gke-workload-scaling

Automate GKE autoscaling by configuring Horizontal Pod Autoscalers and Vertical Pod Autoscalers to dynamically adjust resources based on real-time metrics, ensuring high availability and cost optimization for production environments.

Vertical Pod Autoscaling right-sizes container resource requests in GKE by analyzing actual usage patterns over time, automatically adjusting CPU and memory allocations to ensure efficient resource allocation and reduce over-provisioning costs.

Handling traffic spikes without over-provisioning requires Horizontal Pod Autoscaling to automatically adjust pod counts based on CPU or memory utilization, preventing performance degradation during traffic spikes while reducing costs from over-provisioned infrastructure.

You can configure Horizontal Pod Autoscaling for a deployment like web-server by setting a target CPU utilization of 60 percent, automatically adjusting pod counts to handle varying traffic loads in the production namespace.

GKE workload scaling integrates with the Cluster Autoscaler to ensure the underlying node pool has sufficient capacity to accommodate scaled workloads, dynamically adjusting nodes to support increased pod counts during scaling events.

You need both HPA and VPA for automated infrastructure governance because HPA scales pod counts for traffic loads while VPA right-sizes container resources based on usage patterns, together ensuring high availability and cost optimization.