Course Outline

? Day 1: Core Java and Fundamentals for Scalability

Session 1: Java Basics and Performance-Oriented Coding

• Java platform overview and JVM basics
• Efficient data types and collections usage
• Memory management and garbage collection overview

Session 2: Concurrency and Multithreading

• Threads, Runnable, and ExecutorService
• Synchronization, locks, and thread safety
• Java concurrency utilities: CountDownLatch, Semaphore, Concurrent collections

Session 3: Writing Scalable Code

• Immutability and stateless design
• Avoiding bottlenecks and shared mutable state
• Profiling basics and performance measurement

Lab Activities:

• Write multithreaded code using ExecutorService
• Implement thread-safe data structures
• Profile simple programs to identify performance issues

? Day 2: Advanced Java and Design Patterns for Scalability

Session 1: Design Patterns for Scalable Systems

• Creational patterns: Singleton, Factory
• Structural patterns: Proxy, Decorator
• Behavioral patterns: Observer, Strategy

Session 2: Reactive and Asynchronous Programming

• Introduction to reactive programming concepts
• Using CompletableFuture for async operations
• Overview of reactive libraries (Reactor, RxJava)

Session 3: Resource Management and IO

• Efficient file and network IO with NIO
• Connection pooling and database access optimization
• Caching strategies and best practices

Lab Activities:

• Apply design patterns to improve code modularity
• Implement asynchronous workflows with CompletableFuture
• Optimize file and network IO code

? Day 3: Scaling Java Applications and Deployment

Session 1: Building Scalable Architectures

• Microservices vs Monoliths: Java perspectives
• Load balancing and clustering fundamentals
• Session management and stateless services

Session 2: JVM Tuning and Monitoring

• JVM options for performance tuning
• Garbage collector tuning and logging
• Using monitoring tools (VisualVM, JConsole)

Session 3: Deployment and Cloud-Native Java

• Packaging with Maven/Gradle
• Containerizing Java apps with Docker
• Deploying Java apps on Kubernetes and cloud platforms

Lab Activities:

• Tune JVM settings for sample applications
• Containerize and deploy a Java microservice
• Set up monitoring dashboards and alerts