International Business Machines Corporation

Samuel D Matzek

Gerald Francis McBrearty

Jeffrey Wayne Tenner

George James Romano

Tammy Lynn Van Hove

James J Fall

Anthony Michael Dunbar

Andrew L Hanson

Steven R Kaufer

Jeb R Linton

Siyamack Ghaeedan

Kris Marie Murphy

Jeff McNeely

Disclosed are techniques for post-quantum encrypted trusted execution environments on edge devices. An edge computing device includes a trusted execution environment that encompasses at least some SIMD processing units such as Graphics Processing Units (GPUs). A data record, such as machine learning inferences from a machine learning or artificial intelligence model, is generated on the edge computing device within the trusted execution environment and encrypted with post-quantum encryption (such as lattice based encryption) using SIMD processing units in the trusted execution environment. Workloads received for the trusted execution environment, also encrypted with post-quantum encryption, are decrypted using the SIMD processing units in the trusted execution environment.

Post-quantum cryptography secured execution environments for edge devices

Systems and computer program products to perform an operation comprising receiving a request to perform a predefined operation on at least one of a virtual machine and a workload executing on a host in a first cloud computing environment, identifying a set of credentials to access the first cloud computing environment, and initiating performance of the predefined operation on the at least one of the virtual machine and the workload, wherein the predefined operation comprises at least one of: (i) deleting, and (ii) shelving the at least one of the virtual machine and the workload.

Self-terminating or self-shelving virtual machines and workloads

Methods comprise receiving a request to perform a predefined operation on at least one of a virtual machine and a workload executing on a host in a first cloud computing environment, identifying a set of credentials to access the first cloud computing environment, and initiating performance of the predefined operation on the at least one of the virtual machine and the workload, wherein the predefined operation comprises at least one of: (i) deleting, and (ii) shelving the at least one of the virtual machine and the workload.

Systems, methods, and computer program products to perform an operation comprising receiving, from a workload in a cloud computing environment, an abstract request to modify resources allocated to the workload, translating, by a tuning service, the abstract request to a set of requirements to fulfill the abstract request, identifying, by the tuning service, a resource configuration suitable to satisfy the set of requirements, and providing, by the tuning service, the resource configuration to fulfill the abstract request.

Cloud independent tuning service for autonomously managed workloads

The invention addresses these and other problems associated with the prior art by providing an apparatus and program product that manage virtual machines in a virtualized computing environment based at least in part on limitations associated with storage fabrics through which virtual machines may access one or more storage systems in such an environment. The storage fabric limitations, referred to herein as fabric limits, may be used, for example, in connection with placing virtual machines on hosts in a virtualized computing environment. As another example, fabric limits may be used in connection with deploying virtual machines into a virtualized computing environment to reduce the likelihood of boot errors. As still another example, fabric limits may be used in connection with load balancing across multiple fabrics in a virtualized computing environment.

Delayed boot of a virtual machine in a virtualized computing environment based on a fabric limit

A method manages virtual machines in a virtualized computing environment based at least in part on limitations associated with storage fabrics through which virtual machines may access one or more storage systems in such an environment. The storage fabric limitations may be used, for example, in connection with placing virtual machines on hosts in a virtualized computing environment. As another example, storage fabric limitations may be used in connection with deploying virtual machines into a virtualized computing environment to reduce the likelihood of boot errors. As still another example, storage fabric limitations may be used in connection with load balancing across multiple fabrics in a virtualized computing environment.

An apparatus and program product manage virtual machines in a virtualized computing environment based at least in part on limitations associated with storage fabrics through which virtual machines may access one or more storage systems in such an environment. The storage fabric limitations may be used, for example, in connection with placing virtual machines on hosts in a virtualized computing environment. As another example, storage fabric limitations may be used in connection with deploying virtual machines into a virtualized computing environment to reduce the likelihood of boot errors. As still another example, storage fabric limitations may be used in connection with load balancing across multiple fabrics in a virtualized computing environment.

Management of a virtual machine in a virtualized computing environment based on a fabric limit

Method to perform an operation comprising receiving, from a workload in a cloud computing environment, an abstract request to modify resources allocated to the workload, translating, by a tuning service, the abstract request to a set of requirements to fulfill the abstract request, identifying, by the tuning service, a resource configuration suitable to satisfy the set of requirements, and providing, by the tuning service, the resource configuration to fulfill the abstract request.

Growing community of inventors

Rochester, MN, United States of America

Samuel D Matzek