Company Filing History:
Years Active: 2024
Title: Sandeep Kumta Vishnu: Innovator in Cloud Technology
Introduction
Sandeep Kumta Vishnu is a notable inventor based in Bellevue, WA (US). He has made significant contributions to the field of cloud computing, particularly in the area of workload management. His innovative approach leverages machine learning to enhance the efficiency of cloud systems.
Latest Patents
Sandeep holds a patent for a groundbreaking invention titled "Machine-learning-based replenishment of interruptible workloads in cloud environment." This patent outlines systems and methods for scheduling a virtual machine (VM) to host a workload in a cloud system. The technology focuses on scheduling an evicted VM for redeploying an interruptible workload, utilizing capacity prediction and inference data associated with the type of the evicted VM. The capacity signal predictor generates training data for a machine learning model, which predicts capacity and eviction rates based on the current status of available computing resources. Upon receiving a notice of workload interruption, the intelligent scheduler prioritizes the evicted VM for scheduling and assesses whether to defer redeploying it based on the eviction rate.
Career Highlights
Sandeep is currently employed at Microsoft Technology Licensing, LLC, where he continues to innovate in the realm of cloud technology. His work has positioned him as a key player in the development of advanced scheduling systems that improve the reliability and efficiency of cloud services.
Collaborations
Sandeep has collaborated with talented individuals such as Inigo Goiri Presa and Rakesh Akkera. These partnerships have fostered a creative environment that encourages the development of cutting-edge solutions in cloud computing.
Conclusion
Sandeep Kumta Vishnu's contributions to cloud technology through his innovative patent demonstrate his expertise and commitment to advancing the field. His work not only enhances the efficiency of cloud systems but also sets a precedent for future innovations in workload management.