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

Logs and endpoint validation

In the next sections, we go through several useful HTTP endpoints and service logs that can be fundamental to troubleshoot issues with a Prometheus instance.

Endpoints

Checking whether Prometheus is up and running is usually very simple, as it follows the conventions most cloud-native applications use for service health: one endpoint to check whether the service is healthy and another to check whether it is ready to start handling incoming requests. For those who use or have used Kubernetes in the past, these might sound familiar; in fact, Kubernetes also uses these conventions to assess whether a container needs to be restarted (for example, if the application deadlocks and stops responding to...