# SPEC-018: Advanced Messaging Features

## Overview
Advanced messaging capabilities including message transformations, multiple format support, message shaping, and testing/simulation features for enterprise message processing.

## Components

### Message Transformations
- **Format Conversion**: JSON, Avro, Protocol Buffers, XML support
- **Data Transformation**: Field mapping, data type conversion, validation
- **Message Enrichment**: Add metadata, timestamps, correlation IDs
- **Message Filtering**: Content-based filtering and routing

### Message Format Support
- **JSON**: Native JSON message support with validation
- **Avro**: Apache Avro schema-based messaging
- **Protocol Buffers**: Google Protocol Buffers support
- **XML**: XML message parsing and validation
- **Binary**: Raw binary message support
- **Text**: Plain text message support

### Message Shaping
- **Automatic Headers**: Add retry metadata, timestamps, correlation IDs
- **Message Validation**: Schema-based message validation
- **Message Routing**: Content-based routing and filtering
- **Message Aggregation**: Combine multiple messages into single message

### Testing and Simulation
- **Test Message Injection**: Inject test messages into queues
- **Failure Simulation**: Simulate consumer failures for testing
- **Load Testing**: Generate high-volume test messages
- **Scenario Testing**: Test complex message processing scenarios

### Advanced Message Processing
- **Message Batching**: Process messages in batches for efficiency
- **Message Ordering**: Maintain message order across processing
- **Message Deduplication**: Prevent duplicate message processing
- **Message Replay**: Replay messages for testing and recovery

### Message Analytics
- **Message Tracking**: Track messages through processing pipeline
- **Performance Analytics**: Message processing performance metrics
- **Error Analytics**: Message processing error analysis
- **Usage Analytics**: Message usage patterns and statistics

### Internal Operations (Mixed AMQP + Custom Logic)
**CRITICAL**: Message operations use AMQP protocol + custom transformation logic.

- `message.transform`: Transform message format/content (custom logic, NOT in OpenAPI)
- `message.validate`: Validate message against schema (custom validation with pre-generated Pydantic models)
- `message.inject-test`: Inject test message via AMQP publish (AMQP protocol)
- `message.simulate-failure`: Simulate consumer failure (testing utility, NOT in OpenAPI)
- `message.get-analytics`: Get message processing analytics (custom metrics aggregation)

**Note**: These are advanced features built on top of basic AMQP operations. Index in vector database for semantic discovery.

## Technical Requirements

### Message Format Support
- Support for JSON, Avro, Protocol Buffers, XML, binary, text
- Schema validation for structured formats
- Efficient serialization/deserialization
- Format conversion capabilities

### Transformation Performance
- Message transformation latency < 50ms
- Support for 1000+ transformations per second
- Memory-efficient transformation processing
- Batch transformation support

### Testing Capabilities
- Test message generation and injection
- Failure simulation and testing
- Load testing with high message volumes
- Scenario testing for complex workflows

### Analytics and Monitoring
- Real-time message tracking and analytics
- Performance metrics for message processing
- Error analysis and reporting
- Usage pattern analysis

## Acceptance Criteria

### Functional Requirements
- [ ] All message formats are supported correctly
- [ ] Message transformations work accurately
- [ ] Message validation functions properly
- [ ] Test message injection works correctly
- [ ] Failure simulation functions as expected

### Performance Requirements
- [ ] Message transformation latency under 50ms
- [ ] Supports 1000+ transformations per second
- [ ] Memory usage is efficient for transformations
- [ ] Batch processing works efficiently

### Quality Requirements
- [ ] Message validation is accurate and comprehensive
- [ ] Test message generation is reliable
- [ ] Failure simulation is realistic and useful
- [ ] Analytics provide actionable insights

### Reliability Requirements
- [ ] Message transformations are reliable
- [ ] Test message injection is safe and controlled
- [ ] Failure simulation doesn't affect production
- [ ] Analytics data is accurate and consistent

## Dependencies
- Apache Avro for Avro message support
- Protocol Buffers for protobuf support
- lxml for XML message processing
- asyncio for concurrent message processing

## Implementation Notes
- Use industry-standard libraries for message format support
- Implement efficient message transformation pipelines
- Set up comprehensive message validation
- Create test message generation and injection system
- Implement failure simulation and testing
- Set up message analytics and monitoring
- Create message processing performance optimization
- Implement message tracking and correlation
- Set up message replay and recovery mechanisms
- Create message processing documentation and examples