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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

Defining SLOs with Prometheus data

Prometheus metrics are great for SLIs since they are generally specific enough to pick out individual aspects of a service’s performance but still generic enough to be aggregated into an overarching view of how that service is performing. Once you understand the patterns of defining SLOs with Prometheus, the most challenging part is really just identifying which of your hundreds of thousands (or millions) of metrics are best suited to being the SLIs for SLOs.

Once you have your SLI(s) picked out, the SLOs in Prometheus are typically defined in recording rules. Since SLIs will normally need to be aggregated across multiple instances or dimensions, it’s simpler to precompute their values instead of running their queries over long time ranges. I also recommend keeping the naming of your SLO recording rules consistent so that it is easy and intuitive to query for SLO metrics across services, for example, using the same resultant series...

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