We are different from Keebo in the way we approach warehouse optimization. Keebo seems to dynamically change the size of a warehouse - we have found that to be somewhat risky, especially when it's downsizing. Performance can take a big hit in this case. So we've approached this problem in two ways:

1. Route queries to the right-sized warehouse instead of changing the size of a particular warehouse itself. This is part of our dbt optimizer module. This ensures that performance stays within acceptable limits while optimizing for costs.

2. Baselit's Autoscaler optimally manages the scaling out of a multi-cluster warehouse depending on the load, which is more cost effective than upsizing the warehouse.