Microservices

# BAD: Shared User model across services
OrderService   → reads User.loyaltyPoints
PaymentService → reads User.billingAddress
EmailService   → reads User.email

# GOOD: Each service owns what it needs
OrderService   → owns OrderCustomer { id, name, loyaltyPoints }
PaymentService → owns PaymentProfile { userId, billingAddress, paymentMethods }
EmailService   → owns ContactRecord { userId, email, preferences }

1. Route all traffic through a facade (nginx / API gateway)
2. Identify one vertical slice (e.g., /api/payments/*)
3. Implement that slice as a new service
4. Re-route the facade to the new service
5. Delete the monolith code for that slice
6. Repeat — monolith shrinks, services grow

# Python — requests with retry and timeout
import httpx
from tenacity import retry, stop_after_attempt, wait_exponential

@retry(stop=stop_after_attempt(3), wait=wait_exponential(multiplier=1, min=1, max=10))
def get_user(user_id: str) -> dict:
    response = httpx.get(
        f"http://user-service/users/{user_id}",
        timeout=2.0,  # always set a timeout
    )
    response.raise_for_status()
    return response.json()["data"]

// TypeScript — fetch with timeout and retry
async function getUser(userId: string): Promise<User> {
  const controller = new AbortController();
  const timeout = setTimeout(() => controller.abort(), 2000);
  try {
    const res = await fetch(`http://user-service/users/${userId}`, {
      signal: controller.signal,
    });
    if (!res.ok) throw new Error(`upstream error: ${res.status}`);
    return (await res.json()).data;
  } finally {
    clearTimeout(timeout);
  }
}

// Go — http client with timeout
func (c *UserClient) GetUser(ctx context.Context, userID string) (*User, error) {
    ctx, cancel := context.WithTimeout(ctx, 2*time.Second)
    defer cancel()

    req, _ := http.NewRequestWithContext(ctx, http.MethodGet,
        fmt.Sprintf("http://user-service/users/%s", userID), nil)
    resp, err := c.http.Do(req)
    if err != nil {
        return nil, fmt.Errorf("user-service: %w", err)
    }
    defer resp.Body.Close()
    // decode...
}

// order.proto
service OrderService {
  rpc GetOrder (GetOrderRequest) returns (Order);
  rpc CreateOrder (CreateOrderRequest) returns (Order);
  rpc ListOrders (ListOrdersRequest) returns (stream Order);  // server streaming
}

message GetOrderRequest { string order_id = 1; }
message Order {
  string id = 1;
  string customer_id = 2;
  OrderStatus status = 3;
  repeated OrderItem items = 4;
}

# Python — publishing an event (Kafka)
from confluent_kafka import Producer
import json

producer = Producer({"bootstrap.servers": "kafka:9092"})

def publish_order_placed(order: Order):
    event = {
        "event_type": "order.placed",
        "order_id": order.id,
        "customer_id": order.customer_id,
        "total": str(order.total),
        "occurred_at": order.created_at.isoformat(),
    }
    producer.produce(
        topic="orders",
        key=order.id,
        value=json.dumps(event).encode(),
    )
    producer.flush()

// TypeScript — consuming events (Kafka / KafkaJS)
const consumer = kafka.consumer({ groupId: "notification-service" });
await consumer.subscribe({ topic: "orders", fromBeginning: false });
await consumer.run({
  eachMessage: async ({ message }) => {
    const event = JSON.parse(message.value!.toString());
    if (event.event_type === "order.placed") {
      await notifyCustomer(event.customer_id, event.order_id);
    }
  },
});

# Python — using pybreaker
import pybreaker

breaker = pybreaker.CircuitBreaker(fail_max=5, reset_timeout=30)

@breaker
def call_inventory_service(product_id: str) -> int:
    return inventory_client.get_stock(product_id)

# States: CLOSED (normal) → OPEN (failing, fast-fail) → HALF-OPEN (probing)

// Go — using gobreaker
import "github.com/sony/gobreaker"

cb := gobreaker.NewCircuitBreaker(gobreaker.Settings{
    Name:        "inventory-service",
    MaxRequests: 3,                // requests allowed in half-open
    Interval:    10 * time.Second, // rolling window
    Timeout:     30 * time.Second, // how long to stay OPEN
    ReadyToTrip: func(counts gobreaker.Counts) bool {
        return counts.ConsecutiveFailures > 5
    },
})

stock, err := cb.Execute(func() (interface{}, error) {
    return inventoryClient.GetStock(ctx, productID)
})

# Isolate thread pools per downstream dependency
from concurrent.futures import ThreadPoolExecutor

_inventory_pool = ThreadPoolExecutor(max_workers=10)  # capped per service
_payment_pool   = ThreadPoolExecutor(max_workers=5)

def get_stock(product_id: str):
    future = _inventory_pool.submit(inventory_client.get_stock, product_id)
    return future.result(timeout=2)

# GOOD: exponential backoff with jitter
attempt 1: wait 1s ± 0.5s
attempt 2: wait 2s ± 1s
attempt 3: wait 4s ± 2s
→ stop after 3 attempts, raise to caller

# BAD: retry storm
for i in range(10):
    try: call_service()
    except: continue  # hammers a degraded service

# BAD: shared database
OrderService   → SELECT * FROM payments.transactions WHERE order_id = ?
PaymentService → SELECT * FROM orders.orders WHERE user_id = ?

# GOOD: service-owned databases, expose data via API or events
OrderService   → owns orders_db (Postgres)
PaymentService → owns payments_db (Postgres)
InventoryService → owns inventory_db (Redis + Postgres)

# Choreography saga — order placement
# 1. OrderService publishes order.created
# 2. PaymentService listens → charges card → publishes payment.succeeded or payment.failed
# 3. InventoryService listens to payment.succeeded → reserves stock → publishes stock.reserved
# 4. OrderService listens to stock.reserved → marks order CONFIRMED
# 5. On any failure: compensating events roll back upstream steps

# Compensating transaction example
def on_payment_failed(event):
    order_service.cancel_order(event["order_id"])   # compensation
    notification_service.notify_customer(event["customer_id"], "payment_failed")

Write path:  POST /orders        → OrderCommandHandler → orders_db (normalized)
                                 → publishes order.placed event

Read path:   GET /orders/:id     → OrderQueryHandler   → orders_read_db (denormalized view)
             GET /orders?user=X  → OrderQueryHandler   → orders_read_db (pre-joined)

Read model updated by: consuming order.placed / order.updated events

Client → API Gateway → [UserService, OrderService, ProductService]

Gateway handles:
  - Authentication (JWT verification)
  - Rate limiting per client / API key
  - Request routing / URL rewriting
  - SSL termination
  - Logging and distributed trace injection (X-Request-ID, traceparent)
  - Response aggregation (optional)

Mobile App   → Mobile BFF   → [fine-grained internal APIs]
Web App      → Web BFF      → [fine-grained internal APIs]
Partner API  → Partner BFF  → [fine-grained internal APIs]

# Each BFF is thin: aggregate, reshape, and auth-scope data for its client
# BAD: one general-purpose gateway trying to serve all clients equally

# payment-service resolves to:
# http://payment-service.payments-ns.svc.cluster.local:8080
# within the same namespace: http://payment-service:8080

# Propagate trace context across services (OpenTelemetry)
from opentelemetry import trace
from opentelemetry.propagate import inject, extract

tracer = trace.get_tracer("order-service")

def place_order(order_data: dict, headers: dict):
    ctx = extract(headers)  # pull trace context from incoming request
    with tracer.start_as_current_span("place_order", context=ctx) as span:
        span.set_attribute("order.customer_id", order_data["customer_id"])
        outbound_headers = {}
        inject(outbound_headers)  # inject into outbound calls
        payment_client.charge(order_data, headers=outbound_headers)