table of content

Part 1 Revisiting the foundation for code investigation

1 Starting to know your apps

1.1 How to more easily understand your app

1.2 Typical scenarios for using investigation techniques

1.2.1 Demystifying the unexpected output

1.2.2 Getting familiar with your external libraries

1.2.3 Clarifying slowness

1.2.4 Understanding app crashes

1.3 AI as a game changer in troubleshooting apps

1.4 What you will learn in this book

2 Understanding your app’s logic through debugging techniques

2.1 When analyzing code is not enough

2.2 Investigating code with a debugger

2.2.1 What is the execution stack trace, and how do I use it?

2.2.2 Navigating code with the debugger

2.3 When using the debugger might not be enough

3 Finding problem root causes using advanced debugging techniques

3.1 Minimizing investigation time with conditional breakpoints

3.2 Using breakpoints that don’t pause the execution

3.3 Dynamically altering the investigation scenario

3.4 Rewinding the investigation case

4 Making the most of logs: Auditing an app’s behavior

4.1 Investigating issues with logs

4.1.1 Using logs to identify exceptions

4.1.2 Using exception stack traces to identify what calls a method

4.1.3 Measuring time spent to execute a given instruction

4.1.4 Investigating problems in multithreaded architectures

4.2 Implementing logging

4.2.1 Persisting logs

4.2.2 Defining logging levels and using logging frameworks

4.2.3 Problems caused by logging and how to avoid them

Part 2 Deep diagnosing an app’s execution

5 Identifying resource consumption problems using profiling techniques

5.1 Where would a profiler be useful?

5.1.1 Identifying abnormal usage of resources

5.1.2 Finding out what code executes

5.1.3 Identifying slowness in an app’s execution

5.2 Using a profiler

5.2.1 Installing and configuring VisualVM

5.2.2 Observing the CPU and memory usage

5.2.3 Identifying memory leaks

5.3 Using AI assistance

6 Finding hidden problems using profiling techniques

6.1 Sampling to observe executing code

6.2 Profiling to learn how many times a method is executed

6.3 Using a profiler to identify SQL queries an app executes

6.3.1 Using a profiler to retrieve SQL queries not generated by a framework

6.3.2 Using the profiler to get the SQL queries generated by a framework

6.3.3 Using the profiler to get programmatically generated SQL queries

7 Investigating locks in multithreaded architectures

7.1 Monitoring threads for locks

7.2 Analyzing thread locks

7.3 Analyzing waiting threads

8 Investigating deadlocks with thread dumps

8.1 Getting a thread dump

8.1.1 Getting a thread dump using a profiler

8.1.2 Generating a thread dump from the command line

8.2 Reading thread dumps

8.2.1 Reading plain-text thread dumps

8.2.2 Using tools to better grasp thread dumps

Part 3 Diagnosing memory-related problems

9 Profiling memory-related problems

9.1 Sampling to identify memory allocation problems

9.2 Profiling to find the culprit

10 Investigating memory problems with heap dumps

10.1 Obtaining a heap dump

10.1.1 Configuring an app to generate a heap dump when it encounters a memory problem

10.1.2 Obtaining a heap dump using a profiler

10.1.3 Obtaining a heap dump with the command line

10.2 Reading a heap dump

10.3 Using the OQL console to query a heap dump

11 Analyzing potential JVM problems with GC logs

11.1 Enabling GC logs

11.2 Storing GC logs in files

11.3 Particular configurations for storing GC logs

11.4 Analyzing GC logs

11.4.1 Troubleshooting performance lags with GC pause times

11.4.2 Identifying memory leaks with heap usage logs

11.4.3 Identifying insufficient memory with full GC events

11.4.4 Tuning parallelism in GC

Part 4 Finding problems in large systems

12 Uncovering system-level failures and service communication problems

12.1 Troubleshooting communication patterns: RPC and messaging

12.1.1 Working with trace IDs and spans

12.1.2 OpenTelemetry, Jaeger, Zipkin, and other utilities

12.2 Serialization mismatches and versioning problems

12.3 Understanding systemic failure modes

12.3.1 Cascading failures

12.3.2 Retry storms

12.3.3 Timeout mismatches

13 Measuring data consistency and transactions

13.1 Troubleshooting inconsistencies across services

13.1.1 Inspecting time-based anomalies in event flows

13.1.2 Applying domain invariants to identify invalid states

13.2 Tracking and correlating multistep transactions

13.2.1 Reviewing audit logs to reconstruct transaction steps

13.2.2 Replaying events or examining event logs for missing messages

13.3 Measuring and monitoring consistency guarantees

13.3.1 Verifying data integrity using checksums or hashes

13.4 Running reconciliation jobs to compare expected vs. actual state

Appendices

Appendix A: Tools you’ll need

Appendix B: Opening a project

Appendix C: Recommended further reading

Appendix D: Understanding Java threads

D.1 What is a thread?

D.2 A thread’s life cycle

D.3 Synchronizing threads

D.3.1 Synchronized blocks

D.3.2 Using wait(), notify(), and notifyAll()

D.3.3 Joining threads

D.3.4 Blocking threads for a defined time

D.3.5 Synchronizing threads with blocking objects

D.4 Common problems in multithreaded architectures

D.4.1 Race conditions

D.4.2 Deadlocks

D.4.3 Livelocks

D.4.4 Starvation

D.5 Further reading

Appendix E: Memory management in Java apps

E.1 How the JVM organizes an app’s memory

E.2 The stack used by threads to store local data

E.3 The heap the app uses to store object instances

E.4 The metaspace memory location for storing data types

Appendix F: references

Overview

Appendix C. Recommended further reading

This appendix offers a curated set of books to extend the troubleshooting mindset beyond tools and techniques, emphasizing deeper code comprehension, architectural judgment, and habits that make future investigations easier. The selections aim to sharpen how developers read and reason about code, make informed tradeoffs, and evolve systems toward clarity and maintainability.

For architecture, the recommendations concentrate on microservices. Monolith to Microservices guides when and how to split systems, contrasting monoliths with microservices and highlighting context-driven choices. Building Microservices expands on designing fine-grained services with pragmatic pros and cons, while Microservices Patterns catalogs essential techniques and patterns used in large-scale, service-oriented systems, all illustrated with clear examples.

On code quality and developer practice, The Programmer’s Brain explores how developers process and understand code, grounding effective investigation. Five Lines of Code promotes clean coding and the “Boy Scout rule,” encouraging refactoring after debugging to make code easier to understand. Good Code, Bad Code distills principles for writing high-quality, comprehensible software, and Software Mistakes and Tradeoffs builds skill in making informed compromises. Rounding out the list, Refactoring: Improving the Design of Existing Code remains a foundational guide to systematically improving design and maintainability.

FAQ

What is the purpose of Appendix C: Recommended further reading?

It lists books related to the book’s subject that you may find useful and interesting.

How can “The Programmer’s Brain” help with troubleshooting and code investigation?

Felienne Hermans’s book (Manning, 2021) explores how a developer’s brain works when investigating code. Because reading code precedes applying investigation techniques, understanding these cognitive aspects helps you investigate code more effectively.

What does “Monolith to Microservices” focus on?

Sam Newman’s book (O’Reilly Media, 2019) examines the differences between monolithic and microservices approaches and explains where and how to use each. It’s recommended for studying microservices as an architectural style.

How does “Building Microservices: Designing Fine-Grained Systems, Second Edition” complement the microservices topic?

Sam Newman’s 2021 edition (O’Reilly Media) focuses on designing systems composed of fine‑grained services and analyzes the pros and cons of the techniques with clear, detailed examples.

Why is “Microservices Patterns” considered a must-read?

Chris Richardson’s book (Manning, 2018) clearly details essential techniques used in large‑scale microservices and service‑oriented systems, making it a must‑read for anyone working with microservices architectures.

What does “Five Lines of Code” teach, and what is the “Boy Scout rule” mentioned?

Christian Clausen’s book (Manning, 2021) teaches clean coding practices. After understanding how unclean code works, you should refactor it to make it easier to understand—an approach developers call the “Boy Scout rule.” Debugging is often followed by such refactoring.

How will “Good Code, Bad Code” improve my coding?

Tom Long’s book (Manning, 2021) teaches high‑quality code‑writing principles and is recommended to upskill in refactoring and writing easier‑to‑understand applications.

What topics are covered in “Software Mistakes and Tradeoffs”?

Tomasz Lelek and Jon Skeet (Manning, 2022) discuss how to make difficult decisions, handle compromises, and optimize decisions in software development, with excellent examples.

Why should I read “Refactoring: Improving the Design of Existing Code”?

Martin Fowler’s book with Kent Beck (Addison‑Wesley Professional, 2018) is a must‑read for developers who want to improve their skills in designing and building clean, maintainable applications.

Who would benefit most from these recommended books?

Developers who investigate code, work with microservices, or want to improve code quality, refactoring skills, and decision‑making in software design will find these titles especially valuable.

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$54.99 $27.49

you save $27.50 (50%)

include audio $24.99 $12.49

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renews monthly, pause or cancel renewal anytime

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