"When you have an application that dynamically scales, you often end up with excess headroom. For example, if your application scales at 60% usage, the remaining 40% goes unused because once you reach that, it scales up again, leaving another 40% buffer that you still pay for. Additionally, the Google autoscaler isn’t very strict; it leaves a lot of headroom on the nodes, meaning you’re paying for around 15-20% more computational power than needed because the autoscaler doesn’t reduce that capacity efficiently. Cast AI addressed these issues by reducing headroom on both the physical nodes and the application side."