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Hands-On Infrastructure Monitoring with Prometheus

Hands-On Infrastructure Monitoring with Prometheus

By : Joel Bastos, Pedro Araújo
3.1 (7)
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Hands-On Infrastructure Monitoring with Prometheus

Hands-On Infrastructure Monitoring with Prometheus

3.1 (7)
By: Joel Bastos, Pedro Araújo

Overview of this book

Prometheus is an open source monitoring system. It provides a modern time series database, a robust query language, several metric visualization possibilities, and a reliable alerting solution for traditional and cloud-native infrastructure. This book covers the fundamental concepts of monitoring and explores Prometheus architecture, its data model, and how metric aggregation works. Multiple test environments are included to help explore different configuration scenarios, such as the use of various exporters and integrations. You’ll delve into PromQL, supported by several examples, and then apply that knowledge to alerting and recording rules, as well as how to test them. After that, alert routing with Alertmanager and creating visualizations with Grafana is thoroughly covered. In addition, this book covers several service discovery mechanisms and even provides an example of how to create your own. Finally, you’ll learn about Prometheus federation, cross-sharding aggregation, and also long-term storage with the help of Thanos. By the end of this book, you’ll be able to implement and scale Prometheus as a full monitoring system on-premises, in cloud environments, in standalone instances, or using container orchestration with Kubernetes.
Table of Contents (21 chapters)
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1
Section 1: Introduction
5
Section 2: Getting Started with Prometheus
11
Section 3: Dashboards and Alerts
15
Section 4: Scalability, Resilience, and Maintainability

Scaling with the help of sharding

With growth come more teams, more infrastructure, more applications. With time, running a single Prometheus server can start to become infeasible: changes in recording/alerting rules and scrape jobs become more frequent (thus requiring reloads which, depending on the configured scrape intervals, can take up to a couple of minutes), missed scrapes can start to happen as Prometheus becomes overwhelmed, or the person or team responsible for that instance may simply become a bottleneck in terms of organizational process. When this happens, we need to rethink the architecture of our solution so that is scales accordingly. Thankfully, this is something the community has tackled time and time again, and so there are some recommendations on how to approach this problem. These recommendations revolve around sharding.

In this context, sharding means splitting...

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