Skip to content

Build Worker Environments with SQS

This tutorial introduces Elastic Beanstalk worker environments for asynchronous processing. It follows AWS guidance for queue-driven processing and scheduled tasks with cron.yaml.

Prerequisites

  • Existing Elastic Beanstalk application.
  • SQS queue access and IAM permissions.
  • Worker tier environment created or planned.
  • Python Flask app that can accept worker POST payloads.

What You'll Build

You will build:

  • A worker-tier Elastic Beanstalk environment.
  • SQS-driven message handling endpoint in Flask.
  • Scheduled task definition with cron.yaml.

Steps

  1. Create or identify worker environment.
eb create "$WORKER_ENV_NAME" --tier worker
  1. Add Flask endpoint for worker message processing.
from flask import Flask, request

application = Flask(__name__)


@application.post("/")
def process_message():
    payload = request.get_json(silent=True) or {}
    # Process payload according to your application contract.
    return {"received": bool(payload)}
  1. Add cron.yaml for scheduled worker tasks.
version: 1
cron:
    - name: nightly-task
      url: "/"
      schedule: "0 2 * * *"
  1. Set environment variables needed by worker logic.
eb setenv WORKER_MODE="enabled" TASK_NAME="nightly-task"
  1. Deploy to worker environment.
eb deploy "$WORKER_ENV_NAME" --staged
  1. Observe queue consumer behavior and event logs.
eb events "$WORKER_ENV_NAME" --follow
eb logs "$WORKER_ENV_NAME" --all

flowchart LR
    A[Producer] --> B[SQS Queue]
    B --> C[EB Worker Daemon]
    C --> D[Flask POST Endpoint]
    E[cron.yaml Schedule] --> C

Verification

Validate worker workflow:

eb status "$WORKER_ENV_NAME"
aws sqs get-queue-attributes --queue-url "$QUEUE_URL" --attribute-names ApproximateNumberOfMessages --region "$REGION"

Expected outcomes:

  • Worker environment reports healthy state.
  • Queue messages are consumed and processed.
  • Scheduled entries from cron.yaml trigger at expected intervals.

See Also

Sources