MILPITAS, CA, August 17, 2020 — ProphetStor Data Services, Inc. was assigned the patent “METHOD FOR DEPLOYING STORAGE SYSTEM RESOURCES WITH LEARNING OF WORKLOADS APPLIED THERETO“ (Patent number US 10,013,286) by the United States Patent and Trademark Office. The patented technology is a pillar of the foundation in ProphetStor’s Federator.ai platform that uses application-awareness and workload prediction as the basis for resource allocation and adaptation to meet the requested SLA, to optimize performance, and to reduce the cost of over-provisioning. In contrast to the conventional wisdom of virtualization based on fixed capacity assignment throughout the lifetime of an application, ProphetStor believes that the infrastructure resources should be adaptive by serving the applications according to their KPI, priority, and dynamic requirements in performance and capacity. Federator.ai builds models with Deep Learning and mathematics/statistical methods to create accurate predictions for applications. Federator.ai brings intelligibility to planning, performance enhancement, and just-in-time fitted resource allocation.
ProphetStor has been devoting its innovation in bringing Machine Learning to IT operations since it was founded in 2012. The patented technology is the foundation of our solutions to Kubernetes ecosystems, which are now commonly used for Hybrid MultiCloud, 5G, and Edge Computing that require automation and operational efficiency.
“We believe the resource allocation in Hybrid MultiClouds and 5G edge to core should be adaptive according to application types, SLA requirements, and workloads in its lifecycle. However, optimization of the scheduling and scaling is a very complicated task. ProphetStor’s newly granted patent tackles this issue by incorporating AI technology and digital intelligence to the applications and the infrastructure. The prediction of the application workload, coupled with the Multi-Layer Correlation and Impact Analysis, can effectively reduce the computation power needed to run our AI Engine for planning and operation,” said Eric Chen, CEO of ProphetStor. “We are happy to report that Federator.ai has been working effectively and seamlessly with major cloud monitoring service providers to bring tremendous values to our customers and to help democratize the MultiCloud adoption.”
ProphetStor’s patented, Deep Learning enabled Data Correlation and Impact Prediction Engine (DCIE) forms the foundation for its Federator.ai. ProphetStor’s Federator.ai 4.2 is a generally available product from ProphetStor. For a detailed description of the solution, please visit https://www.prophetstor.com/federator-ai/