second Edition

You're reading from  Learn Grafana 10.x - Second Edition

Product type Book
Published in Dec 2023
Publisher Packt
ISBN-13 9781803231082
Pages 542 pages
Edition 2nd Edition
Languages
Author (1):
Eric Salituro Eric Salituro
Profile icon Eric Salituro

Table of Contents (23) Chapters

Preface 1. Part 1 – Getting Started with Grafana
2. Chapter 1: Introducing Data Visualization with Grafana 3. Chapter 2: Touring the Grafana Interface 4. Chapter 3: Diving into Grafana's Time Series Visualization 5. Part 2 – Real-World Grafana
6. Chapter 4: Connecting Grafana to a Prometheus Data Source 7. Chapter 5: Extracting and Visualizing Data with InfluxDB and Grafana 8. Chapter 6: Shaping Data with Grafana Transformations 9. Chapter 7: Surveying Key Grafana Visualizations 10. Chapter 8: Surveying Additional Grafana Visualizations 11. Chapter 9: Creating Insightful Dashboards 12. Chapter 10: Working with Advanced Dashboard Features and Elasticsearch 13. Chapter 11: Streaming Real-Time IoT Data from Telegraf Agent to Grafana Live 14. Chapter 12: Monitoring Data Streams with Grafana Alerts 15. Chapter 13: Exploring Log Data with Grafana’s Loki 16. Part 3 – Managing Grafana
17. Chapter 14: Organizing Dashboards and Folders 18. Chapter 15: Managing Permissions for Users, Teams, and Organizations 19. Chapter 16: Authenticating Grafana Logins Using LDAP or OAuth 2 Providers 20. Chapter 17: Cloud Monitoring AWS, Azure, and GCP 21. Index 22. Other Books You May Enjoy

Querying the Prometheus data source

Now that we have a whole ton of Prometheus and Grafana logging metrics, let’s play around with some more queries. I won’t be able to give you a full rundown of every aspect of PromQL—the Prometheus query language—but I can give you enough of a taste to be able to examine many of the server metrics that can be accessed via the Prometheus data source.

To get a better understanding of how queries work in time-series databases such as Prometheus, let’s first start with a more traditional database, such as MySQL. Typically, the structure of a query looks something like this:

SELECT some fields
    FROM some table
    WHERE fields match some criteria

You get back from the query some rows, each one containing the contents of some fields. In the case of time-series databases, things work a little differently. The query has a form that is more like the following:

SELECT...
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