Overview

Google, IBM & Meta Certificates – 40% Off

One Coursera Plus subscription covers most Professional Certificates on Coursera.

Master the application of Java concurrency in microservices, serverless computing, and cutting-edge cloud-native architectures. Explore auto-scaling, GPU acceleration, and the future of Java in cloud and edge environments. This course covers the integration of Java concurrency with microservices, serverless platforms, and cloud auto-scaling strategies. Learners will investigate advanced topics such as GPU acceleration, monitoring, and Java's evolving role in edge computing and AI-driven cloud services. The course concludes with forward-looking insights and practical guidance for building high-concurrency, cloud-native Java applications. Combining in-depth conceptual coverage with real-world case studies and code examples, this course guides learners through the latest trends and best practices in cloud-native Java development. Emphasis is placed on practical application and strategic decision-making for scalable, future-ready solutions. This course is part three of a three-course Specialization designed to build a complete and cohesive understanding of the subject. While it offers valuable skills on its own, you'll gain the most benefit by progressing through all three courses as a structured learning journey. This course is based on Java Concurrency and Parallelism, by Jay Wang.

Syllabus

Microservices in the Cloud and Java's Concurrency
- This module explores the implementation of microservices in cloud environments, focusing on concurrency, scalability, and data consistency. Learners will gain insights into real-world applications, such as Netflix and e-commerce systems, and learn best practices for deploying and managing microservices effectively.
Serverless Computing and Java's Concurrent Capabilities
- This module explores the integration of Java's concurrency features with serverless computing models, covering the benefits and limitations of serverless architectures, key tools like AWS SAM and Oracle Functions, and practical application deployment strategies.
Synchronizing Java's Concurrency with Cloud Auto-Scaling Dynamics
- This module explores how to synchronize Java concurrency models with cloud auto-scaling techniques, covering strategies for optimizing performance, integrating monitoring tools, and implementing scalable solutions in cloud environments.
Advanced Java Concurrency Practices in Cloud Computing
- This module covers advanced techniques for implementing Java concurrency in cloud environments, including GPU acceleration with CUDA, OpenCL, and TornadoVM, as well as strategies for monitoring and optimizing cloud-native applications. Learners will gain practical insights into building resilient, high-performance systems using Java in cloud settings.
The Horizon Ahead
- This module explores the future of cloud computing by diving into serverless Java frameworks, edge computing, and AI/ML integration. Learners will gain hands-on experience with building scalable cloud solutions and implementing advanced technologies like Quarkus, AWS Lambda, and Project Loom. The content emphasizes practical applications and real-world use cases.
APPENDIX A
- This module provides an overview of setting up a cloud-native environment for Java applications, covering key steps such as building, packaging, and deploying applications on major cloud platforms like AWS, Azure, and GCP. Learners will also explore essential resources to support their cloud development journey.
APPENDIX B
- This module introduces learners to essential resources for building cloud-native Java applications. It highlights key books and articles that provide practical guidance on designing resilient systems using modern frameworks like Spring Boot and Spring Cloud. Learners will gain an understanding of best practices for cloud-based development.