Kubernetes optimization and application performance automation platform that turns workload, infrastructure, cost, and SLO signals into safe automated actions.
Kubernetes optimization and application performance automation platform that turns workload, infrastructure, cost, and SLO signals into safe automated actions.
Automatically tunes CPU, memory, requests, limits, and replicas based on real workload behavior to reduce overprovisioning without starving applications.
Automated Kubernetes platform that continuously optimizes workloads, right-sizes resources, and manages infrastructure to protect SLOs while reducing cloud spend.
Kubernetes cost and performance intelligence showing actual, requested, and provisioned usage by cluster, namespace, workload, team, CPU, memory, and GPU.
What customers say
“After integrating Cast, we didn’t have to do anything during Black Friday, which is amazing. We gained not just compute cost reduction but also a reduction in engineer workload.No Spot instances are available? No problem; the workload is automatically moved to on-demand instance…”
CustomerCast AI customer
“The core savings we got are just brilliant, falling between 40-70%, depending on the workload. But that’s not the full story. Before implementing Cast AI, my team was constantly moving around knobs and switches to make sure that our production environments and customers were up…”
CustomerCast AI customer
Kubernetes Workload Optimization
Cast AI reports that Bede Gaming adopted Workload Optimization to automatically rightsize Kubernetes requests and limits. Conservative optimization settings delivered 10–15% cloud cost savings without affecting…
Cast AI reports that Ampeers Energy used its cost monitoring module to inspect Kubernetes spending and utilization, then enabled automated optimization on a development cluster for a 33% cost reduction. Additional Spot…
Cast AI reports that Altruist used workload rightsizing, instance provisioning and Spot automation, achieving consistent savings of 45% or more and reclaiming 85–130 engineering hours monthly. The customer interview…
In December 2025, Cast AI introduced pod distribution groups for mutations, expanded Azure Cloud Connect for AKS resource discovery, and improved rebalancing algorithms. Cast AI also achieved certification as a SUSE Rancher solution partner, validating compatibility with Rancher-managed Kubernetes clusters. Other updates included cluster-scoped authentication for hosted AI models and simplified organization management within the console.
In January 2026, Cast AI launched the DBO Index Advisor for PostgreSQL, native Slack integration for alerts, and formally moved Cluster Hibernation to general availability. Infrastructure support was expanded to include AWS Inferentia and Trainium instances, Azure v6-series VMs, and GCP Flexible Committed Use Discounts. The update also introduced container-level exclusion for autoscaling policies and redesigned the AI Enabler analytics dashboard.
In February 2026, Cast AI introduced support for AWS Capacity Blocks for GPU reservations. The company also launched connection pooling for PostgreSQL in its Database Optimizer, batch processing for AI Enabler, GKE Autopilot support, and Azure Savings Plans import. Additional cloud provider improvements include GPU driver management on GKE, Azure permission reductions, and GCP TPU instance support. The update also adds new models to AI Enabler and enhances the Application Performance Automation (APA) service with broader repository integration support.
