Karpenter Cost Optimization: Consolidation Benchmark Results (7-Day Run)

The benchmark study compared four different Kubernetes cluster consolidation strategies using the Karpenter provisioner and Cast AI tools, demonstrating varying cost efficiencies over a seven-day period with adversarial workload conditions on AWS EKS. The baseline approach solely relied on Karpenter's built-in consolidation policy, which was found to be limited due to its inability to perform coordinated multi-node reshuffling, resulting in the highest cost of $703.08. A second variant integrated Cast AI's Evictor, a continuous bin-packing daemon, leading to modest savings of 9.1% by continuously evicting underutilized nodes. The third variant, which employed Cast AI's Continuous Rebalancer from the Karpenter Enterprise Suite, improved savings to 15.8% by enabling more targeted instance selection and coordinated node drains. The most cost-effective solution, the Cast AI Autoscaler, replaced Karpenter entirely, achieving a 43.0% reduction in costs by optimizing workload fit during provisioning, thereby minimizing the need for post-hoc corrections. This study underscores the potential for significant cost reductions through strategic consolidation approaches, particularly when provisioning decisions are optimized from the outset.

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