Maximize the Value of Your Apache Spark Workloads

Pepperdata Capacity Optimizer autonomously and continuously reclaims waste from Spark applications in real time, empowering you to:

  • Reduce monthly spend and run more apps for the same cost
  • Drive optimal price/performance cost outcomes
  • Reduce inefficiencies in the cloud or on premises

Secure up to 47% Cost Savings with Continuous Intelligent Tuning

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    Reduce Costs

    Save an average of 30-47% on your Apache Spark workload costs on Amazon EMR and Amazon EKS

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    Optimize Your Apache Spark Clusters for Efficiency

    Minimize (or eliminate) waste in Spark to run more applications without additional spend

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    Eliminate Manual Tweaking and Tuning of Apache Spark Applications

    Free your developers from the tedium of managing individual apps so they can focus on innovation

Pepperdata saved 50% for a large software company running huge Apache Spark jobs. Let us do the same for you.


Pepperdata Optimizes Apache Spark Clusters
in the Cloud or On-Prem

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No matter where you run Apache Spark—in the cloud, on prem, or in hybrid environments—Pepperdata Capacity Optimizer saves you money by:

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    Automatically identifying where more jobs can be run in real time  

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    Enabling the scheduler to more fully utilize available resources before adding new nodes or pods

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    Eliminating the need for manual tweaking and tuning so your team can focus on higher value tasks

The result: Apache Spark CPU, memory, and I/O resources are automatically optimized to reduce costs and increase utilization, enabling more apps to be launched at cost savings of up to 47%.

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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 can help you start saving immediately.