Microservices Patterns

Microservices Patterns

Design microservices architectures with service boundaries, event-driven communication, and resilience patterns.

Service Decomposition Strategies

By Business Capability

• Organize services around business functions
• Each service owns its domain
• Example: OrderService, PaymentService, InventoryService

By Subdomain (DDD)

• Core domain, supporting subdomains
• Bounded contexts map to services
• Clear ownership and responsibility

Strangler Fig Pattern

• Gradually extract from monolith
• New functionality as microservices
• Proxy routes to old/new systems

Communication Patterns

Synchronous (Request/Response)

from tenacity import retry, stop_after_attempt, wait_exponential

class ServiceClient:
    def __init__(self, base_url: str):
        self.base_url = base_url
        self.client = httpx.AsyncClient(timeout=5.0)

    @retry(stop=stop_after_attempt(3), wait=wait_exponential(min=2, max=10))
    async def get(self, path: str, **kwargs):
        response = await self.client.get(f"{self.base_url}{path}", **kwargs)
        response.raise_for_status()
        return response.json()

Asynchronous (Events/Messages)

from aiokafka import AIOKafkaProducer

class EventBus:
    async def publish(self, event: DomainEvent):
        await self.producer.send_and_wait(
            event.event_type,
            value=asdict(event),
            key=event.aggregate_id.encode()
        )

Resilience Patterns

Circuit Breaker

class CircuitBreaker:
    def __init__(self, failure_threshold=5, recovery_timeout=30):
        self.failure_threshold = failure_threshold
        self.recovery_timeout = recovery_timeout
        self.state = CircuitState.CLOSED

    async def call(self, func, *args, **kwargs):
        if self.state == CircuitState.OPEN:
            if self._should_attempt_reset():
                self.state = CircuitState.HALF_OPEN
            else:
                raise CircuitBreakerOpenError()

        try:
            result = await func(*args, **kwargs)
            self._on_success()
            return result
        except Exception:
            self._on_failure()
            raise

Bulkhead Pattern

• Isolate resources per service
• Limit impact of failures
• Prevent cascade failures

API Gateway Pattern

class APIGateway:
    @circuit(failure_threshold=5, recovery_timeout=30)
    async def call_service(self, service_url: str, path: str, **kwargs):
        response = await self.http_client.request("GET", f"{service_url}{path}", **kwargs)
        response.raise_for_status()
        return response.json()

    async def aggregate(self, order_id: str) -> dict:
        # Parallel requests to multiple services
        order, payment, inventory = await asyncio.gather(
            self.call_order_service(f"/orders/{order_id}"),
            self.call_payment_service(f"/payments/order/{order_id}"),
            self.call_inventory_service(f"/reservations/order/{order_id}"),
            return_exceptions=True
        )
        return {"order": order, "payment": payment, "inventory": inventory}

Data Management

Database Per Service

• Each service owns its data
• No shared databases
• Loose coupling

Saga Pattern for Distributed Transactions

• See saga-orchestration skill for details

Best Practices

1. Service Boundaries: Align with business capabilities 2. Database Per Service: No shared databases 3. API Contracts: Versioned, backward compatible 4. Async When Possible: Events over direct calls 5. Circuit Breakers: Fail fast on service failures 6. Distributed Tracing: Track requests across services 7. Health Checks: Liveness and readiness probes

Common Pitfalls

• Distributed Monolith: Tightly coupled services
• Chatty Services: Too many inter-service calls
• No Circuit Breakers: Cascade failures
• Synchronous Everything: Tight coupling
• Ignoring Network Failures: Assuming reliable network