فهرست مطالب

• Cover
• Copyright
• Contributors
• Table of Contents
• Preface
• Part 1: Foundations of Java Concurrency and Parallelism in Cloud Computing
• Chapter 1: Concurrency, Parallelism, and the Cloud: Navigating the Cloud-Native Landscape
• Technical requirements
• The dual pillars of concurrency versus parallelism – a kitchen analogy
• Java and the cloud – a perfect alliance for cloud-native development
• Modern challenges in cloud-native concurrency and Java’s weapons of choice
• Conquering concurrency – best practices for robust cloud-native applications
• Summary
• Exercise – exploring Java executors
• Questions
• Chapter 2: Introduction to Java’s Concurrency Foundations: Threads, Processes, and Beyond
• Technical requirements
• Java’s kitchen of concurrency – unveiling threads and processes
• The concurrency toolkit – java.util.concurrent
• Synchronization and locking mechanisms
• Employing Future and Callable for result-bearing task execution
• Safe data sharing between concurrent tasks
• Leveraging thread-safe collections to mitigate concurrency issues
• Concurrent best practices for robust applications
• Summary
• Questions
• Chapter 3: Mastering Parallelism in Java
• Technical requirements
• Unleashing the parallel powerhouse – the Fork/Join framework
• Fine-tuning the symphony of parallelism – a journey in performance optimization
• Unlocking the power of big data with a custom Spliterator
• Benefits and pitfalls of parallelism
• Summary
• Questions
• Chapter 4: Java Concurrency Utilities and Testing in the Cloud Era
• Technical requirements
• Introduction to Java concurrency tools – empowering cloud computing
• Taming the threads – conquering the cloud with the Executor framework
• Real-world examples of thread pooling and task scheduling in cloud architectures
• Utilizing Java’s concurrent collections in distributed systems and microservices architectures
• Advanced locking strategies for tackling cloud concurrency
• Advanced concurrency management for cloud workflows
• Utilizing tools for diagnosing concurrency problems
• The quest for clarity – advanced profiling techniques
• Weaving the web – integrating profiling tools into CI/CD pipelines
• Service mesh and APM – your cloud performance powerhouse
• Mastering concurrency in cloud-based Java applications – testing and debugging tips
• Summary
• Questions
• Chapter 5: Mastering Concurrency Patterns in Cloud Computing
• Technical requirements
• Core patterns for robust cloud foundations
• Java concurrency patterns for asynchronous operations and distributed communications
• Combining concurrency patterns for enhanced resilience and performance
• Blending concurrency patterns – a recipe for high-performance cloud applications
• Summary
• Questions
• Part 2: Java's Concurrency in Specialized Domains
• Chapter 6: Java and big data – a Collaborative Odyssey
• Technical requirements
• The big data landscape – the evolution and need for concurrent processing
• Hadoop – the foundation for distributed data processing
• Java and Hadoop – a perfect match
• Beyond the basics – advanced Hadoop concepts for Java developers and architects
• Hadoop and Spark equivalents in major cloud platforms
• Real-world Java and big data in action
• Summary
• Questions
• Chapter 7: Concurrency in Java for Machine Learning
• Technical requirements
• An overview of ML computational demands and Java concurrency alignment
• Java’s tools for parallel processing in ML workflows
• Achieving scalable ML deployments using Java’s concurrency APIs
• Generative AI and Java – a new frontier
• Summary
• Questions
• Chapter 8: Microservices in the Cloud and Java’s Concurrency
• Technical requirements
• Core principles of microservices – architectural benefits in cloud platforms
• Essential Java concurrency tools for microservice management
• Challenges and solutions in microservices concurrency
• Strategic best practices – deploying and scaling microservices
• Advanced concurrency patterns – enhancing microservice resilience and performance
• Summary
• Questions
• Chapter 9: Serverless Computing and Java’s Concurrent Capabilities
• Technical requirements
• Fundamentals of serverless computing in java
• Adapting Java’s concurrency model to serverless environments
• Introducing serverless frameworks and services – AWS SAM, Azure Functions Core Tools, Google Cloud Functions, and Oracle Functions
• Industry examples – Java serverless functions with a focus on concurrency
• Building with serverless frameworks – a practical approach
• Summary
• Questions
• Part 3: Mastering Concurrency in the Cloud – The Final Frontier
• Chapter 10: Synchronizing Java’s Concurrency with Cloud Auto-Scaling Dynamics
• Technical requirements
• Fundamentals of cloud auto-scaling – mechanisms and motivations
• Java’s concurrency models – alignment with scaling strategies
• Advanced topics
• Summary
• Questions
• Chapter 11: Advanced Java Concurrency Practices in Cloud Computing
• Technical requirements
• Enhancing cloud-specific redundancies and failovers in Java applications
• GPU acceleration in Java – leveraging CUDA, OpenCL, and native libraries
• Specialized monitoring for Java concurrency in the cloud
• Summary
• Questions
• Chapter 12: The Horizon Ahead
• Technical requirements
• Future trends in cloud computing and Java’s role
• Edge computing and Java
• AI and ML integration
• Emerging concurrency and parallel processing tools in Java
• Preparing for the next wave of cloud innovations
• Summarya
• Questions
• Appendix A: Setting up a Cloud-Native Java Environment
• Appendix B: Resources and Further Reading
• Index
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