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Learn Grafana 10.x

You're reading from   Learn Grafana 10.x A beginner's guide to practical data analytics, interactive dashboards, and observability

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Product type Paperback
Published in Dec 2023
Publisher Packt
ISBN-13 9781803231082
Length 542 pages
Edition 2nd Edition
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Author (1):
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Eric Salituro Eric Salituro
Author Profile Icon Eric Salituro
Eric Salituro
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Table of Contents (23) Chapters Close

Preface 1. Part 1 – Getting Started with Grafana
2. Chapter 1: Introducing Data Visualization with Grafana FREE CHAPTER 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

Exploring Log Data with Grafana’s Loki

In this final chapter of Part 2, Real-World Grafana, we’re going to shift gears a bit. So far, we’ve been operating under a dashboard-oriented paradigm in terms of how we use Grafana. This is not too unusual since Grafana has always been structured around the dashboard metaphor. The introduction of Explore in Grafana 6 brought an alternative workflow – one that is data-driven and, dare I say it, exploratory.

Grafana really shines when working with numerical and some forms of textual data, but what if the data includes substantial amounts of log data? Every day, countless applications disgorge not only standard numerical metrics but also copious text logs. If you’ve ever enabled debug mode in an application, then you’ve seen how a few meager kilobytes of information can quickly become a flood of gigabytes worth of repetitive, inscrutable gibberish. Diagnosing a problem by enabling the debugging code...

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