Here’s a bit more detail on how the scheduler works under the hood: 1. Each application still runs on its own Kubernetes node to guarantee isolation (so noisy-n

Here’s a bit more detail on how the scheduler works under the hood: 1. Each application still runs on its own Kubernetes node to guarantee isolation (so noisy-neighbor issues are eliminated). 2. We track CPU usage in real-time across all workloads and maintain a global usage map. 3. Idle CPU from any app/node becomes available for re-purchase by other workloads in the same resource plan. 4. CPU limits can be adjusted on the fly without restarts, enabling real-time response to changing load. If anyone wants to dive into topics like threshold algorithms, node assignment heuristics, or Kubernetes API interactions - I'm happy to dig into that.