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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

Service discovery overview

In traditional monitoring environments, administrators either needed to know what they would be monitoring in advance or needed to configure push-based monitoring systems. Since the servers and devices being monitored did not change frequently, it was acceptable that adding or removing monitoring required configuration changes. However, in modern cloud-native environments, where the number of instances of an application can scale up and down automatically through systems such as Kubernetes’ HorizontalPodAutoscaler, this can introduce undesirable gaps in monitoring as targets that should be monitored are constantly added, removed, and replaced. Prometheus solves this through its service discovery system.

The Prometheus service discovery system provides over two dozen different methods of dynamically retrieving and adding scrape targets. These range from cloud providers such as AWS, Azure, and Akamai (Linode) to Docker and Kubernetes to more manual...

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