Pepperdata Capacity Optimizer eliminates the hassle of manual tweaking and tuning while delivering up to 47% cost reduction by:
Capacity Optimizer rapidly identifies where more work can be done and adds tasks to nodes with available resources. The result: CPU, memory, and I/O resources are automatically optimized to increase utilization, enabling more applications to be launched in both Kubernetes and traditional big data environments. Working autonomously in real time, Capacity Optimizer frees your developers to develop rather than fine tune.
A software company found that scaling Amazon EMR resources to handle workloads resulted in runaway costs. Check out the case study to see how Pepperdata significantly increased capacity for their Amazon EMR workloads and reduced costs by over 50%!