# TICKET-PMAT-7003: Workflow Executor Implementation

**Status**: 🔨 TODO
**Priority**: High
**Complexity**: High (5-7 days)
**Sprint**: Sprint 23
**Created**: 2025-10-07
**Dependencies**: Sprint 9 (DAG + Repository) ✅ Complete

## Objective

Implement complete end-to-end workflow execution with agent integration, building on the completed DAG engine and Repository to create a production-ready workflow orchestration system.

## Requirements

### 1. WorkflowExecutor (2-3 days)
- [ ] Execute workflows using DagEngine for ordering
- [ ] Integrate with AgentRegistry for step execution
- [ ] Implement parallel execution support
- [ ] Handle conditional steps and loops
- [ ] Retry logic with exponential backoff strategies
- [ ] Timeout handling per step
- [ ] Resource management and cleanup

### 2. WorkflowMonitor (1-2 days)
- [ ] Track workflow execution metrics in real-time
- [ ] Record step results and timings
- [ ] Alert on failures and timeouts
- [ ] Generate execution reports
- [ ] Export metrics for observability
- [ ] Dashboard integration hooks

### 3. Recovery System (1 day)
- [ ] Checkpoint/resume functionality
- [ ] Rollback and compensation handlers
- [ ] Error recovery strategies
- [ ] State persistence
- [ ] Idempotency guarantees

### 4. Integration Testing (1-2 days)
- [ ] End-to-end workflow execution tests
- [ ] Multi-agent coordination tests
- [ ] Failure and recovery scenarios
- [ ] Performance benchmarks
- [ ] Stress tests with complex workflows

## Implementation Plan

### Files to Create/Extend
- `server/src/workflow/executor.rs` (extend existing)
- `server/src/workflow/monitoring.rs` (extend existing)
- `server/src/workflow/recovery.rs` (extend existing)
- `server/src/workflow/checkpoint.rs` (new)
- Integration tests in `server/tests/workflow_integration.rs`

### Key Components

#### WorkflowExecutor
```rust
pub struct WorkflowExecutor {
    dag_engine: DagEngine,
    agent_registry: Arc<AgentRegistry>,
    monitor: WorkflowMonitor,
    recovery: RecoverySystem,
}

impl WorkflowExecutor {
    pub async fn execute(&self, workflow: &Workflow) -> Result<ExecutionResult>;
    pub async fn execute_step(&self, step: &WorkflowStep) -> Result<StepResult>;
    pub async fn execute_parallel(&self, steps: Vec<WorkflowStep>) -> Result<Vec<StepResult>>;
}
```

#### WorkflowMonitor
```rust
pub struct WorkflowMonitor {
    metrics: Arc<Mutex<ExecutionMetrics>>,
    alerts: AlertManager,
}

impl WorkflowMonitor {
    pub fn record_step_start(&self, step_id: &str);
    pub fn record_step_complete(&self, step_id: &str, result: &StepResult);
    pub fn record_step_failure(&self, step_id: &str, error: &Error);
    pub fn generate_report(&self) -> ExecutionReport;
}
```

#### RecoverySystem
```rust
pub struct RecoverySystem {
    checkpoint_store: CheckpointStore,
    compensation_handlers: HashMap<String, CompensationHandler>,
}

impl RecoverySystem {
    pub async fn checkpoint(&self, state: &WorkflowState) -> Result<()>;
    pub async fn resume(&self, checkpoint_id: &str) -> Result<WorkflowState>;
    pub async fn rollback(&self, to_checkpoint: &str) -> Result<()>;
}
```

## Success Criteria

- [ ] Workflows execute end-to-end with proper ordering
- [ ] Parallel execution works correctly
- [ ] Retry logic handles transient failures
- [ ] Recovery system can resume from checkpoints
- [ ] Monitoring captures all metrics
- [ ] Integration tests pass (95%+ coverage)
- [ ] Performance: <100ms overhead per step
- [ ] Stress test: 100+ concurrent workflows

## Testing Strategy

1. **Unit Tests**: Each component isolated
2. **Integration Tests**: End-to-end workflow scenarios
3. **Failure Tests**: Network failures, timeouts, agent crashes
4. **Recovery Tests**: Checkpoint/resume/rollback
5. **Performance Tests**: Latency, throughput, resource usage

## Value Delivered

**Before**: DAG engine and Repository exist but no execution layer
**After**: Complete workflow orchestration system ready for production
**Impact**: Makes workflow system fully operational, enables complex multi-agent coordination
**ROI**: High - Completes Sprint 9 to 100%, unblocks agent orchestration use cases

## Estimated Effort

5-7 days

## Notes

- Build on existing DAG engine and Repository (already complete)
- Integrate with AgentRegistry for step execution
- Use tokio for async execution
- Consider using tokio::time for timeout handling
- Use serde for checkpoint serialization
- Monitor memory usage during parallel execution
