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Practical Debugging at Scale

About Practical Debugging at Scale

Overhaul your debugging techniques and master the theory and tools needed to debug and troubleshoot cloud applications in production environments. This book teaches debugging skills that universities often avoid, but that typically consume as much as 60% of our time as developers. The book covers the use of debugger features such as tracepoints, object marking, watch renderers, and more. Author Shai Almog presents a scientific approach to debugging that is grounded in theory while being practical enough to help you to chase stubborn bugs through the maze of a Kubernetes deployment. Practical Debugging at Scale assumes a polyglot environment as is common for most enterprises, but focuses on JVM environments. Most of the tooling and techniques described are applicable to Python, Node, and other platforms, as well as to Java and other JVM languages. The book specifically covers debugging in production, an often-neglected discipline but an all too painful reality. Yoüll learn modern techniques around observability, monitoring, logging, and full stack debugging that you can put to immediate use in troubleshooting common ailments in production environments. You Will Learn:The scientific method underlying the process of debugging Debugger capabilities such as tracepoints and marker objects The correct use of less understood features such as exception breakpoints Techniques for tracing issues in production Kubernetes environments Observability and monitoring to resolve production problems Industry best practices for common tooling such as logging Profiling to understand performance and memory problems Who This Book Is For Developers in Java and JVM-related languages who want to improve their debugging skills and production reliability;and developers of cloud applications who are facing the pain of production bugs that are hard to replicate and fix

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  • Language:
  • English
  • ISBN:
  • 9781484290415
  • Binding:
  • Paperback
  • Pages:
  • 292
  • Published:
  • January 2, 2023
  • Edition:
  • 23001
  • Dimensions:
  • 178x16x254 mm.
  • Weight:
  • 554 g.
  In stock
Delivery: 3-5 business days
Expected delivery: November 30, 2024

Description of Practical Debugging at Scale

Overhaul your debugging techniques and master the theory and tools needed to debug and troubleshoot cloud applications in production environments. This book teaches debugging skills that universities often avoid, but that typically consume as much as 60% of our time as developers. The book covers the use of debugger features such as tracepoints, object marking, watch renderers, and more. Author Shai Almog presents a scientific approach to debugging that is grounded in theory while being practical enough to help you to chase stubborn bugs through the maze of a Kubernetes deployment.
Practical Debugging at Scale assumes a polyglot environment as is common for most enterprises, but focuses on JVM environments. Most of the tooling and techniques described are applicable to Python, Node, and other platforms, as well as to Java and other JVM languages. The book specifically covers debugging in production, an often-neglected discipline but an all too painful reality. Yoüll learn modern techniques around observability, monitoring, logging, and full stack debugging that you can put to immediate use in troubleshooting common ailments in production environments.

You Will Learn:The scientific method underlying the process of debugging
Debugger capabilities such as tracepoints and marker objects
The correct use of less understood features such as exception breakpoints
Techniques for tracing issues in production Kubernetes environments
Observability and monitoring to resolve production problems
Industry best practices for common tooling such as logging
Profiling to understand performance and memory problems

Who This Book Is For
Developers in Java and JVM-related languages who want to improve their debugging skills and production reliability;and developers of cloud applications who are facing the pain of production bugs that are hard to replicate and fix

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