DETECTION OF UNDERUTILIZED DATA CENTER RESOURCES

    公开(公告)号:US20250028621A1

    公开(公告)日:2025-01-23

    申请号:US18224112

    申请日:2023-07-20

    Abstract: An apparatus may include a computer processor operating in a data center and running an AI/ML model. The apparatus may include a trace log agent and a telemetry agent. The computer processor may be configured to train and run the AI/ML model to determine if a resource in the data center is being utilized or is idle by using data provided by the trace log agent and a telemetry agent. The apparatus may include a status check engine, a discovery engine, and an analytics engine. The computer processor may be configured to run each of these engines to confirm a prediction by the AI/ML model that the resource is idle. The computer processor may be configured to notify an administrator of the data center if the AI/ML model predicts the resource is idle and the engines provide increased confidence to the prediction.

    User-side non-fungible token storage using super non-volatile random access memory

    公开(公告)号:US12159277B2

    公开(公告)日:2024-12-03

    申请号:US17868235

    申请日:2022-07-19

    Inventor: Elvis Nyamwange

    Abstract: A system for leveraging local/user-side resources (i.e., memory) to store Non-Fungible Tokens (NFTs) and conduct NFT-related computational processes required for generating/minting or exchanging an NFT. The local/user device is equipped with super Non-Volatile Random Access Memory (NVRAM), which operates in accordance with a resource-sharing protocol, such as Network Block Device (NBD) protocol or the like. The resource-sharing protocol is registered with the user's NFT digital wallet, which is in communication with the distributed trust computing networks and, thus links the local/user-side resources (i.e., NVRAM) with the distributed trust computing network for resource sharing capabilities.

    USING AUTOMATIC HOMOMORPHIC ENCRYPTION IN A MULTI-CLOUD ENVIRONMENT TO SUPPORT TRANSLYTICAL DATA COMPUTATION USING AN ELASTIC HYBRID MEMORY CUBE

    公开(公告)号:US20240380570A1

    公开(公告)日:2024-11-14

    申请号:US18781248

    申请日:2024-07-23

    Inventor: Elvis Nyamwange

    Abstract: Aspects of the disclosure relate to using automatic homomorphic encryption in a multi-cloud environment to support translytical data computation using an elastic hybrid memory cube. A computing platform may receive enterprise data from a data collection engine associated with an enterprise organization. The computing platform may inspect the enterprise data and discard enterprise data that fails to satisfy validation criteria. The computing platform may attach encryption rules to the remaining enterprise data. The computing platform may divide the enterprise data into discrete components and may continuously encrypt each component of the enterprise data using public keys. The computing platform may generate private keys that can be used to access the encrypted enterprise data, and may transmit the private keys to the enterprise organization. The computing platform, upon receipt of a private key from the enterprise organization, may determine whether the private key is authorized to access the encrypted enterprise data.

    PERFORMANCE MONITORING SYSTEM USING AGGREGATED TELEMETRY

    公开(公告)号:US20240160552A1

    公开(公告)日:2024-05-16

    申请号:US18508654

    申请日:2023-11-14

    CPC classification number: G06F11/3409 G06F11/3024

    Abstract: Systems, computer program products, and methods are described herein for performance monitoring using aggregated telemetry. The present disclosure is configured to receive, from the first performance monitoring engine, a first metadata associated with the first resiliency status; receive, from the second performance monitoring engine, a second metadata associated with the second resiliency status; determine, using a machine learning (ML) subsystem, an overall resiliency status of the device based on at least the first metadata, the second metadata, the first resiliency status, and the second resiliency status; determine one or more actions to be executed on the device, wherein the one or more actions are associated with the overall resiliency status; generate a notification indicating the overall resiliency status of the device and the one or more actions associated with the overall resiliency status; and transmit control signals configured to cause a user input device to display the notification.

    Virtual Machine Image Management System
    38.
    发明公开

    公开(公告)号:US20240143748A1

    公开(公告)日:2024-05-02

    申请号:US17978637

    申请日:2022-11-01

    CPC classification number: G06F21/554 G06F21/568

    Abstract: Virtual machine images may be constantly scanned using background process, to identify current and evolving security risks, such as by optimizing the image scanning a last-in, first-out (LIFO) stack to prioritize most relevant images. Older and/or non-relevant image are removed from the scanning process and removed from use. Virtual machines image prioritization is based on each virtual machine image's current and/or potential usage requirement, where the LIFO stack prioritizes the scanning order. Newly created virtual machine images and/or newly re-activated virtual machine images are placed onto a provisioning queue (first-in, first out) before activation. The virtual machine images active within a host computing environment are processed via a reconciliation process to scan for indications of security vulnerabilities and/or threats to network security. Obsolete or otherwise irrelevant virtual machine images are removed from use via a repository synchronization process.

    Incremental Image Import Process for Supporting Multiple Upstream Image Repositories

    公开(公告)号:US20240061667A1

    公开(公告)日:2024-02-22

    申请号:US17892754

    申请日:2022-08-22

    CPC classification number: G06F8/63 G06F8/71

    Abstract: Aspects of the disclosure are directed to importing software container images, where an image importer that may import a very large number of container images into local repositories from one or more upstream repositories to an enterprise container platform. An associated computing cluster executes containers (for example, applications and operators) based on the imported container images. Each release (version) of a product supported by the enterprise container platform may require importing newer image sets with respect to the current version. With one aspect, an image importer maintains an image list for container images of the current version, where only missing newer container images for a newer version are added to the list. Only the missing container images for the new version are imported to the enterprise container platform. This approach circumvents importing previously imported container and/or available newer images, thus reducing the amount of imported data from upstream repositories.

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