Infrastructure optimizations such as Managed Autoscaling, Spark Dynamic Allocation, and configuration tuning don’t eliminate the problem of application waste. Pepperdata can automatically save you 30% or more within your applications.
Save an average of 30-47 percent on Spark workload costs on Amazon EMR and Amazon EKS.
Minimize (or eliminate) waste in Spark to run more applications without additional spend.
Free developers from the tedium of managing individual apps so they can focus on more innovative and strategic tasks.
Data from 2023 Pepperdata TPC-DS Benchmark
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.
If you’re running Spark, give us 6 hours,
We’ll save you 30% on top of everything you’ve already done.
If you’re running Spark, give us 6 hours, We’ll save you 30% on top of everything you’ve already done.
If you’re running Spark, give us 6 hours, We’ll save you 30% on top of everything you’ve already done.
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 Cost Optimization Proof-of-Value to see how Pepperdata Capacity Optimizer can help you start saving immediately.