Overview Install Files SecuritySummary Design microservices architectures with service boundaries, event-driven communication, and resilience patterns. Use when building distributed systems, decomposing monoliths, or implementing microservices.
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)
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
Distributed transactions
Compensating actions
Eventual consistency
4. Resilience Patterns
Fail fast on repeated errors
Prevent cascade failures
Transient fault handling
Exponential backoff
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=f"Insufficient inventory")
reservation = await self.create_reservation(order_id, items)
await self.event_bus.publish(InventoryReservedEvent(order_id=order_id))
return ReservationResult(success=True, 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(f"/payments/order/{order_id}"),
self.call_inventory_service(f"/reservations/order/{order_id}"),
return_exceptions=True
)
result = {"order": order}
if not isinstance(payment, Exception):
result["payment"] = payment
if not isinstance(inventory, Exception):
result["inventory"] = inventory
return 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)
return SagaResult(status=SagaStatus.FAILED, error=str(e))
async def compensate(self, completed_steps: List[SagaStep], context: dict):
"""Execute compensating actions in reverse order."""
for step in reversed(completed_steps):
await 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()
return result
except Exception as e:
self._on_failure()
raise
def _on_success(self):
self.failure_count = 0
if self.state == CircuitState.HALF_OPEN:
self.state = CircuitState.CLOSED
def _on_failure(self):
self.failure_count += 1
if self.failure_count >= self.failure_threshold:
self.state = CircuitState.OPEN
self.opened_at = datetime.now()
breaker = CircuitBreaker(failure_threshold=5, recovery_timeout=30)
result = await breaker.call(payment_client.process_payment, payment_data)
Best Practices
Service Boundaries : Align with business capabilities
Database Per Service : No shared databases
API Contracts : Versioned, backward compatible
Async When Possible : Events over direct calls
Circuit Breakers : Fail fast on service failures
Distributed Tracing : Track requests across services
Service Registry : Dynamic service discovery
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