Book Image

Hands-On Infrastructure Monitoring with Prometheus

By : Joel Bastos, Pedro Araújo
Book Image

Hands-On Infrastructure Monitoring with Prometheus

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)
Free Chapter
1
Section 1: Introduction
5
Section 2: Getting Started with Prometheus
11
Section 3: Dashboards and Alerts
15
Section 4: Scalability, Resilience, and Maintainability

Having a global view using federation

When you have multiple Prometheus servers, it can become quite cumbersome to know which one to query for a certain metric. Another problem that quickly comes up is how to aggregate data from multiple instances, possibly in multiple datacenters. Here's where federation comes into the picture. Federation allows you to have a Prometheus instance scraping selected time series from other instances, effectively serving as a higher-level aggregating instance. This can happen in a hierarchical fashion, with each layer aggregating metrics from lower-level instances into larger-encompassing time series, or in a cross-service pattern, where a few metrics are selected from instances in the same level for federation so that some recording and alerting rules become possible. For example, you could collect data for service throughput or latency in each...