In-place pod resizing in Kubernetes now allows users to update container resource requests and limits without restarting the pod, making it possible to adapt to real-time workload demands with minimal disruption. This feature is a game-changer for platform engineering, DevOps, and SRE teams, especially when paired with automation platforms like Cast AI that can fully leverage this capability to adjust resource allocations on the fly. With in-place resizing, teams don't need to resort to overprovisioning to avoid risk, leading to wasted resources and inflated cloud bills. Instead, they can now optimize their workloads continuously, even as they evolve, without manual intervention or complex restart automation logic. Cast AI takes full advantage of this feature by automatically detecting resource inefficiencies and applying the right adjustments at the right time, eliminating the need for manual monitoring and decision-making.