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Mastering Prometheus

You're reading from   Mastering Prometheus Gain expert tips to monitoring your infrastructure, applications, and services

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Product type Paperback
Published in Apr 2024
Publisher Packt
ISBN-13 9781805125662
Length 310 pages
Edition 1st Edition
Concepts
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Author (1):
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William Hegedus William Hegedus
Author Profile Icon William Hegedus
William Hegedus
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Table of Contents (21) Chapters Close

Preface 1. Part 1: Fundamentals of Prometheus FREE CHAPTER
2. Chapter 1: Observability, Monitoring, and Prometheus 3. Chapter 2: Deploying Prometheus 4. Chapter 3: The Prometheus Data Model and PromQL 5. Chapter 4: Using Service Discovery 6. Chapter 5: Effective Alerting with Prometheus 7. Part 2: Scaling Prometheus
8. Chapter 6: Advancing Prometheus: Sharding, Federation, and High Availability 9. Chapter 7: Optimizing and Debugging Prometheus 10. Chapter 8: Enabling Systems Monitoring with the Node Exporter 11. Part 3: Extending Prometheus
12. Chapter 9: Utilizing Remote Storage Systems with Prometheus 13. Chapter 10: Extending Prometheus Globally with Thanos 14. Chapter 11: Jsonnet and Monitoring Mixins 15. Chapter 12: Utilizing Continuous Integration (CI) Pipelines with Prometheus 16. Chapter 13: Defining and Alerting on SLOs 17. Chapter 14: Integrating Prometheus with OpenTelemetry 18. Chapter 15: Beyond Prometheus 19. Index 20. Other Books You May Enjoy

Making robust alerts

The ability to make more robust alerts is one of the distinguishing factors of Prometheus vs. traditional, check-based monitoring solutions such as Nagios. It allows you to consider multiple factors when creating alerts. For example, rather than just alerting on high memory usage on a server, you can easily create an alert that will only fire if you have high memory usage and a high rate of major page faults since that is generally a better indicator of a system experiencing memory pressure. The idea is to craft alerts in such a way that you reduce the number of false positives as much as possible so that alerts only fire when real, visible impact is occurring. This is part of a larger discussion on the philosophy of alerting on symptoms vs. causes, which is covered comprehensively in Rob Ewaschuk’s excellent document entitled My Philosophy on Alerting (linked at the end of this chapter).

Use logical/set binary operators

In order to make robust alerts...

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