Pepperdata Capacity Optimizer autonomously optimizes your cluster resources, recapturing unused capacity so you can run more applications and get the most out of your infrastructure investment running Kubernetes—whether on prem or in the cloud.
Enterprises looking to maximize performance in the cloud are increasingly turning to Kubernetes—most notably for its autoscaling functionality. We surveyed 800 Kubernetes experts about the growth of their Kubernetes clusters and the resulting management challenges.
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Improved Performance: Decrease query duration 30%.
Improved Utilization: Decreased idle CPU by 13%.
Increased Throughput: Increased workload capacity by 35%.
Increased Available Resource Utilization: Decreased available memory by 27%.
*TPC-DS is the Decision Support framework from the Transaction Processing Performance Council. TPC-DS is an industry-standard big data analytics benchmark. Pepperdata’s work is not an official audited benchmark as defined by TPC. TPC-DS benchmark results (Amazon EKS), 1 TB dataset, 30 nodes, 225 executors, 103 jobs.