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.

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.

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.

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.

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.

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.