Like many developers, we've built our fair share of workflows that export data to 3rd-party services. They always start simple: pull data, hit an API, job done! Then the problems show up. We hit API limits, services go down, and those quick-and-dirty workflows become a major source of headaches.
The knee-jerk reaction is often to add a queue! Sure, it helps for a while. But queues introduce their own complexity: handling failures, managing retries, creating visibility... It's a band-aid, not a cure, and we've been wrestling with this problem for too long!
In this blog post, we'll break down:
- Why queues fall short when building truly resilient integrations
- The core principles behind building scalable, fault-tolerant async workflows
- Practical techniques that go beyond the limitations of queues
If you're done with fragile systems and want to level up your integration game, this one's for you!
The knee-jerk reaction is often to add a queue! Sure, it helps for a while. But queues introduce their own complexity: handling failures, managing retries, creating visibility... It's a band-aid, not a cure, and we've been wrestling with this problem for too long!
In this blog post, we'll break down:
- Why queues fall short when building truly resilient integrations - The core principles behind building scalable, fault-tolerant async workflows - Practical techniques that go beyond the limitations of queues
If you're done with fragile systems and want to level up your integration game, this one's for you!