Right-sizing Kubernetes workloads efficiently

As a platform engineering leader overseeing multiple EKS clusters, one of my top priorities is ensuring that our infrastructure scales efficiently without overspending. Kubernetes makes it easy to add capacity, but that flexibility can also lead to overprovisioning, and ultimately, wasted cloud dollars. Datadog’s Vertical Pod Autoscaler (VPA) has been a game-changer in this space. Unlike traditional horizontal scaling, which only adjusts the number of pods, VPA continuously monitors actual CPU and memory usage and automatically tunes resources for each pod. This means workloads are always right-sized: under-provisioned pods get the resources they need to perform reliably, while over-provisioned pods scale down, freeing up capacity and reducing costs. It’s a smart, automated approach that keeps our clusters running efficiently without constant manual intervention.

Beyond the immediate resource optimization, Datadog VPA gives platform teams the visibility and control we need to manage cost and performance at scale. Combined with Datadog Kubernetes Autoscaling, we can see exactly which workloads are over-allocated, understand their impact on cluster spend, and implement scaling recommendations safely across environments. This integrated approach allows us to manage horizontal and vertical scaling together, handle traffic spikes seamlessly, and reclaim wasted resources in real time. For organizations running dynamic workloads on EKS, adopting VPA is no longer just a nice-to-have, it’s a critical part of building cost-conscious, high-performing Kubernetes environments.