Kappa Architecture

Description:
The Kappa Architecture is a data processing architecture that provides a simplified approach to handling both real-time and batch data processing. Unlike the Lambda Architecture, which requires separate paths for batch and real-time processing, the Kappa Architecture uses a single stream processing engine for both real-time and historical data processing.

Main elements of the Kappa Design Pattern include:

• Single Data Pipeline: A unified data processing stream that handles both real-time and historical data.
• Stream Processing Engine: A core component that processes incoming data in real-time.
• Immutable Data Store: All data is stored in an immutable, append-only log, ensuring data integrity and enabling easy reprocessing.
• Reprocessing Capability: The ability to reprocess historical data by replaying the log.

References:

1. Kappa Architecture by Milinda Pathirage
2. Kappa Architecture GitHub Repository
3. Java Design Patterns Contribution Guidelines

Acceptance Criteria:

1. Implement a single data pipeline that processes both real-time and historical data.
2. Integrate a stream processing engine to handle incoming data in real-time.
3. Ensure that the data store is immutable and supports reprocessing of historical data by replaying the log.

No source files, tests, or entry points are named; start by reviewing the referenced Kappa Architecture material and the Java Design Patterns contribution guidelines. Define the implementation scope from the repository's existing patterns, with completion requiring the single pipeline, real-time stream processing, immutable log, and historical replay described in the acceptance criteria.