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retellai-architecture-variants【设计与创意】Choose and implement Retell AI validated architecture blueprints for different scales. Use when designing new Retell AI integrations, choosing between monolith/service/microservice architectures, or planning migration paths for Retell AI applications. Trigger with phrases like "retellai architecture", "retellai blueprint", "how to structure retellai"…
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Three validated architecture blueprints for Retell AI integrations.
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
// 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 });
}
});
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
// Service layer abstraction
class Retell AIService {
constructor(
private client: RetellAIClient,
private cache: CacheService,
private queue: QueueService
) {}
async createResource(data: CreateInput): Promise<Resource> {
// 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;
}
}
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/
// 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<void> {
// Saga orchestration
await this.sagaOrchestrator.continue(event);
}
}
| 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 |
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
Use the decision matrix to identify appropriate variant.
Select Monolith, Service Layer, or Microservice based on needs.
Set up project layout following the chosen blueprint.
Document upgrade path for future scaling.
| 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 |
# Count team size and DAU to select variant
echo "Team: $(git log --format='%ae' | sort -u | wc -l) developers"
echo "DAU: Check analytics dashboard"
For common anti-patterns, see retellai-known-pitfalls.