microservices-patterns

name	microservices-patterns
description	Design microservices architectures with service boundaries, event-driven communication, and resilience patterns. Use when building distributed systems, decomposing monoliths, or implementing microservices.
license	MIT

Microservices Patterns

Master microservices architecture patterns including service boundaries, inter-service communication, data management, and resilience patterns for building distributed systems.

When to Use This Skill

• Decomposing monoliths into microservices
• Designing service boundaries and contracts
• Implementing inter-service communication
• Managing distributed data and transactions
• Building resilient distributed systems
• Implementing service discovery and load balancing
• Designing event-driven architectures

Core Concepts

1. 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

2. Communication Patterns

Synchronous (Request/Response)

• REST APIs
• gRPC
• GraphQL

Asynchronous (Events/Messages)

• Event streaming (Kafka)
• Message queues (RabbitMQ, SQS)
• Pub/Sub patterns

3. Data Management

Database Per Service

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

Saga Pattern

• Distributed transactions
• Compensating actions
• Eventual consistency

4. Resilience Patterns

Circuit Breaker

• Fail fast on repeated errors
• Prevent cascade failures

Retry with Backoff

• Transient fault handling
• Exponential backoff

Bulkhead

• Isolate resources
• Limit impact of failures

Service Decomposition Patterns

Pattern 1: By Business Capability

# Order Service
class OrderService:
    async def create_order(self, order_data: dict) -> Order:
        order = Order.create(order_data)
        await self.event_bus.publish(
            OrderCreatedEvent(order_id=order.id, customer_id=order.customer_id)
        )
        return order

# Payment Service (separate service)
class PaymentService:
    async def process_payment(self, payment_request: PaymentRequest) -> PaymentResult:
        result = await self.payment_gateway.charge(
            amount=payment_request.amount,
            customer=payment_request.customer_id
        )
        if result.success:
            await self.event_bus.publish(
                PaymentCompletedEvent(order_id=payment_request.order_id)
            )
        return result

# Inventory Service (separate service)
class InventoryService:
    async def reserve_items(self, order_id: str, items: List[OrderItem]) -> ReservationResult:
        for item in items:
            available = await self.inventory_repo.get_available(item.product_id)
            if available < item.quantity:
                return ReservationResult(success=False, error=)

        reservation =  .create_reservation(order_id, items)
         .event_bus.publish(InventoryReservedEvent(order_id=order_id))
         ReservationResult(success=, reservation=reservation)

Pattern 2: API Gateway

from fastapi import FastAPI
import httpx

class APIGateway:
    """Central entry point for all client requests."""

    def __init__(self):
        self.order_service_url = "http://order-service:8000"
        self.payment_service_url = "http://payment-service:8001"
        self.http_client = httpx.AsyncClient(timeout=5.0)

    @circuit(failure_threshold=5, recovery_timeout=30)
    async def call_order_service(self, path: str, method: str = "GET", **kwargs):
        """Call order service with circuit breaker."""
        response = await self.http_client.request(
            method, f"{self.order_service_url}{path}", **kwargs
        )
        response.raise_for_status()
        return response.json()

    async def create_order_aggregate(self, order_id: str) -> dict:
        """Aggregate data from multiple services."""
        order, payment, inventory = await asyncio.gather(
            self.call_order_service(f"/orders/{order_id}"),
            self.call_payment_service(),
            .call_inventory_service(),
            return_exceptions=
        )

        result = {: order}
          (payment, Exception):
            result[] = payment
          (inventory, Exception):
            result[] = inventory
         result

Communication Patterns

Pattern 1: Synchronous REST Communication

import httpx
from tenacity import retry, stop_after_attempt, wait_exponential

class ServiceClient:
    """HTTP client with retries and timeout."""

    def __init__(self, base_url: str):
        self.base_url = base_url
        self.client = httpx.AsyncClient(timeout=httpx.Timeout(5.0, connect=2.0))

    @retry(stop=stop_after_attempt(3), wait=wait_exponential(multiplier=1, min=2, max=10))
    async def get(self, path: str, **kwargs):
        """GET with automatic retries."""
        response = await self.client.get(f"{self.base_url}{path}", **kwargs)
        response.raise_for_status()
        return response.json()

payment_client = ServiceClient("http://payment-service:8001")
result = await payment_client.get("/payments/123")

Pattern 2: Asynchronous Event-Driven

from aiokafka import AIOKafkaProducer, AIOKafkaConsumer
import json

class EventBus:
    """Event publishing and subscription."""

    async def publish(self, event: DomainEvent):
        """Publish event to Kafka topic."""
        await self.producer.send_and_wait(
            event.event_type,
            value=asdict(event),
            key=event.aggregate_id.encode()
        )

    async def subscribe(self, topic: str, handler: callable):
        """Subscribe to events."""
        consumer = AIOKafkaConsumer(topic, bootstrap_servers=self.bootstrap_servers)
        await consumer.start()
        async for message in consumer:
            await handler(message.value)

# Order Service publishes
await event_bus.publish(OrderCreatedEvent(order_id=order.id))

# Inventory Service subscribes
async def handle_order_created(event_data: dict):
    await reserve_inventory(event_data["order_id"], event_data["items"])

Pattern 3: Saga Pattern (Distributed Transactions)

class OrderFulfillmentSaga:
    """Orchestrated saga for order fulfillment."""

    def __init__(self):
        self.steps = [
            SagaStep("create_order", self.create_order, self.cancel_order),
            SagaStep("reserve_inventory", self.reserve_inventory, self.release_inventory),
            SagaStep("process_payment", self.process_payment, self.refund_payment),
            SagaStep("confirm_order", self.confirm_order, self.cancel_order_confirmation)
        ]

    async def execute(self, order_data: dict) -> SagaResult:
        completed_steps = []
        context = {"order_data": order_data}

        try:
            for step in self.steps:
                result = await step.action(context)
                if not result.success:
                    await self.compensate(completed_steps, context)
                    return SagaResult(status=SagaStatus.FAILED, error=result.error)

                completed_steps.append(step)
                context.update(result.data)

            return SagaResult(status=SagaStatus.COMPLETED, data=context)
        except Exception as e:
            await self.compensate(completed_steps, context)
             SagaResult(status=SagaStatus.FAILED, error=(e))

      ():
        
         step  (completed_steps):
             step.compensation(context)

Resilience Patterns

Circuit Breaker Pattern

from enum import Enum
from datetime import datetime, timedelta

class CircuitState(Enum):
    CLOSED = "closed"   # Normal operation
    OPEN = "open"       # Failing, reject requests
    HALF_OPEN = "half_open"  # Testing recovery

class CircuitBreaker:
    def __init__(self, failure_threshold: int = 5, recovery_timeout: int = 30):
        self.failure_threshold = failure_threshold
        self.recovery_timeout = recovery_timeout
        self.failure_count = 0
        self.state = CircuitState.CLOSED
        self.opened_at = None

    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("Circuit breaker is open")

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

     ():
        .failure_count = 
         .state == CircuitState.HALF_OPEN:
            .state = CircuitState.CLOSED

     ():
        .failure_count += 
         .failure_count >= .failure_threshold:
            .state = CircuitState.OPEN
            .opened_at = datetime.now()

breaker = CircuitBreaker(failure_threshold=, recovery_timeout=)
result =  breaker.call(payment_client.process_payment, payment_data)

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. Service Registry: Dynamic service discovery
8. Health Checks: Liveness and readiness probes

Common Pitfalls

• Distributed Monolith: Tightly coupled services
• Chatty Services: Too many inter-service calls
• Shared Databases: Tight coupling through data
• No Circuit Breakers: Cascade failures
• Synchronous Everything: Tight coupling, poor resilience
• Premature Microservices: Starting with microservices
• Ignoring Network Failures: Assuming reliable network
• No Compensation Logic: Can't undo failed transactions