Microservices Architecture Blueprint for Growth-Stage Startups
Design a pragmatic microservices architecture for startups transitioning from a monolith, with justified technical decisions and incremental migration roadmap.
Define a microservices architecture appropriate to the startup's stage and size — neither prematurely complex nor limiting for growth — with clear technology choices, communication patterns, and migration strategy from the monolith.
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Prompt objective
Define a microservices architecture appropriate to the startup's stage and size — neither prematurely complex nor limiting for growth — with clear technology choices, communication patterns, and migration strategy from the monolith.
Real use case
A B2B logistics startup processes 2 million events per month in their Node.js monolith, but is doubling in size every 6 months. A team of 20 developers suffers from slow deploys (40 minutes), interfering modules, and inability to scale critical parts independently. The CTO wants a migration plan to microservices that doesn't paralyze the product.
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Prompt
Design a Microservices Architecture for:
Company: [NAME]
Product type: [SaaS / Marketplace / API-first / Consumer app]
Current monolith: [STACK — e.g., Node.js + PostgreSQL + Redis]
Current volume: [REQUESTS/DAY or EVENTS/MONTH]
Team: [NUMBER] developers in [NUMBER] squads
Main monolith bottlenecks: [EX: billing module blocks everything, 40 min deploys, can't scale image processing alone]
Current infrastructure: [AWS / GCP / AZURE / BARE METAL]
Current SLA and target: [CURRENT UPTIME → TARGET]
## PART 1 — EVALUATION: MICROSERVICES OR NOT?
**Criteria to justify migration:**
Current monolith score:
- [ ] Team > 15 developers (+ 1 point for microservices)
- [ ] Frequent deploys blocked by unrelated parts (+1)
- [ ] Need to scale components independently (+1)
- [ ] Different squads working on the same files (+1)
- [ ] Modules with different SLAs (e.g., critical payments vs. reports) (+1)
- [ ] Different technologies needed per component (+1)
Result: [X/6] — if < 3, consider a modular monolith first.
**Alternative before microservices: Modular Monolith**
- Separate code into modules with well-defined interfaces
- Much simpler to implement and operate
- Allows extracting services gradually when needed
## PART 2 — BOUNDED CONTEXTS IDENTIFICATION
**Domain-Driven Design (DDD) — domain mapping:**
Based on product type, identify bounded contexts:
| Domain | Responsibility | Data it owns | Volume | Criticality |
|---------|----------------|--------------|--------|-------------|
| [EX: Authentication] | Login, JWT, sessions | users, sessions | Medium | Critical |
| [EX: Orders] | Order CRUD, state | orders, items | High | Critical |
| [EX: Payments] | Process, refund | payments, invoices | Medium | Critical |
| [EX: Notifications] | Email, push, SMS | notifications | High | Low |
| [EX: Analytics] | Events, reports | events, metrics | Very High | Low |
**Golden rule**: each microservice has its own database (no service accesses another service's database directly).
## PART 3 — PROPOSED ARCHITECTURE
**Component diagram (describe in text):**
```
[Clients: Web / Mobile / API Partners]
↓
[API Gateway] — authentication, rate limiting, routing
↙ ↓ ↘
[Auth] [Orders] [Payments] ← Synchronous services (REST/gRPC)
↓
[Message Broker: Kafka/SQS] ← Asynchronous events
↙ ↘
[Notifications] [Analytics] ← Asynchronous services
```
**For each microservice, define:**
### Service: [NAME]
- Single responsibility: [WHAT IT DOES]
- Stack: [LANGUAGE + FRAMEWORK + DATABASE]
- Interface: [REST API / gRPC / event consumer only]
- Events it publishes: [LIST]
- Events it consumes: [LIST]
- SLA: [TARGET UPTIME AND LATENCY]
- Owner team: [SQUAD]
## PART 4 — INTER-SERVICE COMMUNICATION
**Synchronous Communication (REST / gRPC):**
When to use:
- When the client needs an immediate response
- For read operations
- For simple transactional operations
Conventions:
- REST: JSON, versioning via path (`/v1/orders`), correct HTTP status codes
- gRPC: for high-performance internal communication
- Circuit breaker: Resilience4j / opossum to prevent cascade failure
- Retry with exponential backoff: 3 attempts, 1s → 2s → 4s
- Timeout: define timeout per call (e.g., 5 seconds)
**Asynchronous Communication (Kafka / SQS / RabbitMQ):**
When to use:
- When the result doesn't need to be immediate
- For fanout (1 event, N consumers)
- To decouple services with different speeds
- For Open directly in an AI — the text is pre-filled:
How to use this prompt
- 1Replace the key placeholders first: NAME, SaaS / Marketplace / API-first / Consumer app, STACK — e.g., Node.js + PostgreSQL + Redis, REQUESTS/DAY or EVENTS/MONTH.
- 2Replace any bracketed placeholders like [this] with your own context.
- 3Add extra background information when you want more tailored results.
- 4Combine multiple prompts in one conversation when you need a richer output.
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