Apache Ignite 

Module 1: Introduction to In-Memory Computing

• What is in-memory computing and why it matters

• Traditional database limitations and performance bottlenecks

• In-memory computing use cases and benefits

• Apache Ignite overview and ecosystem position

• Ignite vs. other solutions (Redis, Hazelcast, etc.)

Lab: Environment setup and first Ignite cluster startup

Module 2: Ignite Architecture Deep Dive

• Ignite cluster topology and node types

• Data distribution and partitioning concepts

• Memory architecture (on-heap, off-heap, persistence)

• Discovery mechanisms (multicast, static IP, cloud discovery)

• Baseline topology and cluster activation

Lab: Multi-node cluster setup with different discovery mechanisms

Module 3: Basic Cache Operations

• Cache API fundamentals

• CRUD operations (put, get, remove, replace)

• Cache modes: PARTITIONED, REPLICATED, LOCAL

• Synchronous vs. asynchronous operations

• Batch operations and performance considerations

Lab: Implementing basic cache operations with different cache modes

Module 4: Configuration and Deployment

• XML vs. programmatic configuration

• Spring Boot integration basics

• Cache configuration parameters

• Node and cluster configuration best practices

• Basic monitoring and logging setup

Lab: Configure caches with different settings and Spring Boot integration

Module 5: Data Modeling and Persistence

• Data modeling best practices for Ignite

• Affinity keys and colocation strategies

• Native persistence layer overview

• Write-through, write-behind, and read-through patterns

• Integration with external databases

Lab: Implement data models with proper affinity keys and persistence configuration

Module 6: SQL and Indexing

• SQL support in Ignite (DDL, DML, DQL)

• Creating and managing indexes

• Query performance optimization

• JDBC driver usage

• Distributed joins and their implications

Lab: Create tables, indexes, and perform complex queries

Module 7: Transactions and ACID Properties

• Transaction concepts in distributed systems

• Ignite transaction models (PESSIMISTIC, OPTIMISTIC)

• Isolation levels and consistency guarantees

• Deadlock detection and resolution

• Transaction best practices

Lab: Implement transactional operations with different isolation levels

Module 8: Advanced Caching Patterns

• Cache-aside, write-through, write-behind patterns

• Near caches and client-side caching

• Expiry policies and eviction strategies

• Cache entry processors for atomic operations

• Event handling and continuous queries

Lab: Implement different caching patterns and event listeners

Module 9: Compute Grid Fundamentals

• Distributed computing concepts

• Compute closures and jobs

• Task execution and load balancing

• Affinity-aware computing for performance

• MapReduce operations

Lab: Implement distributed computing tasks with affinity awareness

Module 10: Integration and Connectivity

• REST API usage and web console

• Integration with Spring Framework

• Kafka connector and streaming data

• Hibernate L2 cache integration

• Client vs. server node configurations

Lab: Set up REST API access and integrate with external systems

Module 11: Performance Tuning and Monitoring

• JVM tuning for Ignite workloads

• Memory management and garbage collection

• Performance metrics and monitoring tools

• Benchmarking and load testing strategies

• Common performance anti-patterns

Lab: Performance analysis and tuning exercise with real workloads

Module 12: Production Deployment and Best Practices

• Cluster sizing and capacity planning

• Security configuration (authentication, SSL/TLS)

• Backup and disaster recovery strategies

• Rolling updates and maintenance procedures

• Troubleshooting common issues

• Container deployment (Docker, Kubernetes basics)

Lab: Deploy a production-ready cluster with security and monitoring

Course Materials and Prerequisites

Prerequisites:

• Java programming experience 

• Basic understanding of databases and SQL

• Familiarity with distributed systems concepts (helpful but not required)

• Development environment with Java 8+ and Maven/Gradle