Real-time, automated cost optimization for Amazon EMR and Amazon EKS with no manual tuning, no recommendations, and no application code changes.
Run more work per node. Deploy fewer nodes.
Pepperdata intelligently increases resource utilization by evaluating actual instead of allocated resource utilization
Pepperdata ensures new instances are added only when existing instances are fully utilized
Pepperdata instructs the scheduler to remove capacity from overprovisioned applications
You’re probably optimizing your platform infrastructure with a variety of techniques, but there’s still waste inherent in your applications. Pepperdata’s Continuous Intelligent Tuning fixes that for you automatically.
*Statistics captured from our 2023 benchmark work on Amazon EKS
Cost Savings: Reduced instance hour consumption
Improved Performance: Decreased application runtime
Increased Throughput: Uplift in average concurrent container count
*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, 500 nodes, and 10 parallel applications with 275 executors per application.
Know exactly where and how your money is being spent in all of your cloud workloads to immediately reduce your spend.
Pepperdata uses Machine Learning to optimize your spend so you pay only for the resources you actually use.
Pepperdata automates application tuning in real time so your workloads are maintained in their optimal sweet spot continuously and autonomously.
Looking for a safe, proven method to reduce waste and cost by up to 47% and maximize value for your cloud environment? Sign up now for a free savings assessment to see how Pepperdata Capacity Optimizer Next Gen can help you start saving immediately.