Kubernetes Workload, Node, & Cluster Optimization
Rule-based automation only works until workloads change. Sedai’s ML constantly adapts, keeping Kubernetes optimized even when behavior evolves.
Autonomous Workload Rightsizing
Continuously tunes pod CPU & memory based on real workload behavior. No static requests, limits or thresholds.
Smarter Node Utilization
Packs workloads based on real utilization patterns and performance. Reduce waste while keeping services stable.
Cluster-Level Optimization
Sedai evaluates your cluster beyond the pod or node level. So you get actual node reductions and real infra savings.
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