Queue-based Elastic Deployment Quickstart

Welcome! This guide will walk you through setting up and testing YottaLabs' queue-based elastic deployment from start to finish.

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What You'll Accomplish

By the end of this guide, you'll have:

• ✅ Built a queue-compatible worker image

• ✅ Deployed it as a QUEUE elastic deployment

• ✅ Submitted tasks through the Queue API

• ✅ Monitored task status in real-time

• ✅ Retrieved and verified task results

• ✅ Confirmed a complete end-to-end workflow

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Understanding the Queue Model

How It Works

In QUEUE mode, YottaLabs operates with the following flow:

Your Client (curl or Python)
   ↓
   Sends: POST /skywalker/tasks/create
   ↓
Yotta Queue System
   ↓
   Sends: HTTP POST with taskData
   ↓
Your Worker Container (Docker)
   ↓
   Receives: FastAPI endpoint (/run)
   ↓
Your handler(job) function
   ↓
   Returns: result
   ↓
Yotta Queue System
   ↓
   Stores: taskResult for retrieval

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Step 1: Build Your Worker

1.1 Create Your Business Logic

First, let's create handler.py — this is where your core logic lives. This is a super easy example of "echoing" what you prompted back to you.

File: handler.py

def handler(job):
    """
    job format:
    {
        "input": {
            "prompt": "hello"
        }
    }
    """
    job_input = job.get("input", {})
    prompt = job_input.get("prompt", "no prompt provided")
    return f"You said: {prompt}"

1.2 Create the HTTP Server

Now let's wrap your handler with FastAPI so YottaLabs can communicate with it.

File: server.py

from fastapi import FastAPI, Request
from handler import handler

app = FastAPI()

@app.post("/run")
async def run(request: Request):
    job = await request.json()
    result = handler(job)
    return {
        "result": result
    }

What's happening here? YottaLabs sends your task data to the /run endpoint, and your server passes it to your handler function.

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Step 2: Package Everything in Docker

2.1 Define Dependencies

File: requirements.txt

fastapi
uvicorn

2.2 Create Your Dockerfile

File: Dockerfile

FROM python:3.10-slim

WORKDIR /app

COPY requirements.txt .
RUN pip install --no-cache-dir fastapi uvicorn

COPY handler.py server.py ./

EXPOSE 8000

CMD ["uvicorn", "server:app", "--host", "0.0.0.0", "--port", "8000"]

2.3 Build and Test Locally

Build your image:

docker build -t yotta-queue-test .

Run it locally:

docker run -p 8000:8000 yotta-queue-test

Test that it works:

curl -X POST http://localhost:8000/run \
  -H "Content-Type: application/json" \
  -d '{"input":{"prompt":"Hello Queue"}}'

You should see:

{"result":"You said: Hello Queue"}

✅ Great! Your worker is ready for deployment.

Push the image to Dockerhub for future use. Create,for example, yotta-queue-test:latest as my image name and tag.

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Step 3: Deploy to YottaLabs

Create Your Elastic Deployment

Head to the YottaLabs Console and configure:

Setting	Value
Service Mode	QUEUE
Image	yotta-queue-test (or your image name)
Worker Port	8000

Wait for deployment to complete — you'll see Status = RUNNING when ready.

Save Your Endpoint ID

You'll receive an Endpoint ID that looks like this:

Endpoint ID: 407712238196040165

⚠️ Important: Endpoint ID is NOT worker ID shown at the bottom of detail page. Use the code below to get your Endpoint ID list

curl --request GET \
--url 'https://api.yottalabs.ai/openapi/v1/elastic/deploy/list?statusList=INITIALIZING&statusList=RUNNING&statusList=STOPPED' \
--header 'Content-Type: application/json' \
--header 'X-API-Key: <YOUR_API_KEY>'

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Step 5: Full Python Integration Test

For a more robust testing workflow, let's use Python.

Complete Test Script

File: test_remote.py

import time
import uuid
import requests
import json

YOTTA_API_BASE = "https://api.yottalabs.ai"

API_KEY = "<YOUR_API_KEY>"
ENDPOINT_ID = "<YOUR_ENDPOINT_ID>"

WORKER_PORT = 8000
PROCESS_URI = "/run"

TIMEOUT_S = 300
POLL_S = 2


def pretty(x):
    return json.dumps(x, ensure_ascii=False, indent=2)


def create_task(prompt):
    url = f"{YOTTA_API_BASE}/openapi/v1/skywalker/tasks/create"
    headers = {
        "X-API-Key": API_KEY,
        "X-Endpoint-ID": ENDPOINT_ID,
        "Content-Type": "application/json",
    }

    user_task_id = f"task_{time.strftime('%Y%m%d_%H%M%S')}_{uuid.uuid4().hex[:8]}"
    payload = {
        "userTaskId": user_task_id,
        "workerPort": WORKER_PORT,
        "processUri": PROCESS_URI,
        "taskData": {"input": {"prompt": prompt}},
    }

    r = requests.post(url, headers=headers, json=payload, timeout=30)
    r.raise_for_status()
    data = r.json()

    if data.get("code") != 10000:
        raise RuntimeError(pretty(data))

    return user_task_id


def get_task(task_id):
    url = f"{YOTTA_API_BASE}/openapi/v1/skywalker/tasks/{task_id}"
    headers = {
        "X-API-Key": API_KEY,
        "X-Endpoint-ID": ENDPOINT_ID,
    }
    r = requests.get(url, headers=headers, timeout=30)
    r.raise_for_status()
    return r.json()["data"]


def wait_done(task_id):
    start = time.time()
    while True:
        detail = get_task(task_id)
        status = detail["status"]

        if status in ("SUCCESS", "FAILED", 2, 3):
            return detail

        if time.time() - start > TIMEOUT_S:
            raise TimeoutError(pretty(detail))

        time.sleep(POLL_S)


def main():
    prompt = "Hello from Queue!"
    task_id = create_task(prompt)

    print("[create]", task_id)

    detail = wait_done(task_id)
    print(pretty(detail))

    assert detail["status"] == "SUCCESS"
    assert detail["taskResult"]["result"] == f"You said: {prompt}"

    print("\n✅ Queue end-to-end test passed!")


if __name__ == "__main__":
    main()

Run Your Test

python3 test_remote.py

Expected Output

{
  "userTaskId": "task_20260129_125952_a4337d96",
  "status": "SUCCESS",
  "workerUrl": "http://localhost:8000/run",
  "taskData": {
    "input": {
      "prompt": "Hello from Queue!"
    }
  },
  "taskResult": {
    "result": "You said: Hello from Queue!"
  },
  "resultSendStatus": "SUCCESS"
}

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Next Steps

Ready to take things further? Consider exploring:

• Batch Processing — Submit multiple tasks at once

• Monitoring — Add observability and metrics tracking

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Need more help? Check out:

• YottaLabs API Documentation