# komodo_defi_workers Implementation Plan

## Overview
The `komodo_defi_workers` package provides infrastructure for managing ephemeral and specialized KDF instances that operate independently of the main KDF instance. These workers handle specific tasks like individual swaps or automated trading strategies.

This package enables critical performance and UX improvements:
- Long-running tasks like the trading bot and swaps can be executed remotely, allowing the process to continue even if the GUI is closed.
- Specialized workers can handle intensive tasks without impacting the performance of the main KDF instance, whether it's running locally or remotely

## Core Components

### 1. Worker Manager (KdfWorkerManager)
Central coordinator for worker lifecycle management:
- Worker provisioning and cleanup
- Resource allocation
- Load balancing
- Health monitoring
- State management

```dart
class KdfWorkerManager {
  Future<KdfWorker> spawnWorker(WorkerConfig config);
  Future<void> terminateWorker(String workerId);
  Stream<WorkerHealthStatus> monitorWorkers();
  Future<List<KdfWorker>> getActiveWorkers();
}
```

### 2. Swap Worker (SwapWorker)
Optimized for single-swap execution:
- Minimal coin activation
- Focused configuration
- Quick startup/shutdown
- Transaction monitoring

```dart
class SwapWorker implements KdfWorker {
  Future<void> initialize(SwapConfig config);
  Future<SwapResult> executeSwap(SwapParameters params);
  Future<void> cleanup();
  Stream<SwapProgress> watchProgress();
}
```

### 3. Trading Bot Worker (TradingBotWorker) 
Long-running worker that manages isolated instances of KDF's trading bot:
- Trading bot process lifecycle management
- Configuration and strategy deployment
- Resource allocation and optimization
- Health monitoring and automatic recovery
- Performance metrics collection

```dart
class TradingBotWorker implements KdfWorker {
  Future<void> initialize(TradingBotConfig config);
  Future<void> deployBot(KdfTradingBotConfig botConfig);
  Future<void> stopBot();
  Future<void> updateBotConfig(KdfTradingBotConfig newConfig);
  Stream<BotHealthStatus> watchHealth();
  Stream<KdfTradingBotStatus> watchBotStatus();
}
```

### 4. Worker Pool (KdfWorkerPool)
Manages a pool of pre-initialized workers:
- Resource pooling
- Worker reuse
- Load distribution
- Pool scaling

```dart
class KdfWorkerPool {
  Future<void> initialize(PoolConfig config);
  Future<KdfWorker> acquireWorker();
  Future<void> releaseWorker(String workerId);
  Future<void> scalePool(int targetSize);
}
```

## Worker Types

### 1. Ephemeral Workers
- Single-task focused
- Quick startup/shutdown
- Minimal resource usage
- Automatic cleanup

### 2. Persistent Workers
- Long-running operations
- State preservation
- Resource optimization
- Automated recovery

## Implementation Phases

### Phase 1: Core Infrastructure
1. Basic worker management
2. Worker lifecycle handling
3. Health monitoring
4. Resource management

### Phase 2: Swap Workers
1. Swap-specific optimization
2. Transaction handling
3. Error recovery
4. Performance tuning

### Phase 3: Trading Bot Workers
1. KDF trading bot integration
2. Instance isolation
3. Resource optimization
4. Performance monitoring

### Phase 4: Advanced Features
1. Worker pooling
2. Load balancing
3. State persistence
4. Advanced monitoring

## Integration

### komodo_defi_sdk Integration
```dart
extension WorkerExtension on KomodoDefiSdk {
  Future<SwapWorker> createSwapWorker(SwapWorkerConfig config);
  Future<TradingBotWorker> createTradingWorker(TradingConfig config);
  Future<KdfWorkerPool> createWorkerPool(PoolConfig config);
}
```

### Remote Integration
The workers package integrates with `komodo_defi_remote` for deploying workers to remote servers:

```dart
class RemoteWorkerManager extends KdfWorkerManager {
  RemoteWorkerManager(RemoteKdfController remoteController);
  
  // Spawn a worker on a remote server
  Future<KdfWorker> spawnRemoteWorker(
    RemoteWorkerConfig config,
    RemoteLocation location,
  );
  
  // Create a worker pool distributed across multiple remote servers
  Future<KdfWorkerPool> createDistributedPool(
    List<RemoteLocation> locations,
    PoolConfig config,
  );

  // Get geographic metrics for deployed workers
  Future<Map<RemoteLocation, WorkerMetrics>> getDistributionMetrics();
}

// Extension on RemoteKdfController for worker management
extension WorkerManagementExtension on RemoteKdfController {
  Future<RemoteWorkerManager> createWorkerManager();
  Future<List<KdfWorker>> getActiveWorkers();
  Future<WorkerMetrics> getWorkerMetrics();
}
```

## Security Considerations

### Isolation
- Process separation
- Memory isolation
- Network segregation
- Resource limits

### Authentication
- Worker identity verification
- Access control
- Key management
- Request signing

### Monitoring
- Activity logging
- Resource tracking
- Error detection
- Anomaly detection

## Configuration Examples

### Swap Worker Config
```yaml
worker:
  type: swap
  ttl: 300s
  max_memory: 512M
  cleanup_delay: 30s
  
swap:
  coins: ["KMD", "BTC"]
  order_type: market
  slippage_tolerance: 1.0
```

### Trading Bot Config
```yaml
worker:
  type: trading
  memory_limit: 1G
  cpu_limit: 2
  auto_restart: true

trading_bot:
  kdf_config: # Standard KDF trading bot config
    strategy: grid
    pairs: ["KMD/BTC", "KMD/ETH"]
    interval: 5m
    position_limit: 1000
  instance:
    dedicated_coins: true  # Only activate needed coins
    performance_mode: true # Optimize for trading performance
    health_check_interval: 30s
```

## Directory Structure
```
lib/
  ├── src/
  │   ├── workers/         # Worker implementations
  │   ├── manager/         # Worker management
  │   ├── pool/            # Worker pooling
  │   ├── trading/         # Trading strategies
  │   └── security/        # Security implementations
  └── komodo_defi_workers.dart

test/
  ├── unit/
  ├── integration/
  └── e2e/
```

## Testing Strategy

### Unit Tests
- Worker lifecycle
- Resource management
- Trading strategies
- Error handling

### Integration Tests
- Worker coordination
- Pool management
- Strategy execution
- System recovery

### Performance Tests
- Startup time
- Resource usage
- Transaction throughput
- Strategy performance

## Monitoring & Metrics

### System Metrics
- Worker count
- Resource usage
- Error rates
- Response times

### Trading Metrics
- Trade volume
- Success rates
- Strategy performance
- Risk metrics

## Error Handling

### Recovery Strategies
1. Automatic retry
2. Graceful degradation
3. State recovery
4. Resource cleanup

### Error Types
1. System errors
2. Trading errors
3. Network errors
4. Resource errors

## Future Considerations

1. **Advanced Trading Features**
   - Machine learning integration
   - Custom strategy framework
   - Advanced risk management
   - Portfolio optimization

2. **Scaling Improvements**
   - Geographic distribution
   - Automatic scaling
   - Performance optimization
   - Resource prediction

3. **Integration Enhancements**
   - External data sources
   - Additional exchanges
   - Custom plugins
   - API extensions

## Documentation Requirements

1. API Documentation
2. Trading Strategy Guide
3. Performance Tuning Guide
4. Security Best Practices
5. Troubleshooting Guide

## Initial Milestones

### Milestone 1: Basic Worker Management
- Core worker framework
- Basic lifecycle management
- Simple swap worker
- Initial documentation

### Milestone 2: Trading Capabilities
- Trading bot worker
- Basic strategies
- Market analysis
- Position management

### Milestone 3: Advanced Features
- Worker pooling
- Advanced monitoring
- Performance optimization
- Complete documentation

### Milestone 4: Production Readiness
- Security hardening
- Recovery mechanisms
- Advanced strategies
- Production deployment guide