Technical Architecture and Components
The Message Processor implements a modern, distributed architecture designed for reliability and efficient processing of large transaction volumes. The system comprises four core components that work in concert to ensure smooth message processing:
Integration Layer
The integration system manages inbound and outbound connections, supporting multiple enterprise messaging platforms:
- Supported Message Brokers:
- Apache Kafka
- Apache Pulsar
- Amazon SQS
- Google Cloud Pub/Sub
- Azure Event Hub
- Key Features:
- Protocol-agnostic message handling
- Automatic connection management
- Message format validation
- Delivery guarantee enforcement
Data Storage Layer
MongoDB serves as the primary data store, managing three critical data types:
- Workflow Metadata:
- Process definitions
- Routing rules
- Transformation logic
- Business rules
- Enrichment Data:
- Reference data
- Lookup tables
- Configuration parameters
- Transaction Data:
- Message processing history
- Audit trails
- Processing results
Cache Layer
Redis provides high-performance caching and concurrency control:
- Primary Functions:
- Temporary data storage
- Processing state management
- Concurrency lock management
- Key Features:
- Message deduplication
- Race condition prevention
- Processing speed optimization
Workflow Engine
The core processing component orchestrates message handling:
- Responsibilities:
- Workflow execution
- State management
- Data transformation
- Rule application
- Integration Points:
- Pulls workflow definitions from MongoDB
- Uses Redis for concurrency control
- Coordinates with integration layer
- Manages transaction state
System Interaction Flow
- Messages arrive through the integration layer via supported message brokers
- Workflow engine retrieves relevant workflow metadata from MongoDB
- Redis manages processing locks and temporary state
- Workflow engine executes the defined process
- Results are stored in MongoDB and sent to outbound destinations