Extract the most from your cloud investment
Pepperdata enhances resource optimization in your clusters in real time to save you 30–47% on average.
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Reduce Instance Hours immediately
Pepperdata reduces cost by eliminating waste and decreasing instance hour consumption.
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Optimize Spark clusters for peak application efficiency
Optimize Spark application capacity and run more jobs without changing your application code.
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Tune resources automatically
in real timeTune resources automatically in real time
Free developers from the hassle of manual resource optimization with automatic waste elimination.
Resource optimization with Continuous Intelligent Tuning
Resource optimization with Continuous Intelligent Tuning
Using patented algorithms, Capacity Optimizer’s Continuous Intelligent Tuning:
- Rapidly identifies opportunities and implements resource optimization in real time
- Automatically adds tasks fill nodes that have available resources
- Enables new nodes to be launched only when existing nodes are fully utilized
The result:
CPU and memory are automatically optimized
More applications launched
without increasing cost
Developers are freed to focus on innovation versus continually tuning apps by hand
CPU and memory are automatically optimized
More applications launched
without increasing cost
Developers are freed to focus on innovation versus continually tuning apps by hand
CASE STUDY
Autodesk reduces Amazon EMR costs by 50% and boosts performance with Pepperdata
CASE STUDY
Autodesk reduces Amazon EMR costs by 50% and boosts performance with Pepperdata
Autodesk successfully reduced the cost of running Spark workloads on Amazon EMR by over 50% by optimizing application capacity with Pepperdata’s continuous, real-time resource optimization from Pepperdata.
TPC-DS Benchmarks for Apache Spark on Amazon EMR and EKS
Reduced the total instance hours and related costs by 41.8% and enabled the entire workload to run 45.5% faster (October 2023)
Optimized resource utilization with a 157% increase in CPU utilization and a 38% increase in memory utilization (August 2021)
*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, 10 parallel applications with 275 executors per application.
Pepperdata Capacity Optimizer
EMR on EKS savings
Pepperdata Capacity Optimizer EMR on EKS savings
Pepperdata conducted an October 2023 performance audit of Capacity Optimizer for Amazon EMR on EKS using a live customer’s workloads. The result: 42.5% reduced cost.