ProphetStor has been devoting its innovation in applying Machine Learning in IT operations since it was founded in 2012. The patented technology is a part of its efforts to manage the complexity of automating and optimizing the operations in Kubernetes ecosystems, Cloud, and Zero-Touch operation in 5G.

 

“We believe the resource allocation in Clouds and in the 5G edge to core network should be adaptive according to the application workloads. ProphetStor’s newly granted patent illustrates that prediction could help simplify the operation by bringing in intelligence about the applications and the infrastructure. The prediction of application workload, coupled with the Multi-Layer Correlation and Impact Analysis, can effectively reduce the computation resources needed for planning and operation,” said Eric Chen, CEO of ProphetStor. “Working from the top of the application stack, and analyzing the correlation from the top layer down, we can achieve the reduction in the computational cost by hundreds or even thousands times less than needed for optimizing planning, scheduling, and scaling. Also, the application-awareness and workload-awareness sets Federator.ai, our AIOps solution for Kubernetes ecosystems, apart from other solutions that claim to have a similar objective.”

 

ProphetStor’s patented, Deep Learning enabled Data Correlation and Impact Prediction Engine (DataProphet) 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://prophetstor.com/federator-ai/