Hi everyone,
I’m Steve, a product manager here at Bubble focused on helping you scale your apps. I’m excited to share that the Schedule API Workflow on a List action can now schedule up to 100K workflows, making this a robust, native option for completing bulk operations. This update builds on previously announced improvements to reliability and performance and represents an important step in strengthening Bubble’s capabilities as an enterprise-grade platform where you can scale confidently.
Note: If your app is on a legacy plan, you will need to upgrade your plan to unlock these improvements.
Schedule API workflows with confidence
A few months ago, we announced enhancements that increased the number of workflows that could be scheduled with Schedule API Workflow on a List. But we know we left a critical question unanswered: exactly how many workflows could be scheduled?
This question was difficult to answer because the limit could vary dramatically depending on the memory available at any given time and the parameters of the workflow being scheduled. To eliminate the resulting ambiguity, our engineering team made changes to batch the tasks being scheduled and clear the cache along the way. This allows us to avoid hitting a memory limit and significantly reduces the variability around the number of workflows that can be scheduled. Now we can reliably schedule 100K workflows irrespective of external conditions or the specifics of the workflow parameters.
If your app is on a dedicated server (available on the Enterprise plan), you will be able to schedule at least 100K workflows — and in many cases, multiples of that. There is no explicit limit since the capabilities can vary based on your instance’s configuration. Please reach out to your Technical Success team if you have questions about your unique instance.
Capitalize on performance and reliability at scale — by default
The enhancements we’ve made over the past few months have helped us significantly speed up scheduling and execution of backend workflows for bulk use cases. At the same time, we’ve improved workflow reliability and protected performance for your app’s frontend users during processing.
With this foundation in place, we’ve updated the default (empty state) interval for Schedule API Workflow on a List to schedule workflows at a much higher frequency. If you’re using the default interval, you’ll see a significant difference in how quickly a given set of workflows completes. Existing actions with intervals that have been set manually won’t be modified automatically, but you can update them easily in the Bubble editor.
Here are results from benchmark tests for simple bulk operations using Schedule API Workflow on a List to execute 100K workflows compared to scheduling them recursively:
Schedule API Workflow on a List | Recursive | |
---|---|---|
Delete 100K things | 20–25 min | 6–7 hrs |
Copy 100K things | 60 min | 10 hrs |
Modify 100K things | 75 min | 12 hrs |
WU for scheduling 100K workflows | ~12,000 (~0.12 per workflow) | 70,000 (0.70 per workflow) |
The results above are approximate and intended to illustrate some simple examples. Results will vary based on the specifics of your app and workflows.
Looking forward
We’re committed to giving you more ways to support your apps as they grow. If you’d like to learn more about our initiatives across the Bubble platform, our new Director of Platform Engineering, Payam, shared more about the progress we’ve made and our plans for the coming months in this post.
Over the coming months, the Scale team is investing further in observability, including new functionality to help you track progress, understand outcomes, and troubleshoot issues for workflows scheduled using Schedule API Workflow on List.
As a reminder, for technical reasons, these improvements are only available on our new (workload-based) pricing or Enterprise plans. If your app is still on a legacy plan you can upgrade to one of our new plans to take advantage of these changes and the rest of our exciting scalability improvements on the roadmap for 2024.