Oracle Coherence is an in-memory data grid (IMDG) solution that allows organizations to scale their applications by distributing data and computation across multiple nodes in a cluster. It is designed for high-performance, low-latency applications that require quick access to data stored in-memory.

1. Introduction to Oracle Coherence

• What is Oracle Coherence?
  • Overview of in-memory data grid (IMDG) and distributed caching.
  • Use cases in real-time, high-performance systems.
  • Benefits of using Coherence (scalability, low-latency, high availability).
• Coherence Architecture
  • Clusters, nodes, and partitioned data.
  • Distributed caches and the role of cache servers.
  • Introduction to Coherence cluster design.
• Coherence Data Models
  • Replicated caches vs. partitioned caches.
  • Cache topology (partitioning, sharding, and replication).

2. Coherence Basic Concepts

• Cache Basics
  • Definition and purpose of a cache.
  • How data is distributed and cached across nodes.
  • Cache eviction strategies (LRU, Least Frequently Used, etc.).
• Cache Types
  • Partitioned Cache: Benefits and use cases.
  • Replicated Cache: Benefits and use cases.
• Working with Coherence
  • Creating and configuring a simple Coherence cache.
  • Using Coherence with standard Java collections and POJOs (Plain Old Java Objects).
• Inserting and Retrieving Data
  • Adding, updating, and removing entries from the cache.
  • Basic cache operations: put(), get(), remove().

3. Data Structures & Advanced Caching

• Coherence Data Structures
  • EntryProcessor, CacheMap, CacheList, CacheSet.
  • Distributed data structures: Maps, Sets, Lists.
• Coherence Query Language (CQL)
  • Introduction to querying distributed caches.
  • Filtering and retrieving data from Coherence using CQL.
• Eviction Policies and Expiration
  • Time-based expiration vs. space-based eviction.
  • Managing cache lifecycle with eviction strategies.

4. Coherence for Distributed Computing

• MapReduce and Distributed Processing
  • Understanding distributed computation with Coherence.
  • Using Coherence to implement MapReduce tasks.
  • Parallel execution with Coherence.
• Events and Listeners
  • Event-driven programming with Coherence.
  • Implementing listeners for cache events (insert, update, remove).
  • Subscription and processing of events.

5. Coherence Advanced Features

• Coherence*Extend
  • Extending a Coherence grid to remote clients (Coherence*Extend).
  • Integration of Coherence with WebLogic Server, JMS, etc.
• Coherence and JCache (JSR-107)
  • Introduction to JCache API.
  • Integration with Coherence for unified caching solutions.
• Distributed Transactions
  • Implementing distributed transactions with Coherence.
  • Consistency models and CAP theorem (availability, consistency, partition tolerance).

6. Performance Optimization and Scalability

• Performance Tuning
  • Optimizing cache access and data retrieval.
  • Adjusting partitioning strategies for better performance.
  • Garbage collection and heap management in Coherence.
• High Availability and Fault Tolerance
  • Configuring replication and backup strategies.
  • Ensuring data availability during node failure.
  • Failover mechanisms and disaster recovery with Coherence.
• Scaling Coherence
  • Horizontal scaling with Coherence clusters.
  • Dynamic scaling with automatic partition redistribution.
  • Handling network latencies and balancing across nodes.

7. Coherence Security

• Security Basics
  • Authentication and authorization with Coherence.
  • Securing communications in the cluster.
  • Implementing security policies at the cache and cluster level.

8. Coherence Integration with Other Systems

• Integration with Java EE / Spring Framework
  • Using Coherence with Java EE applications.
  • Spring Cache integration with Oracle Coherence.
• Coherence and Oracle Database
  • Using Coherence as a caching layer with Oracle Database.
  • Configuring Coherence for database integration.
• Coherence on Cloud
  • Coherence integration with Oracle Cloud Infrastructure (OCI).
  • Deploying Coherence on Kubernetes or Docker for scalable applications.

9. Coherence Administration and Monitoring

• Coherence Management
  • Using Coherence’s administrative tools for cluster management.
  • Coherence web console for real-time monitoring.
  • Configuring the Coherence logs for diagnostics.
• Monitoring and Troubleshooting
  • Monitoring cache usage, memory consumption, and system health.
  • Using tools like JMX for performance diagnostics.
• Upgrading and Maintenance
  • Strategies for updating Coherence without downtime.
  • Managing distributed system upgrades.

10. Real-World Coherence Use Cases

• Coherence in E-Commerce and Financial Services
  • Real-time analytics and fraud detection.
  • Session management for high-traffic applications.
• Coherence in IoT and Real-Time Systems
  • Streamlining real-time data processing for IoT devices.
  • Real-time dashboard updates using Coherence.