Retell AI Migration Deep Dive
retellai-migration-deep-dive
Execute Retell AI major re-architecture and migration strategies with strangler fig pattern. Use when migrating to or from Retell AI, performing major version upgrades, or re-platforming existing integrations to Retell AI. Trigger with phrases like "migrate retellai", "retellai migration", "switc...
SKILL.md
Full skill instructions
Retell AI Migration Deep Dive
Overview
Comprehensive guide for migrating to or from Retell AI, or major version upgrades.
Prerequisites
- Current system documentation
- Retell AI SDK installed
- Feature flag infrastructure
- Rollback strategy tested
Migration Types
| Type | Complexity | Duration | Risk |
|---|---|---|---|
| Fresh install | Low | Days | Low |
| From competitor | Medium | Weeks | Medium |
| Major version | Medium | Weeks | Medium |
| Full replatform | High | Months | High |
Pre-Migration Assessment
Step 1: Current State Analysis
# Document current implementation
find . -name "*.ts" -o -name "*.py" | xargs grep -l "retellai" > retellai-files.txt
# Count integration points
wc -l retellai-files.txt
# Identify dependencies
npm list | grep retellai
pip freeze | grep retellai
Step 2: Data Inventory
interface MigrationInventory {
dataTypes: string[];
recordCounts: Record<string, number>;
dependencies: string[];
integrationPoints: string[];
customizations: string[];
}
async function assessRetell AIMigration(): Promise<MigrationInventory> {
return {
dataTypes: await getDataTypes(),
recordCounts: await getRecordCounts(),
dependencies: await analyzeDependencies(),
integrationPoints: await findIntegrationPoints(),
customizations: await documentCustomizations(),
};
}
Migration Strategy: Strangler Fig Pattern
Phase 1: Parallel Run
┌─────────────┐ ┌─────────────┐
│ Old │ │ New │
│ System │ ──▶ │ Retell AI │
│ (100%) │ │ (0%) │
└─────────────┘ └─────────────┘
Phase 2: Gradual Shift
┌─────────────┐ ┌─────────────┐
│ Old │ │ New │
│ (50%) │ ──▶ │ (50%) │
└─────────────┘ └─────────────┘
Phase 3: Complete
┌─────────────┐ ┌─────────────┐
│ Old │ │ New │
│ (0%) │ ──▶ │ (100%) │
└─────────────┘ └─────────────┘
Implementation Plan
Phase 1: Setup (Week 1-2)
# Install Retell AI SDK
npm install @retellai/sdk
# Configure credentials
cp .env.example .env.retellai
# Edit with new credentials
# Verify connectivity
node -e "require('@retellai/sdk').ping()"
Phase 2: Adapter Layer (Week 3-4)
// src/adapters/retellai.ts
interface ServiceAdapter {
create(data: CreateInput): Promise<Resource>;
read(id: string): Promise<Resource>;
update(id: string, data: UpdateInput): Promise<Resource>;
delete(id: string): Promise<void>;
}
class Retell AIAdapter implements ServiceAdapter {
async create(data: CreateInput): Promise<Resource> {
const retellaiData = this.transform(data);
return retellaiClient.create(retellaiData);
}
private transform(data: CreateInput): Retell AIInput {
// Map from old format to Retell AI format
}
}
Phase 3: Data Migration (Week 5-6)
async function migrateRetell AIData(): Promise<MigrationResult> {
const batchSize = 100;
let processed = 0;
let errors: MigrationError[] = [];
for await (const batch of oldSystem.iterateBatches(batchSize)) {
try {
const transformed = batch.map(transform);
await retellaiClient.batchCreate(transformed);
processed += batch.length;
} catch (error) {
errors.push({ batch, error });
}
// Progress update
console.log(`Migrated ${processed} records`);
}
return { processed, errors };
}
Phase 4: Traffic Shift (Week 7-8)
// Feature flag controlled traffic split
function getServiceAdapter(): ServiceAdapter {
const retellaiPercentage = getFeatureFlag('retellai_migration_percentage');
if (Math.random() * 100 < retellaiPercentage) {
return new Retell AIAdapter();
}
return new LegacyAdapter();
}
Rollback Plan
# Immediate rollback
kubectl set env deployment/app RETELLAI_ENABLED=false
kubectl rollout restart deployment/app
# Data rollback (if needed)
./scripts/restore-from-backup.sh --date YYYY-MM-DD
# Verify rollback
curl https://app.yourcompany.com/health | jq '.services.retellai'
Post-Migration Validation
async function validateRetell AIMigration(): Promise<ValidationReport> {
const checks = [
{ name: 'Data count match', fn: checkDataCounts },
{ name: 'API functionality', fn: checkApiFunctionality },
{ name: 'Performance baseline', fn: checkPerformance },
{ name: 'Error rates', fn: checkErrorRates },
];
const results = await Promise.all(
checks.map(async c => ({ name: c.name, result: await c.fn() }))
);
return { checks: results, passed: results.every(r => r.result.success) };
}
Instructions
Step 1: Assess Current State
Document existing implementation and data inventory.
Step 2: Build Adapter Layer
Create abstraction layer for gradual migration.
Step 3: Migrate Data
Run batch data migration with error handling.
Step 4: Shift Traffic
Gradually route traffic to new Retell AI integration.
Output
- Migration assessment complete
- Adapter layer implemented
- Data migrated successfully
- Traffic fully shifted to Retell AI
Error Handling
| Issue | Cause | Solution |
|---|---|---|
| Data mismatch | Transform errors | Validate transform logic |
| Performance drop | No caching | Add caching layer |
| Rollback triggered | Errors spiked | Reduce traffic percentage |
| Validation failed | Missing data | Check batch processing |
Examples
Quick Migration Status
const status = await validateRetell AIMigration();
console.log(`Migration ${status.passed ? 'PASSED' : 'FAILED'}`);
status.checks.forEach(c => console.log(` ${c.name}: ${c.result.success}`));
Resources
Flagship+ Skills
For advanced troubleshooting, see retellai-advanced-troubleshooting.
