Emc IP Holding Company LLC

Dell Products Inc.

Dell & Products L.p.

Xuebin He

Victor Fong

Kenneth Durazzo

Amy N Seibel

Megan A Murawski

Stephen J Todd

James Robert King

Alex Robbins

Malini Bhattacharjee

Himanshu Arora

Michael Robillard

Kathleen Moriarty

Brendan Burns Healy

Orlando Xavier Nieves

Akshaya Khare

Thinh Lam Truong Nguyen

Brian Roche

Thinh Nguyen

Gary White, Jr

Aman Wangde

Prasenjit Roy

Nisanth Mathilakath Padinharepatt

Edgardo Robles

Benjamin E Santaus

One example method includes evaluating a function invoked by a request that is received at a local classical computing execution environment, and the request also implies performance of a quantum computing function in a quantum computing execution environment, based on an outcome of the evaluating, determining whether or not the function should be run in the local classical computing execution environment, or whether the function should be run in a separate classical computing execution environment, and when the determining indicates that the function should be run in the separate classical computing execution environment, forwarding the request to the separate classical computing environment for execution of the function. The local classical computing execution environment, the separate classical computing execution environment, and the quantum computing execution environment, are respective first, second, and third, tiers of a hybrid computing execution environment.

3-tier quantum computing execution model

An apparatus comprises a processing device configured to identify one or more dependent services for a workload deployed in a first computing cluster of a multi-cluster computing environment and to select, utilizing a global service catalog aggregating service information for sets of available services offered by at least two computing clusters of the multi-cluster computing environment, a second computing cluster of the multi-cluster computing environment to utilize for provisioning at least a given one of the one or more dependent services for the workload. The processing device is further configured to provision the given dependent service on a multi-cluster service mesh associated with the multi-cluster computing environment by configuring the multi-cluster service mesh to permit access by the workload on the first computing cluster of the multi-cluster computing environment to the given dependent service on the second computing cluster of the multi-cluster computing environment.

Global service catalog for provisioning services on a multi-cluster service mesh of a multi-cluster computing environment

Mechanisms of cloning containers to spawn offspring, orchestrate new containers on different execution environments, and enabling intra-container communication while maintaining parent-child relationships are disclosed.

Container cloning and branching

One example method includes performing dynamic access control in a computing network. A computing environment is configured such that an application can access a service without specifying secrets. The secrets needed to access the service are obtained and stored in a credential store. The secrets can be obtained using the service mesh in a manner that isolates the application from the secrets.

Dynamic access control in service mesh with service broker

One example method includes connecting to a server component, transmitting, to the server component, information concerning a hardware configuration associated with an asset having a capability that is fully utilized during a first time period and the capability is idle during a second time period, receiving, from the server component, cluster connection information, and using the cluster connection information to temporarily connect the asset to the cluster as a node of the cluster so that the capability is available during idle time to perform a workload of the cluster.

Dynamic cloud native cluster construction using under-utilized machines

One example method includes transmitting a request for a container image to a registry, receiving metadata associated with the container image, wherein the metadata allows a controller to mount an empty filesystem on a host machine, starting a container from the container image without receiving all files associated with the container image, receiving files, from a container server, needed by the container based on an access sequence associated with the container. This allows a container to be started without downloading the entire container image and also conversed bandwidth by providing the files as needed based on the manner in which the container accesses files during execution.

Intelligent filesystem for container images

Techniques for function execution environment selection for a decomposed application are provided. In one example, an apparatus comprises at least one processing platform configured to execute a portion of an application program in a first virtual computing element, wherein the application program comprises one or more portions of marked code, receive a request for execution of one of the one or more portions of marked code, decide whether to execute the portion of marked code identified in the request in the first virtual computing element or in a second virtual computing element, determine an execution environment from one or more execution environments specified in the marked code for the second virtual computing element to execute the marked code, when it is decided to execute the portion of the marked code in the second virtual computing element, and cause the portion of marked code identified in the request to be executed.

Function execution environment selection for decomposed application

An apparatus comprises a first processing device, the first processing device comprising a physical hardware controller configured for coupling with a second processing device. The first processing device is configured to identify remote storage service instances attached to the second processing device, and to initiate storage emulation modules for the remote storage service instances attached to the second processing device, the storage emulation modules emulating physical storage devices configured for attachment to the second processing device. The first processing device is also configured to provision the remote storage service instances to the second processing device by utilizing the physical hardware controller (i) to dynamically select at least one remote storage service instance to utilize for processing input/output requests directed to storage volumes of the emulated physical storage devices and (ii) to provide results of processing the input/output requests to the second processing device via the emulated physical storage devices.

Physical hardware controller for provisioning dynamic storage services on processing devices

A method includes identifying a first event that has been at least partly performed, wherein the first event comprises an element of a sequence of events, and the first event comprises performance of a first computing function, predicting a second event expected to occur next in the sequence after completion of the first event, and the second event comprises performance of a second computing function, predicting a start time of the second event, based on information about the second event, identifying a particular container capable of implementing the second computing function associated with the second event, predicting a start time for start-up of the container, starting up the container, and completing start-up of the container prior to receipt of a request for the second computing function to be performed by the container, wherein the container is ready to perform the second computing function immediately after start-up has been completed.

Finding the optimum time to prestart container running functions using events

A resource usage platform is disclosed. The platform performs preemptive container load balancing, auto scaling, and placement in a computing system. Resource usage data is collected from containers and used to train a model that generates inferences regarding resource usage. The resource usage operations are performed based on the inferences and on environment data such as available resources, service needs, and hardware requirements.

Pre-emptive container load-balancing, auto-scaling and placement

One example method includes receiving, from a microservice, a service request that identifies a service needed by the microservice, and an API of an endpoint that provides the service, evaluating the service request to determine whether the service request conforms to a policy, when the service request has been determined to conform with the policy, evaluating the endpoint to determine if endpoint performance meets established guidelines, and when it is determined that the endpoint performance does not meet the established guidelines, identifying an alternative endpoint that meets the established guidelines and that provides the requested service. Next, the method includes transforming the API of the service identified in the service request to an alternative API of the service provided by the alternative endpoint, and sending the service request and the alternative API to the alternative endpoint.

Dynamic service mesh

One example method includes configuring an input device based in part on a type of network with which the input device is expected to be used, configuring an output device based in part on a type of network with which the output device is expected to be used, registering the input device and the output device with an orchestrator, downloading a service needed to process a data stream generated by the input device, configuring an execution pipeline, and the execution pipeline includes the service, receiving the data stream from the input device and processing the data stream with the execution pipeline, and transmitting information relating to the processed data stream to the output device.

Home-smartmedia-MEC with cloud marketplace

A peer container filesystem is provided. The peer container filesystem allows peer nodes to share containers. The peer container filesystem allows the images or portions thereof to be shared without a container registry. A node send requests to the network that are configured to push or distribute an image in the network, search for an image in the network, download an image in the network, and perform updates amongst the peer nodes such that the locations of images and/or their files are known to at least some of the peers in the network.

Intelligent peer-to-peer container filesystem

A method for managing data includes obtaining, by a database proxy server, a document manifest, wherein the document manifest specifies a plurality of queries, wherein each of the plurality of queries specifies data and a policy to be implemented on the data, wherein the data is stored in a central database, and processing the plurality of queries.

Growing community of inventors

Westwood, MA, United States of America

Xuebin He