To maintain a consistent user experience and optimize resource utilization in a GKE cluster, what should you configure for your stateless application?

The ideal choice for maintaining a consistent user experience and optimizing resource utilization in a Google Kubernetes Engine (GKE) cluster for a stateless application is to configure a Horizontal Pod Autoscaler (HPA).

The Horizontal Pod Autoscaler automatically adjusts the number of pod replicas in a deployment based on observed CPU utilization or other select metrics. By dynamically scaling the number of pods, HPA can accommodate varying workloads efficiently, ensuring that the application has the necessary resources to handle incoming requests while minimizing resource waste during periods of low demand. This approach allows for a responsive adjustment to user load, enhancing the user experience through consistent application performance.

While other options serve important purposes, they do not specifically address the need for dynamic scaling of stateless applications. For instance, configuring a cron job to scale a deployment may be useful for periodic workloads but lacks the responsiveness needed for real-time demand changes. A Vertical Pod Autoscaler adjusts resource limits and requests for existing pods rather than scaling the number of pods, and while it can improve performance, it does not directly enhance user experience by providing more instances when demand spikes. Lastly, cluster autoscaling on the node pool manages the number of nodes in the cluster, which is important for capacity but does not directly scale the application instances themselves.