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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

Using VictoriaMetrics

VictoriaMetrics is one of the most popular and established options for the remote storage of Prometheus metrics. In fact, some people and projects use VictoriaMetrics as a drop-in replacement for Prometheus since it supports directly scraping targets via its vmagent component and is mostly compatible with the Prometheus configuration file (it lacks support for the remote_write, remote_read, rule_files, and alerting sections).

One of the primary reasons that people choose VictoriaMetrics as their remote storage destination is its resource efficiency. In a head-to-head benchmark against Prometheus, VictoriaMetrics boasts seven times the reduction in disk space (~0.3 bytes per sample vs. ~2.1 bytes) and five times the reduction in memory (~4.3GB of RAM vs. ~23GB) for the same amount of time series and samples (2.8 million active time series and 280,000 samples/sec) in their benchmark, published at https://valyala.medium.com/prometheus-vs-victoriametrics-benchmark...

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