Using Message Queues

from confluent_kafka import Producer, Consumer

# Producer
producer = Producer({'bootstrap.servers': 'localhost:9092'})
producer.produce('orders', key='order_123', value='{"status": "created"}')
producer.flush()

# Consumer
consumer = Consumer({
    'bootstrap.servers': 'localhost:9092',
    'group.id': 'order-processors',
    'auto.offset.reset': 'earliest'
})
consumer.subscribe(['orders'])

while True:
    msg = consumer.poll(1.0)
    if msg is not None:
        process_order(msg.value())

from celery import Celery

app = Celery('tasks', broker='redis://localhost:6379')

@app.task(bind=True, max_retries=3)
def process_image(self, image_url: str):
    try:
        result = expensive_image_processing(image_url)
        return result
    except RecoverableError as e:
        raise self.retry(exc=e, countdown=60)

import { Queue, Worker } from 'bullmq'

const queue = new Queue('webhooks', {
  connection: { host: 'localhost', port: 6379 }
})

// Enqueue job
await queue.add('send-webhook', {
  url: 'https://example.com/webhook',
  payload: { event: 'order.created' }
})

// Process jobs
const worker = new Worker('webhooks', async job => {
  await fetch(job.data.url, {
    method: 'POST',
    body: JSON.stringify(job.data.payload)
  })
}, { connection: { host: 'localhost', port: 6379 } })

from temporalio import workflow, activity
from datetime import timedelta

@workflow.defn
class OrderSagaWorkflow:
    @workflow.run
    async def run(self, order_id: str) -> str:
        # Step 1: Reserve inventory
        inventory_id = await workflow.execute_activity(
            reserve_inventory,
            order_id,
            start_to_close_timeout=timedelta(seconds=10),
        )

        # Step 2: Charge payment
        payment_id = await workflow.execute_activity(
            charge_payment,
            order_id,
            start_to_close_timeout=timedelta(seconds=30),
        )

        return f"Order {order_id} completed"

{
  "event_type": "order.created.v2",
  "event_id": "uuid-here",
  "timestamp": "2025-12-02T10:00:00Z",
  "version": "2.0",
  "data": {
    "order_id": "ord_123",
    "customer_id": "cus_456"
  },
  "metadata": {
    "producer": "order-service",
    "trace_id": "abc123",
    "correlation_id": "xyz789"
  }
}

@app.task(bind=True, max_retries=3)
def process_order(self, order_id: str):
    try:
        result = perform_processing(order_id)
        return result
    except UnrecoverableError as e:
        send_to_dlq(order_id, str(e))
        raise Reject(e, requeue=False)

@app.post("/process")
async def process_payment(
    payment_data: dict,
    idempotency_key: str = Header(None)
):
    # Check if already processed
    cached_result = redis_client.get(f"idempotency:{idempotency_key}")
    if cached_result:
        return {"status": "already_processed"}

    result = process_payment_logic(payment_data)
    redis_client.setex(f"idempotency:{idempotency_key}", 86400, result)
    return {"status": "processed", "result": result}

# FastAPI endpoint for real-time job status
@app.get("/status/{task_id}")
async def task_status_stream(task_id: str):
    async def event_generator():
        while True:
            task = celery_app.AsyncResult(task_id)

            if task.state == 'PROGRESS':
                yield {"event": "progress", "data": task.info.get('progress', 0)}
            elif task.state == 'SUCCESS':
                yield {"event": "complete", "data": task.result}
                break

            await asyncio.sleep(0.5)

    return EventSourceResponse(event_generator())