The post discusses implementing Horizontal Pod Autoscaler (HPA) for Kubernetes Pods to achieve automatic horizontal scaling, contrasting it with Vertical Pod Autoscaler (VPA) and highlighting that they should not be used together for CPU or memory metrics. HPA, which updates workload resources in response to throughput demand, relies on metrics provided by the Kubernetes Metrics Server. The post details configuring HPA for a Konnect Data Plane deployment, including setting CPU and memory requests and replacing the NodeGroup with a smaller instance type to observe HPA in action. It describes a scenario where HPA creates new Pod replicas when CPU usage hits a 75% threshold, although resource limitations can lead to pending Pods. The post suggests using a cluster autoscaler, like Kubernetes Cluster Autoscaler or Karpenter on Amazon EKS, to address resource shortages and hints at further exploration of these tools in the series' next installment.