Pepperdata, a provider of performance and capacity optimization software, has introduced managed autoscaling in the cloud with Pepperdata Capacity Optimizer version 6.3. Capacity Optimizer augments autoscaling to ensure all nodes are fully utilized before additional nodes are created, helping to decrease waste and reduce cost.
According to Pepperdata, cloud providers provision infrastructure based on the peak needs of workloads, but while this guarantees the maximums are met, there is waste inherent in the current method of provisioning. Capacity Optimizer makes thousands of decisions per second, analyzing the resource usage of each node in real time to optimize the utilization of CPU, memory and I/O resources on big data clusters. The net effect is that horizontal scaling is optimized and waste is eliminated.
Pepperdata provides automated deployment options for customers that can seamlessly be added to EMR, Dataproc and Qubole deployments. In addition to automatically tuning cloud deployment for optimal performance, Pepperdata helps to reduce troubleshooting time, tune application resources for peak efficiency, and automatically detect and alert on bottlenecks that impact SLAs.
"Even with the best cloud migration strategy and dedicated attempts to curb costs, the cloud makes managing resourcesmore difficult,” says Ash Munshi, CEO Pepperdata. “But, by leveraging machine learning and managing infrastructure in real time, IT operations teams automatically recapture wasted capacity and significantly reduce their costs.”
Pepperdata Capacity Optimizer with managed autoscaling is available in July as a supported beta release for companies looking for early access, with free updates provided. The general availability release is due in September 2020. For more information, visit www.pepperdata.com.