microservices-patterns

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

# E-commerce example

# Order Service
class OrderService:
    """Handles order lifecycle."""

    async def create_order(self, order_data: dict) -> Order:
        order = Order.create(order_data)

        # Publish event for other services
        await self.event_bus.publish(
            OrderCreatedEvent(
                order_id=order.id,
                customer_id=order.customer_id,
                items=order.items,
                total=order.total
            )
        )

        return order

# Payment Service (separate service)
class PaymentService:
    """Handles payment processing."""

    async def process_payment(self, payment_request: PaymentRequest) -> PaymentResult:
        # Process payment
        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,
                    transaction_id=result.transaction_id
                )
            )

        return result

# Inventory Service (separate service)
class InventoryService:
    """Handles inventory management."""

    async def reserve_items(self, order_id: str, items: List[OrderItem]) -> ReservationResult:
        # Check availability
        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 for {item.product_id}"
                )

        # Reserve items
        reservation = await self.create_reservation(order_id, items)

        await self.event_bus.publish(
            InventoryReservedEvent(
                order_id=order_id,
                reservation_id=reservation.id
            )
        )

        return ReservationResult(success=True, reservation=reservation)

Pattern 2: API Gateway

from fastapi import FastAPI, HTTPException, Depends
import httpx
from circuitbreaker import circuit

app = FastAPI()

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.inventory_service_url = "http://inventory-service:8002"
        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."""
        # Parallel requests
        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
        )

        # Handle partial failures
        result = {"order": order}
        if not isinstance(payment, Exception):
            result["payment"] = payment
        if not isinstance(inventory, Exception):
            result["inventory"] = inventory

        return result

@app.post("/api/orders")
async def create_order(
    order_data: dict,
    gateway: APIGateway = Depends()
):
    """API Gateway endpoint."""
    try:
        # Route to order service
        order = await gateway.call_order_service(
            "/orders",
            method="POST",
            json=order_data
        )
        return {"order": order}
    except httpx.HTTPError as e:
        raise HTTPException(status_code=503, detail="Order service unavailable")

Communication Patterns

Pattern 1: Synchronous REST Communication

# Service A calls Service B
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),
            limits=httpx.Limits(max_keepalive_connections=20)
        )

    @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()

    async def post(self, path: str, **kwargs):
        """POST request."""
        response = await self.client.post(f"{self.base_url}{path}", **kwargs)
        response.raise_for_status()
        return response.json()

# Usage
payment_client = ServiceClient("http://payment-service:8001")
result = await payment_client.post("/payments", json=payment_data)

Pattern 2: Asynchronous Event-Driven

# Event-driven communication with Kafka
from aiokafka import AIOKafkaProducer, AIOKafkaConsumer
import json
from dataclasses import dataclass, asdict
from datetime import datetime

@dataclass
class DomainEvent:
    event_id: str
    event_type: str
    aggregate_id: str
    occurred_at: datetime
    data: dict

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

    def __init__(self, bootstrap_servers: List[str]):
        self.bootstrap_servers = bootstrap_servers
        self.producer = None

    async def start(self):
        self.producer = AIOKafkaProducer(
            bootstrap_servers=self.bootstrap_servers,
            value_serializer=lambda v: json.dumps(v).encode()
        )
        await self.producer.start()

    async def publish(self, event: DomainEvent):
        """Publish event to Kafka topic."""
        topic = event.event_type
        await self.producer.send_and_wait(
            topic,
            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,
            value_deserializer=lambda v: json.loads(v.decode()),
            group_id="my-service"
        )
        await consumer.start()

        try:
            async for message in consumer:
                event_data = message.value
                await handler(event_data)
        finally:
            await consumer.stop()

# Order Service publishes event
async def create_order(order_data: dict):
    order = await save_order(order_data)

    event = DomainEvent(
        event_id=str(uuid.uuid4()),
        event_type="OrderCreated",
        aggregate_id=order.id,
        occurred_at=datetime.now(),
        data={
            "order_id": order.id,
            "customer_id": order.customer_id,
            "total": order.total
        }
    )

    await event_bus.publish(event)

# Inventory Service listens for OrderCreated
async def handle_order_created(event_data: dict):
    """React to order creation."""
    order_id = event_data["data"]["order_id"]
    items = event_data["data"]["items"]

    # Reserve inventory
    await reserve_inventory(order_id, items)

Pattern 3: Saga Pattern (Distributed Transactions)

# Saga orchestration for order fulfillment
from enum import Enum
from typing import List, Callable

class SagaStep:
    """Single step in saga."""

    def __init__(
        self,
        name: str,
        action: Callable,
        compensation: Callable
    ):
        self.name = name
        self.action = action
        self.compensation = compensation

class SagaStatus(Enum):
    PENDING = "pending"
    COMPLETED = "

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