- You should consider sharding when you're sure a single instance isn't enough to handle the load, and you can't run it with more resources.
- Vertical sharding is used to split scrape workload according to responsibility (for example, by function or team), where each Prometheus shard scrapes different jobs. Horizontal sharding splits loads from a single scrape job into multiple Prometheus instances.
- To reduce the ingestion load on a Prometheus instance, you should consider dropping unnecessary metrics through the use of metric_relabel_configs rules, or by increasing the scrape interval so that fewer samples are ingested in total.
- Instance-level Prometheus servers should federate job-level aggregate metrics. Job-level Prometheus servers should federate datacenter-level aggregate metrics.
- You might need to use metrics only...
Hands-On Infrastructure Monitoring with Prometheus
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Hands-On Infrastructure Monitoring with Prometheus
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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.
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Hands-On Infrastructure Monitoring with Prometheus
Table of Contents (21 chapters)
Preface
Monitoring Fundamentals
An Overview of the Prometheus Ecosystem
Setting Up a Test Environment
Section 2: Getting Started with Prometheus
Prometheus Metrics Fundamentals
Running a Prometheus Server
Exporters and Integrations
Prometheus Query Language - PromQL
Troubleshooting and Validation
Section 3: Dashboards and Alerts
Defining Alerting and Recording Rules
Discovering and Creating Grafana Dashboards
Understanding and Extending Alertmanager
Section 4: Scalability, Resilience, and Maintainability
Choosing the Right Service Discovery
Scaling and Federating Prometheus
Integrating Long-Term Storage with Prometheus
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