Kubernetes On-Premises: How to Automate and Optimize Costs

Cast AI has extended its automation and cost optimization capabilities to include on-premises Kubernetes clusters, addressing challenges such as overprovisioning, lack of automated workload rightsizing, fragmented ecosystem, complex infrastructure management, security and compliance, maintenance and updates. The platform provides a unified optimization platform, automated workload rightsizing through Horizontal Pod Autoscaler (HPA) and Vertical Pod Autoscaler (VPA), and cost monitoring with customizable dashboards and automated alerts via tools like Prometheus and Grafana. Additionally, Cast AI's bin-packing technology optimizes workload placement within nodes to maximize efficiency and minimize waste, resulting in increased node utilization, automated pod scheduling adjustments, and cost and energy savings. By automating infrastructure management and improving visibility, Cast AI simplifies Kubernetes optimization across on-premises and multi-cloud environments.

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