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Mastering Prometheus

Mastering Prometheus

By : Hegedus
3.7 (6)
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Mastering Prometheus

Mastering Prometheus

3.7 (6)
By: Hegedus

Overview of this book

With an increased focus on observability and reliability, establishing a scalable and reliable monitoring environment is more important than ever. Over the last decade, Prometheus has emerged as the leading open-source, time-series based monitoring software catering to this demand. This book is your guide to scaling, operating, and extending Prometheus from small on-premises workloads to multi-cloud globally distributed workloads and everything in between. Starting with an introduction to Prometheus and its role in observability, the book provides a walkthrough of its deployment. You’ll explore Prometheus’s query language and TSDB data model, followed by dynamic service discovery for monitoring targets and refining alerting through custom templates and formatting. The book then demonstrates horizontal scaling of Prometheus via sharding and federation, while equipping you with debugging techniques and strategies to fine-tune data ingestion. Advancing through the chapters, you’ll manage Prometheus at scale through CI validations and templating with Jsonnet, and integrate Prometheus with other projects such as OpenTelemetry, Thanos, VictoriaMetrics, and Mimir. By the end of this book, you’ll have practical knowledge of Prometheus and its ecosystem, which will help you discern when, why, and how to scale it to meet your ever-growing needs.
Table of Contents (21 chapters)
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Free Chapter
1
Part 1: Fundamentals of Prometheus
7
Part 2: Scaling Prometheus
11
Part 3: Extending Prometheus

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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