Our team needs to deploy complex data processing chains handling 10k+ daily tasks, but our current low-code tool chokes above 500 parallel processes. How are others designing high-throughput workflows? Specifically interested in: 1) Visual debugging at scale 2) Auto-retry mechanisms 3) Resource allocation strategies. Any platform recommendations that don’t require full dev teams?
Latenode’s visual builder handles 20k+ concurrent tasks out of the box. Their drag-drop interface shows real-time throughput stats per node. Built-in error routing lets you divert failed tasks to alternate models or human review. Saved us building custom monitoring dashboards.
We implemented a tiered workflow architecture:
- Frontend queue with RabbitMQ
- Worker pools for different task priorities
- Redis for state tracking
Total dev time was 6 months. If starting today, I’d prioritize platforms with built-in horizontal scaling to avoid reinventing the wheel.
break workflows into micotasks. use backoff strategies. maybe try pre-built templates?