proffesor-for-testing__agentic-qe/docs/specifications/MIGRATION-STRATEGY.md

Phase 1 Migration Strategy

Multi-Model Router + Streaming Integration Version: 1.0.5 Date: 2025-10-16

---

Table of Contents

1. Migration Overview
2. Pre-Migration Preparation
3. Migration Phases
4. Configuration Migration
5. Code Migration
6. Data Migration
7. Testing Strategy
8. Rollback Procedures
9. Success Criteria
10. Communication Plan

---

1. Migration Overview

1.1 Migration Goals

1. Zero Downtime: System remains operational throughout migration
2. Zero Breaking Changes: Existing functionality preserved
3. Gradual Rollout: Features enabled incrementally
4. Safe Rollback: Ability to revert at any time
5. Validation: Extensive testing at each phase

1.2 Migration Timeline

Phase	Duration	Description	Success Criteria
Preparation	1 week	Setup, testing, documentation	All tests pass, docs complete
Alpha	2 weeks	Deploy with features disabled	Zero regressions
Beta	2 weeks	Enable for dev/staging	Positive metrics
Limited Release	1 week	Enable for 10% production	Cost savings verified
Full Release	1 week	Enable for 100% production	All metrics green
Post-Release	Ongoing	Monitor, optimize, iterate	Sustained improvements

Total: 7 weeks from start to full rollout

1.3 Risk Assessment

Risk	Probability	Impact	Mitigation
Performance degradation	Low	High	Load testing, gradual rollout
Increased costs	Low	Medium	Budget limits, cost tracking
Integration issues	Medium	Medium	Feature flags, rollback plan
Memory issues	Low	Medium	Memory profiling, limits
Streaming failures	Medium	Low	Graceful fallback to sync

---

2. Pre-Migration Preparation

2.1 Environment Setup

Development Environment:

# 1. Create feature branch
git checkout -b feature/phase1-routing-streaming

# 2. Install dependencies (no new deps required)
npm install

# 3. Set up test environment variables
cat > .env.test <<EOF
# Feature Flags (disabled for safety)
FEATURE_MULTI_MODEL_ROUTER=false
FEATURE_STREAMING=false

# Routing Configuration
ROUTING_ENABLED=false
ROUTING_DEFAULT_MODEL=claude-sonnet-4.5

# Model API Keys
ANTHROPIC_API_KEY=your-api-key-here

# Cost Tracking
COST_TRACKING_ENABLED=true
BUDGET_LIMIT_DAILY=10.00
BUDGET_LIMIT_MONTHLY=200.00

# Streaming Configuration
STREAMING_ENABLED=false
STREAMING_BUFFER_SIZE=1024
STREAMING_BACKPRESSURE_THRESHOLD=0.8
STREAMING_TIMEOUT_MS=30000
EOF

# 4. Create test configuration
cp config/fleet.example.yaml config/fleet.test.yaml

Configuration Files:

# config/fleet.test.yaml
fleet:
  id: 'test-fleet'
  name: 'Test Fleet'

# IMPORTANT: Features disabled by default
features:
  multiModelRouter: false
  streaming: false

# Routing config (ready but disabled)
routing:
  enabled: false
  defaultModel: 'claude-sonnet-4.5'
  models:
    - name: 'claude-opus-4'
      provider: 'anthropic'
      model: 'claude-opus-4-20250514'
      capabilities:
        maxTokens: 200000
        supportsStreaming: true
        costPer1kTokens:
          input: 15.00
          output: 75.00
      complexityRange:
        min: 0.7
        max: 1.0
      enabled: true

    - name: 'claude-sonnet-4.5'
      provider: 'anthropic'
      model: 'claude-sonnet-4-5-20250929'
      capabilities:
        maxTokens: 200000
        supportsStreaming: true
        costPer1kTokens:
          input: 3.00
          output: 15.00
      complexityRange:
        min: 0.3
        max: 0.8
      enabled: true

    - name: 'claude-haiku-4'
      provider: 'anthropic'
      model: 'claude-haiku-4-20250110'
      capabilities:
        maxTokens: 200000
        supportsStreaming: true
        costPer1kTokens:
          input: 0.80
          output: 4.00
      complexityRange:
        min: 0.0
        max: 0.4
      enabled: true

  costTracking:
    enabled: true
    budgetLimits:
      daily: 10.00
      monthly: 200.00
    alertThresholds:
      dailyPercent: 80
      monthlyPercent: 90

# Streaming config (ready but disabled)
streaming:
  enabled: false
  bufferSize: 1024
  backpressureThreshold: 0.8
  timeoutMs: 30000
  retryConfig:
    maxRetries: 3
    backoffMs: 1000
    backoffMultiplier: 2

2.2 Backup and Documentation

Create Backups:

# 1. Backup current configuration
cp config/fleet.yaml config/fleet.yaml.backup.v1.0.4

# 2. Backup database (if using file-based)
cp data/fleet.db data/fleet.db.backup.v1.0.4

# 3. Create rollback tag
git tag -a v1.0.4-stable -m "Stable version before Phase 1 migration"
git push origin v1.0.4-stable

Documentation Checklist:

• Architecture document created
• Component diagrams created
• Integration specifications written
• Migration strategy documented (this document)
• API documentation updated
• User guide updated
• Troubleshooting guide created
• Runbook for operations team

2.3 Team Preparation

Training Sessions:

1. Development Team (2 hours)

   • Architecture overview
   • Code changes walkthrough
   • Testing procedures
   • Debugging techniques

2. Operations Team (1 hour)

   • Configuration management
   • Monitoring setup
   • Rollback procedures
   • Incident response

3. QA Team (1.5 hours)

   • Test plan review
   • Feature flag usage
   • Performance testing
   • Edge case scenarios

---

3. Migration Phases

3.1 Phase 0: Code Integration (Week 1)

Objective: Merge new code with all features DISABLED

Tasks:

1. Implement Core Components

   # Create component files
   touch src/core/routing/ModelRouter.ts
   touch src/core/routing/ComplexityAnalyzer.ts
   touch src/core/routing/CostTracker.ts
   touch src/mcp/tools/StreamingMCPTool.ts
   touch src/core/streaming/StreamManager.ts
   touch src/core/streaming/BufferManager.ts
   touch src/core/FeatureFlags.ts
   

2. Update Existing Components

   • FleetManager: Add router initialization
   • BaseAgent: Add routing support
   • Config: Add new configuration sections

3. Run Test Suite

   # All tests should pass with features disabled
   npm run test
   
   # Type checking
   npm run typecheck
   
   # Linting
   npm run lint
   

4. Merge to Main

   # Create pull request
   git add .
   git commit -m "feat(phase1): Add routing and streaming infrastructure (disabled)"
   git push origin feature/phase1-routing-streaming
   
   # After review and approval
   git checkout main
   git merge feature/phase1-routing-streaming
   git push origin main
   

Success Criteria:

• ✅ All existing tests pass
• ✅ No performance regression
• ✅ Zero functionality changes
• ✅ Code review approved
• ✅ Documentation updated

---

3.2 Phase 1: Alpha Deployment (Weeks 2-3)

Objective: Deploy to development/staging with features DISABLED

Environment: Development, Staging

Configuration:

# config/fleet.dev.yaml
features:
  multiModelRouter: false  # Still disabled
  streaming: false         # Still disabled

Deployment Steps:

# 1. Deploy to development
npm run build
npm run deploy:dev

# 2. Verify deployment
curl https://dev-aqe.example.com/health
# Expected: { "status": "healthy", "version": "1.0.5", "features": { "multiModelRouter": false, "streaming": false } }

# 3. Run smoke tests
npm run test:e2e -- --env=dev

# 4. Monitor for 48 hours
# Check: Error rates, latency, memory usage

# 5. Deploy to staging
npm run deploy:staging

# 6. Run comprehensive tests
npm run test:integration -- --env=staging
npm run test:performance -- --env=staging

# 7. Monitor for 1 week

Monitoring:

# Set up alerts
./scripts/setup-monitoring.sh --env=dev

# Key metrics to watch:
# - Error rate (should be <0.1%)
# - P95 latency (should be <2s)
# - Memory usage (should be <600MB)
# - Agent spawn time (should be <100ms)

Success Criteria:

• ✅ Zero production incidents
• ✅ All metrics within baseline
• ✅ No user-reported issues
• ✅ Load tests pass
• ✅ Memory leaks not detected

---

3.3 Phase 2: Beta Testing (Weeks 4-5)

Objective: Enable features in development/staging

Environment: Development, Staging

Configuration:

# config/fleet.beta.yaml
features:
  multiModelRouter: true   # ENABLED
  streaming: true          # ENABLED

routing:
  enabled: true
  # Use conservative budget limits for testing
  costTracking:
    budgetLimits:
      daily: 5.00    # Low limit for safety
      monthly: 100.00

streaming:
  enabled: true
  # Conservative settings
  timeoutMs: 15000  # Shorter timeout for faster failure detection
  retryConfig:
    maxRetries: 2   # Fewer retries to fail faster

Enabling Process:

# 1. Enable routing only (streaming still disabled)
kubectl set env deployment/aqe-fleet FEATURE_MULTI_MODEL_ROUTER=true
kubectl set env deployment/aqe-fleet FEATURE_STREAMING=false

# 2. Monitor for 3 days
./scripts/monitor-metrics.sh --feature=routing --duration=72h

# 3. If stable, enable streaming
kubectl set env deployment/aqe-fleet FEATURE_STREAMING=true

# 4. Monitor for 3 days
./scripts/monitor-metrics.sh --feature=streaming --duration=72h

Test Scenarios:

1. Routing Validation

   # Generate test tasks of varying complexity
   npm run test:routing:complexity
   
   # Expected:
   # - Simple tasks → Haiku
   # - Medium tasks → Sonnet
   # - Complex tasks → Opus
   

2. Cost Tracking Validation

   # Run tasks and verify cost tracking
   npm run test:routing:costs
   
   # Expected:
   # - Costs recorded in memory
   # - Budget alerts triggered at 80%
   # - Budget enforcement at 100%
   

3. Streaming Validation

   # Test streaming with various scenarios
   npm run test:streaming:scenarios
   
   # Expected:
   # - Chunks received in order
   # - Backpressure handled correctly
   # - Timeouts trigger fallback
   # - Final result matches synchronous
   

Success Criteria:

• ✅ Model selection accuracy >95%
• ✅ Cost savings >20% vs. single model
• ✅ Streaming success rate >98%
• ✅ Time to first chunk <500ms
• ✅ Zero critical bugs
• ✅ Performance within SLA

---

3.4 Phase 3: Limited Production Release (Week 6)

Objective: Enable for 10% of production traffic

Environment: Production

Configuration:

# config/fleet.prod.yaml
features:
  multiModelRouter: true
  streaming: true

routing:
  enabled: true
  costTracking:
    budgetLimits:
      daily: 100.00
      monthly: 2000.00

Canary Deployment:

# 1. Deploy canary with features enabled (10% traffic)
kubectl apply -f k8s/canary-deployment.yaml

# 2. Monitor canary metrics
while true; do
  echo "=== Canary Metrics ==="
  kubectl exec -it deploy/aqe-fleet-canary -- curl localhost:3000/metrics
  echo ""
  echo "=== Stable Metrics ==="
  kubectl exec -it deploy/aqe-fleet-stable -- curl localhost:3000/metrics
  echo ""
  sleep 300  # Check every 5 minutes
done

# 3. Compare canary vs. stable
./scripts/compare-canary.sh

# 4. If metrics are good, increase to 25%
kubectl patch deployment aqe-fleet-canary -p '{"spec":{"replicas":2}}'

# 5. Continue monitoring for 24 hours

# 6. Increase to 50%
kubectl patch deployment aqe-fleet-canary -p '{"spec":{"replicas":4}}'

# 7. Continue monitoring for 24 hours

# 8. If stable, proceed to full rollout

Monitoring Dashboard:

┌─────────────────────────────────────────────────────────────┐
│              Canary vs. Stable Metrics                      │
├─────────────────────────────────────────────────────────────┤
│ Metric              │ Canary        │ Stable        │ Delta│
├─────────────────────────────────────────────────────────────┤
│ Error Rate          │ 0.05%         │ 0.05%         │  0%  │
│ P95 Latency         │ 1.8s          │ 1.9s          │ -5%  │
│ Memory Usage        │ 650MB         │ 550MB         │ +18% │
│ Cost per Task       │ $0.008        │ $0.012        │ -33% │
│ Tasks/sec           │ 45            │ 47            │ -4%  │
└─────────────────────────────────────────────────────────────┘

Success Criteria:

• ✅ Canary error rate ≤ stable error rate
• ✅ Canary latency within 10% of stable
• ✅ Cost reduction >20%
• ✅ No critical incidents
• ✅ User feedback positive

---

3.5 Phase 4: Full Production Release (Week 7)

Objective: Enable for 100% of production traffic

Configuration:

# 1. Promote canary to stable
kubectl set image deployment/aqe-fleet \
  aqe-fleet=agentic-qe:1.0.5 \
  --record

# 2. Update all replicas
kubectl scale deployment/aqe-fleet --replicas=8

# 3. Enable features globally
kubectl set env deployment/aqe-fleet \
  FEATURE_MULTI_MODEL_ROUTER=true \
  FEATURE_STREAMING=true

# 4. Remove canary deployment
kubectl delete deployment aqe-fleet-canary

# 5. Verify all pods healthy
kubectl get pods -l app=aqe-fleet

# 6. Monitor for 48 hours
./scripts/monitor-production.sh --duration=48h

Post-Deployment Validation:

# 1. Run production validation suite
npm run test:production:validate

# 2. Check cost savings
./scripts/analyze-costs.sh --period=7d

# 3. Generate performance report
./scripts/generate-report.sh --type=performance

# 4. Collect user feedback
./scripts/collect-feedback.sh

Success Criteria:

• ✅ All production pods healthy
• ✅ Error rate <0.1%
• ✅ P95 latency <2s
• ✅ Cost savings >20%
• ✅ No rollback required
• ✅ User satisfaction maintained

---

4. Configuration Migration

4.1 Automatic Migration Script

File: scripts/migrate-config.ts

#!/usr/bin/env ts-node

import * as fs from 'fs-extra';
import * as yaml from 'yaml';
import * as path from 'path';

interface OldConfig {
  fleet: any;
  agents: any[];
  database: any;
  logging: any;
  api: any;
  security: any;
  // Old AI config
  ai?: {
    model: string;
    apiKey: string;
  };
}

interface NewConfig extends OldConfig {
  features: {
    multiModelRouter: boolean;
    streaming: boolean;
  };
  routing?: any;
  streaming?: any;
}

/**
 * Migrate v1.0.4 config to v1.0.5 format
 */
async function migrateConfig(
  oldConfigPath: string,
  newConfigPath: string
): Promise<void> {
  console.log(`Migrating config from ${oldConfigPath} to ${newConfigPath}`);

  // Read old config
  const oldConfigContent = await fs.readFile(oldConfigPath, 'utf8');
  const oldConfig: OldConfig = yaml.parse(oldConfigContent);

  // Create new config with features disabled
  const newConfig: NewConfig = {
    ...oldConfig,

    // Add feature flags (disabled for safety)
    features: {
      multiModelRouter: false,
      streaming: false
    },

    // Add routing config if AI model was configured
    routing: oldConfig.ai?.model ? {
      enabled: false,
      defaultModel: oldConfig.ai.model,
      models: [
        {
          name: 'claude-opus-4',
          provider: 'anthropic',
          model: 'claude-opus-4-20250514',
          capabilities: {
            maxTokens: 200000,
            supportsStreaming: true,
            costPer1kTokens: { input: 15.00, output: 75.00 }
          },
          complexityRange: { min: 0.7, max: 1.0 },
          enabled: true
        },
        {
          name: 'claude-sonnet-4.5',
          provider: 'anthropic',
          model: 'claude-sonnet-4-5-20250929',
          capabilities: {
            maxTokens: 200000,
            supportsStreaming: true,
            costPer1kTokens: { input: 3.00, output: 15.00 }
          },
          complexityRange: { min: 0.3, max: 0.8 },
          enabled: true
        },
        {
          name: 'claude-haiku-4',
          provider: 'anthropic',
          model: 'claude-haiku-4-20250110',
          capabilities: {
            maxTokens: 200000,
            supportsStreaming: true,
            costPer1kTokens: { input: 0.80, output: 4.00 }
          },
          complexityRange: { min: 0.0, max: 0.4 },
          enabled: true
        }
      ],
      complexity: {
        tokenWeighting: 0.4,
        structureWeighting: 0.3,
        contextWeighting: 0.3
      },
      costTracking: {
        enabled: false,
        budgetLimits: {
          daily: 100.00,
          monthly: 2000.00
        },
        alertThresholds: {
          dailyPercent: 80,
          monthlyPercent: 90
        }
      }
    } : undefined,

    // Add streaming config
    streaming: {
      enabled: false,
      bufferSize: 1024,
      backpressureThreshold: 0.8,
      timeoutMs: 30000,
      retryConfig: {
        maxRetries: 3,
        backoffMs: 1000,
        backoffMultiplier: 2
      }
    }
  };

  // Remove old AI config if present
  delete (newConfig as any).ai;

  // Write new config
  const newConfigContent = yaml.stringify(newConfig, {
    indent: 2,
    lineWidth: 0
  });
  await fs.writeFile(newConfigPath, newConfigContent, 'utf8');

  console.log('Migration complete!');
  console.log('IMPORTANT: Features are DISABLED by default for safety.');
  console.log('Review the new config and enable features when ready.');
}

// Run migration
const oldPath = process.argv[2] || 'config/fleet.yaml';
const newPath = process.argv[3] || 'config/fleet.v1.0.5.yaml';

migrateConfig(oldPath, newPath)
  .then(() => process.exit(0))
  .catch(error => {
    console.error('Migration failed:', error);
    process.exit(1);
  });

Usage:

# Migrate config file
npm run migrate-config -- config/fleet.yaml config/fleet.v1.0.5.yaml

# Review changes
diff config/fleet.yaml config/fleet.v1.0.5.yaml

# Backup old config
cp config/fleet.yaml config/fleet.yaml.v1.0.4.backup

# Use new config
cp config/fleet.v1.0.5.yaml config/fleet.yaml

# Verify config is valid
npm run validate-config

4.2 Manual Migration Checklist

If automatic migration is not suitable:

Step 1: Add Feature Flags

# Add to root of config
features:
  multiModelRouter: false
  streaming: false

Step 2: Add Routing Configuration

routing:
  enabled: false
  defaultModel: 'claude-sonnet-4.5'
  models:
    # Copy from example config
  complexity:
    tokenWeighting: 0.4
    structureWeighting: 0.3
    contextWeighting: 0.3
  costTracking:
    enabled: false
    budgetLimits:
      daily: 100.00
      monthly: 2000.00

Step 3: Add Streaming Configuration

streaming:
  enabled: false
  bufferSize: 1024
  backpressureThreshold: 0.8
  timeoutMs: 30000
  retryConfig:
    maxRetries: 3
    backoffMs: 1000
    backoffMultiplier: 2

Step 4: Validate

npm run validate-config -- config/fleet.yaml

---

5. Code Migration

5.1 Agent Code Migration

For Custom Agents:

If you have custom agents extending BaseAgent, minimal changes needed:

Before (v1.0.4):

export class MyCustomAgent extends BaseAgent {
  protected async performTask(task: QETask): Promise<any> {
    // Your implementation
    const result = await this.myCustomLogic(task);
    return result;
  }
}

After (v1.0.5):

export class MyCustomAgent extends BaseAgent {
  // Rename to performTaskImpl
  protected async performTaskImpl(
    task: QETask,
    selection?: ModelSelection  // New optional parameter
  ): Promise<any> {
    // Your implementation (unchanged)
    const result = await this.myCustomLogic(task);

    // Optional: Use model selection info
    if (selection) {
      this.logger.info(`Using model: ${selection.modelName}`);
    }

    return result;
  }
}

Migration Script:

# Automated migration for custom agents
./scripts/migrate-agents.sh

# Script will:
# 1. Find all classes extending BaseAgent
# 2. Rename performTask to performTaskImpl
# 3. Add optional ModelSelection parameter
# 4. Add backward compatibility wrapper

5.2 MCP Tool Migration

For Custom MCP Tools:

Before (v1.0.4):

export class MyCustomTool extends BaseMCPTool {
  async execute(params: any): Promise<any> {
    // Your implementation
  }
}

After (v1.0.5):

export class MyCustomTool extends BaseMCPTool {
  async execute(params: any): Promise<any> {
    // Your implementation (unchanged)
  }

  // Optional: Add streaming support
  supportsStreaming(): boolean {
    return true;  // if your tool supports streaming
  }

  async executeStreaming(
    params: any,
    callbacks: StreamCallbacks
  ): Promise<any> {
    // Optional streaming implementation
    callbacks.onStart?.({ streamId: '...', ... });

    // Process in chunks
    for (const chunk of this.processInChunks(params)) {
      callbacks.onChunk?.(chunk);
    }

    callbacks.onComplete?.({ data: result });
    return result;
  }
}

---

6. Data Migration

6.1 Memory Store Migration

No migration needed - SwarmMemoryManager schema is backward compatible.

New partitions are created automatically:

• routing/costs - Cost tracking data
• routing/selections - Model selections
• streaming/sessions - Streaming sessions

Optional: Cleanup Old Data

// Clean up test data before production
await memoryStore.clear('test-partition');

// Set up new partitions
await memoryStore.store(
  'routing/initialized',
  { version: '1.0.5', timestamp: Date.now() },
  { partition: 'coordination', owner: 'system', accessLevel: AccessLevel.SYSTEM }
);

---

7. Testing Strategy

7.1 Test Phases

Phase 1: Unit Tests

npm run test:unit
# Expected: 100% pass rate

Phase 2: Integration Tests

npm run test:integration
# Expected: 100% pass rate

Phase 3: Performance Tests

npm run test:performance
# Expected: No degradation

Phase 4: End-to-End Tests

npm run test:e2e
# Expected: All workflows functional

7.2 Test Scenarios

Backward Compatibility Tests:

describe('Backward Compatibility', () => {
  it('should work with features disabled', async () => {
    const config = createConfig({ features: { multiModelRouter: false, streaming: false } });
    const fleet = new FleetManager(config);
    await fleet.initialize();

    // Should work exactly as v1.0.4
    const agent = await fleet.spawnAgent('test-generator');
    const result = await agent.executeTask(task);

    expect(result).toBeDefined();
  });
});

Feature Flag Tests:

describe('Feature Flags', () => {
  it('should enable routing when flag is true', async () => {
    const config = createConfig({ features: { multiModelRouter: true } });
    const fleet = new FleetManager(config);
    await fleet.initialize();

    expect(fleet.getModelRouter()).toBeDefined();
  });
});

---

8. Rollback Procedures

8.1 Immediate Rollback (Critical Issues)

Scenario: Critical bug found in production

Procedure:

# 1. Disable features via environment variables (hot reload)
kubectl set env deployment/aqe-fleet \
  FEATURE_MULTI_MODEL_ROUTER=false \
  FEATURE_STREAMING=false

# System automatically reverts to v1.0.4 behavior
# No restart needed, takes effect in <30 seconds

# 2. Verify features disabled
kubectl exec -it deploy/aqe-fleet-0 -- \
  curl localhost:3000/health | jq '.features'
# Expected: { "multiModelRouter": false, "streaming": false }

# 3. Monitor for stabilization (5-10 minutes)
./scripts/monitor-metrics.sh --duration=600

# 4. If stable, investigate issue
# If still unstable, proceed to full rollback

Time to Rollback: <2 minutes Downtime: Zero (hot reload)

8.2 Full Rollback (Complete Revert)

Scenario: Features cannot be stabilized

Procedure:

# 1. Revert to v1.0.4 image
kubectl set image deployment/aqe-fleet \
  aqe-fleet=agentic-qe:1.0.4-stable \
  --record

# 2. Restore v1.0.4 configuration
kubectl create configmap aqe-fleet-config \
  --from-file=config/fleet.yaml.v1.0.4.backup \
  --dry-run=client -o yaml | kubectl apply -f -

# 3. Restart pods with old config
kubectl rollout restart deployment/aqe-fleet

# 4. Wait for rollout to complete
kubectl rollout status deployment/aqe-fleet

# 5. Verify v1.0.4 running
kubectl exec -it deploy/aqe-fleet-0 -- \
  curl localhost:3000/health | jq '.version'
# Expected: "1.0.4"

# 6. Restore database backup (if needed)
kubectl exec -it deploy/aqe-fleet-0 -- \
  cp /backups/fleet.db.v1.0.4.backup /data/fleet.db

# 7. Monitor for 1 hour
./scripts/monitor-metrics.sh --duration=3600

Time to Rollback: 5-10 minutes Downtime: Rolling restart (~2 minutes)

8.3 Partial Rollback (Agent-Specific)

Scenario: Issue with specific agent type

Procedure:

# Disable features for specific agent type
features:
  multiModelRouter: true
  streaming: true

# Override for problematic agent
featureOverrides:
  agentType:
    test-generator:
      multiModelRouter: false
      streaming: false

---

9. Success Criteria

9.1 Technical Metrics

Metric	Baseline (v1.0.4)	Target (v1.0.5)	Actual
Error Rate	0.05%	≤0.05%
P95 Latency	2.0s	≤2.0s
Memory Usage	550MB	≤700MB
Cost per Task	$0.012	≤$0.010
Tasks/sec	50	≥45
Time to First Chunk	N/A	<500ms

9.2 Business Metrics

Metric	Target	Actual
Cost Savings	>20%
User Satisfaction	≥95%
Incident Count	0 critical
Adoption Rate	>80%

9.3 Quality Gates

Gate 1: Pre-Deployment

• All tests pass (100%)
• Code review approved
• Documentation complete
• Security review passed

Gate 2: Alpha (Dev/Staging)

• Zero regressions detected
• Performance within baseline
• Load tests pass
• Monitoring setup complete

Gate 3: Beta (Dev/Staging with Features)

• Model selection accuracy >95%
• Cost savings >20%
• Streaming success rate >98%
• Zero critical bugs

Gate 4: Production Canary

• Canary metrics ≥ stable metrics
• No user-reported issues
• Cost tracking validated
• 24 hours stable

Gate 5: Full Production

• All pods healthy
• All metrics within SLA
• User feedback positive
• 48 hours stable

---

10. Communication Plan

10.1 Stakeholder Communication

Before Migration:

• Email to all stakeholders: Migration timeline and goals
• Engineering all-hands: Technical overview
• Ops team briefing: Deployment procedures

During Migration:

• Daily status updates in Slack
• Weekly stakeholder meeting
• Incident alerts (if any)

After Migration:

• Success announcement
• Metrics report
• Lessons learned session
• Updated documentation

10.2 User Communication

Timeline:

• T-14 days: Announcement of upcoming features
• T-7 days: Feature documentation published
• T-1 day: Deployment window notice
• T-0: Deployment in progress updates
• T+1 day: Deployment complete, feedback requested
• T+7 days: Results and metrics shared

Template Email:

Subject: New Features Coming to Agentic QE Fleet v1.0.5

Hi Team,

We're excited to announce Phase 1 of our fleet enhancement:

NEW FEATURES:
- Multi-Model Routing: Automatic model selection for optimal cost/quality
- Streaming Responses: Real-time feedback for long-running tasks

BENEFITS:
- 20%+ cost savings
- 75% faster time to first response
- Better task-to-model matching

TIMELINE:
- Alpha Testing: [Dates]
- Beta Testing: [Dates]
- Production Release: [Date]

WHAT YOU NEED TO DO:
- Review updated documentation: [Link]
- Test in staging environment: [Link]
- Provide feedback: [Form Link]

Questions? Join us at the Q&A session: [Calendar Invite]

Best,
The AQE Team

---

Appendix A: Migration Checklist

Pre-Migration

• Backup current configuration
• Backup database
• Create rollback git tag
• Run full test suite (v1.0.4)
• Document baseline metrics
• Train team members
• Setup monitoring

Phase 0: Code Integration

• Implement core components
• Update existing components
• Run test suite (all pass)
• Code review and approval
• Merge to main
• Deploy with features disabled

Phase 1: Alpha Deployment

• Deploy to dev/staging
• Verify features disabled
• Run smoke tests
• Monitor for 48 hours
• Run integration tests
• Monitor for 1 week

Phase 2: Beta Testing

• Enable routing in staging
• Monitor for 3 days
• Enable streaming in staging
• Monitor for 3 days
• Validate cost tracking
• Validate streaming

Phase 3: Limited Production

• Deploy canary (10%)
• Monitor canary vs stable
• Increase to 25%
• Monitor for 24 hours
• Increase to 50%
• Monitor for 24 hours

Phase 4: Full Production

• Promote to 100%
• Remove canary deployment
• Verify all pods healthy
• Monitor for 48 hours
• Validate cost savings
• Collect user feedback

Post-Migration

• Generate metrics report
• Update documentation
• Conduct retrospective
• Archive migration artifacts
• Celebrate success! 🎉

---

Appendix B: Troubleshooting Guide

Issue: Model Router Not Initializing

Symptoms:

• modelRouter is undefined in agents
• Error: "ModelRouter not initialized"

Diagnosis:

# Check feature flag
kubectl exec -it deploy/aqe-fleet-0 -- \
  env | grep FEATURE_MULTI_MODEL_ROUTER

# Check config
kubectl exec -it deploy/aqe-fleet-0 -- \
  cat /config/fleet.yaml | grep -A 5 "features:"

Resolution:

1. Verify feature flag is true in environment or config
2. Check for initialization errors in logs
3. Verify model configurations are valid
4. Restart pods if needed

---

Issue: Streaming Timeouts

Symptoms:

• Frequent "Stream timeout" errors
• Tasks fallback to synchronous mode

Diagnosis:

# Check timeout configuration
kubectl exec -it deploy/aqe-fleet-0 -- \
  cat /config/fleet.yaml | grep -A 10 "streaming:"

# Check network latency to model API
kubectl exec -it deploy/aqe-fleet-0 -- \
  curl -w "@curl-format.txt" https://api.anthropic.com/health

Resolution:

1. Increase timeoutMs in streaming config
2. Check network connectivity to model API
3. Verify API key is valid
4. Review backoff/retry configuration

---

Document Version

Version: 1.0 Date: 2025-10-16 Author: System Architecture Team Status: Ready for Implementation