retellai-architecture-variants

# Retell AI Architecture Variants ## Overview Three validated architecture blueprints for Retell AI integrations. ## Prerequisites - Understanding of team size and DAU requirements - Knowledge of deployment infrastructure - Clear SLA requirements - Growth projections available ## Variant A: Monolith (Simple) **Best for:** MVPs, small teams, < 10K daily active users ``` my-app/ ├── src/ │ ├── retellai/ │ │ ├── client.ts # Singleton client │ │ ├── types.ts # Types │ │ └── middleware.ts # Express middleware │ ├── routes/ │ │ └── api/ │ │ └── retellai.ts # API routes │ └── index.ts ├── tests/ │ └── retellai.test.ts └── package.json ``` ### Key Characteristics - Single deployment unit - Synchronous Retell AI calls in request path - In-memory caching - Simple error handling ### Code Pattern ```typescript // Direct integration in route handler app.post('/api/create', async (req, res) => { try { const result = await retellaiClient.create(req.body); res.json(result); } catch (error) { res.status(500).json({ error: error.message }); } }); ``` --- ## Variant B: Service Layer (Moderate) **Best for:** Growing startups, 10K-100K DAU, multiple integrations ``` my-app/ ├── src/ │ ├── services/ │ │ ├── retellai/ │ │ │ ├── client.ts # Client wrapper │ │ │ ├── service.ts # Business logic │ │ │ ├── repository.ts # Data access │ │ │ └── types.ts │ │ └── index.ts # Service exports │ ├── controllers/ │ │ └── retellai.ts │ ├── routes/ │ ├── middleware/ │ ├── queue/ │ │ └── retellai-processor.ts # Async processing │ └── index.ts ├── config/ │ └── retellai/ └── package.json ``` ### Key Characteristics - Separation of concerns - Background job processing - Redis caching - Circuit breaker pattern - Structured error handling ### Code Pattern ```typescript // Service layer abstraction class Retell AIService { constructor( private client: RetellAIClient, private cache: CacheService, private queue: QueueService ) {} async createResource(data: CreateInput): Promise { // Business logic before API call const validated = this.validate(data); // Check cache const cached = await this.cache.get(cacheKey); if (cached) return cached; // API call with retry const result = await this.withRetry(() => this.client.create(validated) ); // Cache result await this.cache.set(cacheKey, result, 300); // Async follow-up await this.queue.enqueue('retellai.post-create', result); return result; } } ``` --- ## Variant C: Microservice (Complex) **Best for:** Enterprise, 100K+ DAU, strict SLAs ``` retellai-service/ # Dedicated microservice ├── src/ │ ├── api/ │ │ ├── grpc/ │ │ │ └── retellai.proto │ │ └── rest/ │ │ └── routes.ts │ ├── domain/ │ │ ├── entities/ │ │ ├── events/ │ │ └── services/ │ ├── infrastructure/ │ │ ├── retellai/ │ │ │ ├── client.ts │ │ │ ├── mapper.ts │ │ │ └── circuit-breaker.ts │ │ ├── cache/ │ │ ├── queue/ │ │ └── database/ │ └── index.ts ├── config/ ├── k8s/ │ ├── deployment.yaml │ ├── service.yaml │ └── hpa.yaml └── package.json other-services/ ├── order-service/ # Calls retellai-service ├── payment-service/ └── notification-service/ ``` ### Key Characteristics - Dedicated Retell AI microservice - gRPC for internal communication - Event-driven architecture - Database per service - Kubernetes autoscaling - Distributed tracing - Circuit breaker per service ### Code Pattern ```typescript // Event-driven with domain isolation class Retell AIAggregate { private events: DomainEvent[] = []; process(command: Retell AICommand): void { // Domain logic const result = this.execute(command); // Emit domain event this.events.push(new Retell AIProcessedEvent(result)); } getUncommittedEvents(): DomainEvent[] { return [...this.events]; } } // Event handler @EventHandler(Retell AIProcessedEvent) class Retell AIEventHandler { async handle(event: Retell AIProcessedEvent): Promise { // Saga orchestration await this.sagaOrchestrator.continue(event); } } ``` --- ## Decision Matrix | Factor | Monolith | Service Layer | Microservice | |--------|----------|---------------|--------------| | Team Size | 1-5 | 5-20 | 20+ | | DAU | < 10K | 10K-100K | 100K+ | | Deployment Frequency | Weekly | Daily | Continuous | | Failure Isolation | None | Partial | Full | | Operational Complexity | Low | Medium | High | | Time to Market | Fastest | Moderate | Slowest | ## Migration Path ``` Monolith → Service Layer: 1. Extract Retell AI code to service/ 2. Add caching layer 3. Add background processing Service Layer → Microservice: 1. Create dedicated retellai-service repo 2. Define gRPC contract 3. Add event bus 4. Deploy to Kubernetes 5. Migrate traffic gradually ``` ## Instructions ### Step 1: Assess Requirements Use the decision matrix to identify appropriate variant. ### Step 2: Choose Architecture Select Monolith, Service Layer, or Microservice based on needs. ### Step 3: Implement Structure Set up project layout following the chosen blueprint. ### Step 4: Plan Migration Path Document upgrade path for future scaling. ## Output - Architecture variant selected - Project structure implemented - Migration path documented - Appropriate patterns applied ## Error Handling | Issue | Cause | Solution | |-------|-------|----------| | Over-engineering | Wrong variant choice | Start simpler | | Performance issues | Wrong layer | Add caching/async | | Team friction | Complex architecture | Simplify or train | | Deployment complexity | Microservice overhead | Consider service layer | ## Examples ### Quick Variant Check ```bash # Count team size and DAU to select variant echo "Team: $(git log --format='%ae' | sort -u | wc -l) developers" echo "DAU: Check analytics dashboard" ``` ## Resources - [Monolith First](https://martinfowler.com/bliki/MonolithFirst.html) - [Microservices Guide](https://martinfowler.com/microservices/) - [Retell AI Architecture Guide](https://docs.retellai.com/architecture) ## Next Steps For common anti-patterns, see `retellai-known-pitfalls`.