Managing Long-Running Tasks

Architecting background task schedulers prevents server connection timeouts when executing heavy compute jobs.

1. Task Queue Architecture

Heavy operations (generating PDF reports, video transcoding) must be handled asynchronously using a queue-worker model.

Client Request ---> API Gateway ---> Enqueue Job (Celery/Redis) ---> Worker Node
                                                                          |
                                                                    DB (Job Status)

Execution Flow

1. Submit Job: Client requests task execution.

2. Immediate Response: Server generates a unique job_id, appends the task to a message broker (RabbitMQ/Redis), and returns a 202 Accepted status with the job ID.

3. Worker Processing: Background workers pull jobs, update status to PROCESSING, run tasks, and update status to COMPLETED.

4. Client Notification: Client tracks status via Polling, WebSockets, or Webhooks.

2. References & Tech Blogs

• Netflix Tech Blog: Conductor - Microservice Task Orchestrator
• Celery: Distributed Task Queue Documentation