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English
Total Size:
6.1 MB
Info Hash:
B1808953D8C6A679F17244F9DA673A61A8538C4B
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June 10, 2025, 2:47 a.m.
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(Last updated: Oct. 22, 2025, 8 p.m.)
| File | Size |
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| Badawy M. Hands-On Monitoring and Alerting with Prometheus...Best Practices 2025.pdf | 6.1 MB |
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SOURCE: Badawy M Hands On Monitoring and Alerting with Prometheus Best Practices 2025
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Textbook in PDF format Build reliable, scalable monitoring and alerting systems with Prometheus, PromQL, and real-world demos. Book Description Prometheus has emerged as the leading open-source monitoring solution for building resilient, observable systems, and Hands-On Monitoring and Alerting with Prometheus shows you exactly how to utilize its full potential. The book begins with the fundamentals of modern monitoring and the core architecture of Prometheus. Through hands-on labs, you’ll master Prometheus service discovery, labeling, and relabeling to organize metrics at scale. Whether you are collecting metrics from Linux machines, Windows servers, Docker containers, or databases, this book equips you with practical skills through real-world examples and tutorials. You will learn how to install and configure Prometheus, use its service discovery features, label and relabel metrics, and build powerful queries using PromQL - all leading to actionable insights through alerts and dashboards. You’ll configure alerts and Alertmanager integrations, apply advanced techniques, and put everything together with real-world applications. Each chapter builds practical skills so you can confidently design and operate a robust observability stack. Whether you're a DevOps engineer, SRE, or system architect, this book is your gateway to production-grade monitoring. Don’t just collect metrics—turn them into action with Prometheus today. This Book Covers Chapter 1. Introduction and Key Concepts in Monitoring: This chapter introduces the landscape of modern monitoring, explaining the difference between static and dynamic environments, where Prometheus fits into the DevOps lifecycle, and the stages of metrics monitoring. It also highlights anti-patterns, design patterns, and the relationship between logs and metrics, concluding with a guide on setting up your Prometheus workspace. Chapter 2. Prometheus Server Architecture and Features: This chapter explores the core architecture and key components of Prometheus, providing a solid foundation for understanding how it collects, stores, and processes metrics. We will learn about the Prometheus server, exporters, instrumentation, the Push Gateway, Service Discovery, and how PromQL enables powerful querying. We will also introduce Alertmanager for basic alert handling. A special focus is given to the Time Series Database (TSDB) - its features, scalability, and handling of high cardinality and dynamic sampling, along with the challenges they may bring. Chapter 3. Different Types of Prometheus Metrics: In this chapter, we will understand the fundamental metric types: Counters, Gauges, Summaries, and Histograms. This chapter explains when and how to use each type, along with best practices for accurate metric representation. Chapter 4. Metrics Exporters for Infrastructure Monitoring: In this chapter, we will learn how Prometheus collects data using exporters. This chapter focuses on key exporters such as Node Exporter, BlackBox Exporter, WMI Exporter for Windows, MySQL Exporter, and cAdvisor for container metrics. Chapter 5. Prometheus Service Discovery Feature: In this chapter, we will explore how Prometheus uses Service Discovery to dynamically find targets in environments such as Kubernetes. The chapter includes a demo setup with prerequisites and implementation of service discovery in action. Chapter 6. Metrics Labeling and Relabeling: Labels are central to how Prometheus stores and queries data. This chapter discusses the importance of labels, how source and target labels are used, and introduces the relabeling mechanism for refining target configurations. Chapter 7. Prometheus Query Language PromQL: In this chapter, we will master PromQL with real examples. Topics include aggregation operators, label matchers, grouping (by/without), binary operations, and core functions such as rate, irate, avg_over_time, and count_values. We will also learn which functions work with range vectors. Chapter 8. Alerts and Alert Receivers: This chapter covers the complete alerting lifecycle in Prometheus. We will earn to define alerts, label and annotate them, and configure Alertmanager for routing, grouping, throttling, and silencing. We will also explore how to integrate with alert receivers like email, Slack, or PagerDuty. Chapter 9. Advanced Prometheus Techniques: Take your skills to the next level with advanced topics such as securing endpoints with TLS, optimizing storage, writing complex PromQL queries, and integrating with tools like Grafana, Jaeger, and OpenTelemetry for full observability. Additionally, we will learn careful configuration for capacity planning and performance tuning, and also Prometheus automation, which is essential for scaling. Chapter 10. Prometheus and Real-world Applications: This chapter highlights how Prometheus is applied across real-world architectures, including cloud infrastructure, network monitoring, and DevOps environments. You'll explore how Prometheus supports different teams, the types of metrics it provides, and practical use cases in each domain. We also take a brief look at how companies like SoundCloud and Uber successfully use Prometheus in production. Chapter 11. Conclusion: Future Steps: Wrap up the journey with a recap of key takeaways, tips for the PCA certification, and guidance on next steps for expanding your observability knowledge and Prometheus practice
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