OpenTelemetry Cookbook: Proven approaches for real-time monitoring and observability on cloud, AI, and modern infrastructures (Paperback) (ISBN-13: 9789349174399)

A hands-on, recipe-driven book that puts OpenTelemetry into immediate use. This cookbook is for IT folks like developers, Linux admins, cloud engineers, backend pros, networking experts, and security practitioners. It's for anyone who wants a proven, hands-on way to keep an eye on, trace, and understand modern systems.

This book gives you step-by-step easy solutions to everyday observability challenges, so you can integrate, configure, and operate OpenTelemetry in dynamic environments. Each chapter focuses on solving problems that are directly relevant to production teams. These problems include installing and bootstrapping the Collector on Linux, wiring telemetry pipelines for traces, metrics, logs, and baggage, and integrating with the platforms that organizations trust for analysis and alerting.

• Get the OpenTelemetry Collector up and running on Linux, Docker, and Kubernetes.
• Make and adjust pipelines to collect, process, and send out different telemetry signals.
• Use it to develop apps across Python, Go, Java, and Node.js.
• Boost signals with semantic info and resource detectors for more context.
• Integrate with AWS CloudWatch, X-Ray, Elastic, Prometheus, Splunk, Datadog, New Relic, Grafana Tempo, Loki, and Jaeger.
• Make a visual plan for telemetry and set up real-time alerts.

There's no need to get lost in theoretical jargon because OpenTelemetry Cookbook gets right to the meat and potatoes of implementation. Every recipe gives you a clear problem statement, a step-by-step solution, and practical validation. If you're just starting out with observability or want to level up your skills, this book's got you covered with clear steps to understand distributed, cloud-native, and hybrid systems.

1. Bootstrapping OpenTelemetry
2. Building Telemetry Pipelines
3. Instrumenting Applications with OpenTelemetry SDKs
4. Code-Based Instrumentation and Auto-Instrumentation
5. Telemetry with Attributes and Resource Detectors
6. Advanced Signal Processing and Filtering
7. Observability in Kubernetes
8. Integrations with Cloud and Observability Platforms
9. Visualizing and Alerting Telemetry Data