Trilio Data, Inc.

Jisto Inc.

Aleksandr Biberman

Andrey Turovsky

Brad Cordova

Systems and methods for deploying computer application workload elements among a plurality of computing resources are described. An elastic workload orchestration architecture includes a workload queue that is configured to receive application workload elements for processing using one or more distributed hybrid application services. The workload elements are evaluated to confirm whether they are properly formatted for deployment among the distributed hybrid application services and, if such confirmation cannot be made, the workload elements are adapted into a proper format. An elastic workload operator then deploys the workload elements to the distributed hybrid application services.

Ubiquitous and elastic workload orchestration architecture of hybrid applications/services on hybrid cloud

A bottom-up approach is taken to creating a condensed container, in which an automatic determination is made of the minimum set of requirements and dependencies, in forms of libraries and packages, for deployed applications/services and any corresponding user-specified content. The most fitting libraries and packages are merged with the applications/services, and the merged results are containerized using a minimized version of a container base image. Specialized unikernel generation includes automatically determining the minimum set of requirements and dependencies, in forms of libraries and packages, for the deployed applications/services and any corresponding user-specified content. The best available library operating system is identified, and compilation occurs to generate the unikernel. In effect, optimized (in terms of most fitting to applications/services, for any combination of size, speed, resource utilization, and performance) containers and unikernel images from applications/services by leveraging traditional unikernel technologies are produced.

Efficient workload deployment using containers and unikernels

Described are computer-based methods and apparatuses, including computer program products, for leveraging available compute resources from a plurality of computing devices using containers. Each computing device from the plurality of computing devices executes a container that virtualizes a portion of an operating system executing on the computing device such that the container can execute one or more secondary applications in isolation from any incumbent applications being executed by the operating system on the computing device that have priority over the one or more secondary applications.

Elastic compute cloud based on underutilized server resources using a distributed container system

Various embodiments of the invention provide methods and systems for providing a distributed computing platform. Tasks for execution are received from a remote computer and a set of computation users are identified to execute the set of computation task segments. The tasks are distributed to the set of computation users a solution segment is received from each computation user in the set of computation users to generate a set of solution segments, which are combined into a solution.

Growing community of inventors

Cambridge, MA, United States of America

Aleksandr Biberman