Tutorial 9: Complex Orchestration Strategies
Master advanced orchestration techniques for large-scale projects, including multi-phase implementations, conditional workflows, and intelligent decision trees. Learn to handle the most complex development scenarios.
Learning Objectives
By the end of this tutorial, you'll:
- ✅ Design multi-phase orchestrations
- ✅ Implement conditional workflows
- ✅ Handle complex dependencies
- ✅ Create intelligent decision trees
- ✅ Orchestrate system-wide changes
Prerequisites
- Completed intermediate tutorials
- Large project experience helpful
- 90 minutes of time
Understanding Complex Orchestration
Complex orchestration handles:
- Multi-phase projects spanning weeks
- Conditional paths based on discoveries
- Dynamic adaptation to changing requirements
- System-wide refactoring with safety
- Cross-team coordination at scale
Scenario: Microservices Migration
We'll orchestrate migrating a monolithic application to microservices - a complex, multi-phase project.
Part 1: Strategic Orchestration
Initial Analysis
/orchestrate "
Analyze our monolithic e-commerce application and create a comprehensive plan
to migrate to microservices architecture. The monolith currently handles:
- User management and authentication
- Product catalog and inventory
- Order processing and payments
- Shipping and fulfillment
- Customer support tickets
- Analytics and reporting
Constraints:
- Must maintain 99.9% uptime
- No data loss permitted
- Gradual migration preferred
- Current team size: 12 developers
"Observe the Strategic Plan
The orchestration will produce a multi-phase strategy:
🎯 Strategic Microservices Migration Plan
## Phase 0: Foundation (Weeks 1-2)
- Set up service discovery
- Implement API gateway
- Create shared libraries
- Establish CI/CD pipeline
- Define service boundaries
## Phase 1: Edge Services (Weeks 3-6)
- Extract authentication service
- Implement user service
- Create API compatibility layer
- Set up monitoring
## Phase 2: Core Business (Weeks 7-12)
- Extract product catalog
- Separate inventory management
- Isolate order processing
- Implement event bus
## Phase 3: Support Services (Weeks 13-16)
- Extract payment processing
- Separate shipping service
- Isolate support system
- Create reporting service
## Phase 4: Optimization (Weeks 17-20)
- Remove monolith code
- Optimize service communication
- Implement caching
- Performance tuningPart 2: Conditional Orchestration
Decision Tree Implementation
Create .orchestre/commands/orchestrate-with-decisions.md:
# /orchestrate-with-decisions
Orchestrate with intelligent decision points.
## Prompt
Create an orchestration plan with conditional paths:
1. **Assess Current State**
- If microservices exist → Plan integration
- If monolith → Plan extraction
- If hybrid → Plan completion
2. **Choose Migration Strategy**
Based on assessment:
**Strangler Fig Pattern** (if high risk):
- Gradual replacement
- Parallel running
- Progressive cutover
**Big Bang** (if low risk):
- Complete rewrite
- Full cutover
- Shorter timeline
**Branch by Abstraction** (if complex):
- Abstract interfaces
- Swap implementations
- Feature flags
3. **Dynamic Phase Planning**
For each phase:
- Check prerequisites
- Assess risks
- Define rollback plan
- Set success criteria
4. **Adaptive Execution**
After each phase:
- Measure impact
- Adjust next phase
- Update timeline
- Reassess approach
Generate executable plan with decision points.Using Conditional Orchestration
/orchestrate-with-decisions "Migrate authentication to microservice"Output includes decision points:
## Conditional Migration Plan
### Decision Point 1: Current Auth System
```bash
/analyze-auth-systemIF: Using JWT tokens → Path A: Stateless service extraction → Timeline: 1 week → Risk: Low
IF: Using sessions → Path B: Add token support first → Timeline: 2 weeks
→ Risk: Medium
IF: Multiple auth methods → Path C: Implement auth gateway → Timeline: 3 weeks → Risk: High
Decision Point 2: User Data Location
/analyze-user-dataIF: Single database → Extract user tables → Create service database
IF: Multiple databases → Implement data aggregation → Consider CQRS pattern
Execution Plan
Based on decisions above:
- [Conditional steps inserted here]
- [Adapted to discoveries]
## Part 3: Dependency Management
### Complex Dependency Chains
```bash
/orchestrate "
Map dependencies for extracting order service:
- Orders depend on users, products, inventory, payments
- Must maintain data consistency
- Need real-time inventory updates
- Payment processing must be atomic
"Dependency Resolution Strategy
## Dependency Resolution Plan
### Layer 1: Data Dependencies
```mermaid
graph TD
Orders --> Users[User Service]
Orders --> Products[Product Service]
Orders --> Inventory[Inventory Service]
Orders --> Payments[Payment Service]Resolution Strategy
Shared Data Pattern
typescript// Order service maintains minimal data interface Order { id: string userId: string // Reference only items: OrderItem[] // Product IDs only paymentId: string // Reference only }Event Sourcing
typescript// Publish events for consistency orderService.on('OrderCreated', async (event) => { await inventoryService.reserve(event.items) await paymentService.process(event.payment) })Saga Pattern
typescript// Coordinate distributed transactions class OrderSaga { async execute(order) { const saga = new Saga() .step(inventoryService.reserve) .compensate(inventoryService.release) .step(paymentService.charge) .compensate(paymentService.refund) .step(orderService.confirm) await saga.run(order) } }
## Part 4: Multi-Phase Execution
### Phase Orchestration
```bash
/orchestrate "Execute Phase 1 of microservices migration with rollback capability"Intelligent Phase Execution
## Phase 1 Execution Plan
### Pre-Phase Validation
```bash
/validate-prerequisites "service-discovery, api-gateway, monitoring"Step 1: Extract Authentication Service
1.1 Preparation
/execute-task "Create auth service repository"
/execute-task "Set up service infrastructure"
/execute-task "Implement service interfaces"1.2 Parallel Development
/setup-parallel "auth-service" "monolith-adapter" "integration-tests"
/distribute-tasks "
auth-service:
- Implement JWT generation
- Create user validation
- Add refresh token logic
monolith-adapter:
- Proxy auth requests
- Maintain session compatibility
- Add feature flags
integration-tests:
- Test both paths
- Verify compatibility
- Load test new service
"1.3 Progressive Rollout
/execute-task "Enable for 1% of traffic"
# Monitor for 24 hours
/execute-task "Increase to 10% traffic"
# Monitor for 48 hours
/execute-task "Increase to 50% traffic"
# Monitor for 48 hours
/execute-task "Full rollout"Rollback Plan
At any point:
/execute-rollback "Revert to monolith auth"
## Part 5: System-Wide Orchestration
### Cross-Service Coordination
```bash
/orchestrate "
Coordinate system-wide change:
- Update API versioning across all services
- Implement new error format
- Add correlation IDs for tracing
- Standardize logging format
Must be backward compatible
"Orchestrated System Update
## System-Wide Update Orchestration
### Phase 1: Preparation
All services in parallel:
```bash
/coordinate-parallel "Implement backward-compatible changes"
service-1:
/execute-task "Add version negotiation"
/execute-task "Support both error formats"
service-2:
/execute-task "Add correlation ID passing"
/execute-task "Dual logging format"
[... for all services]Phase 2: Staged Rollout
# Enable new features via feature flags
/execute-task "Enable v2 API for internal services"
/execute-task "Test service communication"
/execute-task "Enable for beta customers"
/execute-task "Monitor error rates"Phase 3: Migration
# Migrate clients progressively
/orchestrate "Create client migration plan"
/execute-task "Update SDKs with version selection"
/execute-task "Notify API consumers"
/execute-task "Provide migration tools"Phase 4: Cleanup
# After all clients migrated
/execute-task "Remove v1 support"
/execute-task "Clean up compatibility code"
/execute-task "Update documentation"
## Advanced Patterns
### Pattern 1: Recursive Orchestration
```bash
/orchestrate "
For each service identified:
- Orchestrate its extraction
- Each extraction may identify sub-services
- Recursively orchestrate until atomic services
"Pattern 2: Adaptive Timeline
## Adaptive Timeline Orchestration
Initial estimate: 20 weeks
After each phase:
1. Measure actual vs estimated
2. Adjust remaining estimates
3. Re-evaluate approach
4. Update stakeholders
If behind schedule:
- Identify bottlenecks
- Propose adjustments
- Consider scope changesPattern 3: Risk-Based Orchestration
/orchestrate "Plan migration prioritizing by risk assessment"Output:
## Risk-Based Migration Order
### Low Risk First (Build Confidence)
1. Logging service (read-only, stateless)
2. Notification service (async, non-critical)
3. Search service (cacheable, read-heavy)
### Medium Risk (Core Features)
4. User service (critical but well-defined)
5. Product service (complex but stable)
### High Risk Last (With Lessons Learned)
6. Payment service (financial data)
7. Order service (complex dependencies)Real-World Example: Feature Flag System
Complex orchestration for adding feature flags across the system:
/orchestrate "
Implement comprehensive feature flag system:
- Centralized flag management
- Real-time flag updates
- User targeting
- A/B testing support
- Gradual rollouts
- Emergency kill switches
Must work across web, mobile, and API
"Result:
## Feature Flag System Orchestration
### Analysis Phase
- 15 services need integration
- 3 client types (web, iOS, Android)
- Existing configuration system
- Performance requirements: <50ms
### Architecture Decision
Based on analysis:
→ Centralized service with edge caching
→ WebSocket for real-time updates
→ SDK for each platform
### Implementation Phases
#### Phase 1: Core Service (Week 1-2)
```bash
/create flag-service cloudflare-hono
/execute-task "Design flag data model"
/execute-task "Implement management API"
/execute-task "Add admin UI"Phase 2: Distribution (Week 3-4)
/setup-parallel "cdn-setup" "websocket" "sdks"
/coordinate-parallel "
cdn-setup: Configure edge caching
websocket: Real-time flag updates
sdks: Build JS, Swift, Kotlin SDKs
"Phase 3: Integration (Week 5-8)
For each service:
/execute-task "Integrate flag SDK"
/execute-task "Wrap feature code"
/execute-task "Add flag checks"
/execute-task "Test flag behavior"Phase 4: Migration (Week 9-10)
/orchestrate "Migrate existing features to flags"
/execute-task "Create flag inventory"
/execute-task "Set initial flag states"
/execute-task "Update deployment process"
## Practice Exercise
Orchestrate a complex scenario:
### Database Migration
```bash
/orchestrate "
Migrate from PostgreSQL to distributed database:
- Current size: 2TB
- Must maintain ACID guarantees
- Zero downtime required
- Support geographic distribution
- Keep costs reasonable
"Expected Considerations
- Data consistency strategies
- Gradual migration approach
- Fallback mechanisms
- Performance validation
- Cost optimization
Best Practices
1. Always Have Rollback Plans
Every phase should be reversible.
2. Measure Everything
Data drives decisions in complex orchestrations.
3. Communicate Status
Keep all stakeholders informed.
4. Validate Assumptions
What worked in dev might not in production.
5. Document Decisions
Future you will thank present you.
Common Pitfalls
1. Over-Engineering
Don't make it more complex than needed.
2. Under-Estimating
Complex orchestrations always take longer.
3. Skipping Validation
Each phase must be verified before proceeding.
4. Ignoring Dependencies
Hidden dependencies cause failures.
What You've Learned
✅ Designed multi-phase orchestrations ✅ Implemented conditional workflows ✅ Managed complex dependencies ✅ Created intelligent decision trees ✅ Orchestrated system-wide changes
Next Steps
You can now handle the most complex development scenarios!
Continue to: Advanced Tutorials →
Challenge yourself:
- Orchestrate a cloud provider migration
- Plan a complete rewrite strategy
- Design a global deployment rollout
Remember: Complex orchestration is about managing uncertainty intelligently!
