Dynamically assigning storage objects to compartment constructs of a storage system to reduce application risk

    公开(公告)号:US12056353B2

    公开(公告)日:2024-08-06

    申请号:US18093267

    申请日:2023-01-04

    Applicant: Kyndryl, Inc.

    CPC classification number: G06F3/0604 G06F3/0614 G06F3/0644 G06F3/067

    Abstract: A computer-implemented method, according to one embodiment, includes logically partitioning a storage system into a plurality of compartment constructs, and mapping hosts in communication with the storage system to the compartment constructs, thereby enabling interoperability among the hosts and the compartment constructs. The interoperability of the hosts and the compartment constructs is analyzed, and the interoperability is based on storage software and/or firmware versions being run by the hosts. The method further includes defining, based on the analysis, risk profiles for applications run on the hosts, and determining, based on the risk profiles, recommendations for assignment and mapping of the hosts with the compartment constructs. Ownership of storage objects is assigned to the compartment constructs based on the recommendations. Each of the storage objects define a logical partition of one of the hosts and a logical partition of a storage volume of the storage system.

    DYNAMICALLY ASSIGNING STORAGE OBJECTS TO COMPARTMENT CONSTRUCTS OF A STORAGE SYSTEM TO REDUCE APPLICATION RISK

    公开(公告)号:US20240220102A1

    公开(公告)日:2024-07-04

    申请号:US18093267

    申请日:2023-01-04

    Applicant: Kyndryl, Inc.

    CPC classification number: G06F3/0604 G06F3/0614 G06F3/0644 G06F3/067

    Abstract: A computer-implemented method, according to one embodiment, includes logically partitioning a storage system into a plurality of compartment constructs, and mapping hosts in communication with the storage system to the compartment constructs, thereby enabling interoperability among the hosts and the compartment constructs. The interoperability of the hosts and the compartment constructs is analyzed, and the interoperability is based on storage software and/or firmware versions being run by the hosts. The method further includes defining, based on the analysis, risk profiles for applications run on the hosts, and determining, based on the risk profiles, recommendations for assignment and mapping of the hosts with the compartment constructs. Ownership of storage objects is assigned to the compartment constructs based on the recommendations. Each of the storage objects define a logical partition of one of the hosts and a logical partition of a storage volume of the storage system.

    Noisy-neighbor detection and remediation

    公开(公告)号:US11928518B2

    公开(公告)日:2024-03-12

    申请号:US17398196

    申请日:2021-08-10

    Applicant: KYNDRYL, INC.

    Abstract: Noisy-neighbor detection and remediation is provided by performing real-time monitoring of workload processing and associated resource consumption of application components that use shared resource(s) of a computing environment, determining workload and shared resource consumption patterns for each of the application components, for each application, of a plurality of applications, that includes at least one application component of the application components, correlating the determined workload and shared resource consumption patterns of each of those application component(s) and determining a correlated shared resource usage pattern for that application, performing impact analysis to determine impact of the applications on each other, and identifying noisy-neighbor(s) that use the one or more shared resources and automatically raising an alert indicating those noisy-neighbor(s).

    Analytics-driven direction for computer storage subsystem device behavior

    公开(公告)号:US11436145B1

    公开(公告)日:2022-09-06

    申请号:US17301290

    申请日:2021-03-30

    Applicant: KYNDRYL, INC.

    Abstract: A computer directs activity within a computer storage subsystem. The computer identifies a computer operating environment including a computer, and a storage subsystem connected to a group of storage devices. The compute receives metadata representing current and historic performance metrics of said computer operating environment. The computer identifies a first device associated with a first behavior profile governed by a power law distribution, and a second device associated with a second behavior profile governed by a normal distribution. The computer trains Machine Learning (ML) models based on the behavior profiles. The computer establishes Device Performance Rules based on the ML models. The computer forecasts time-based storage system requirements based, at least in part on the Device Performance Rules. The computer prefetches data to a cache component based, at least in part on said forecasted system requirements, in accordance with a time reference available to said computer.

    Cognitive data protection and disaster recovery policy management

    公开(公告)号:US11329896B1

    公开(公告)日:2022-05-10

    申请号:US17173250

    申请日:2021-02-11

    Applicant: KYNDRYL, INC.

    Abstract: An embodiment for cognitively aligning data protection (DP) and disaster recovery (DR) policies is provided. The embodiment may include ingesting a variety of data associated with one or more applications into a repository. The embodiment may also include executing differential analysis on the data and changes to the data to identify differences between the data and the changes to the data. The changes to the data may be obtained by periodically polling internal and external data sources. The embodiment may also include translating the differences between the data and the changes to the data into an updated SLA. The embodiment may further include in response to determining that the differences between the data and the changes to the data warrant a change in the current DP and DR policies, generating one or more recommendations to modify the current DP and DR policies and/or create new DP and DR policies.

    Data analytics for mitigation of data center thermal issues

    公开(公告)号:US11644876B2

    公开(公告)日:2023-05-09

    申请号:US17301378

    申请日:2021-03-31

    Applicant: KYNDRYL, INC.

    CPC classification number: G06F1/206 H05K7/20709

    Abstract: Mitigating the impact of data center thermal environmental issues on production applications includes retrieving, by a computer, from a centralized repository first data corresponding to I/O and processing activities of an infrastructure component executing one or more applications, second data corresponding to an application-to-infrastructure map, and third data corresponding to a business priority of the one or more applications. Based on the first data and the second data, the one or more applications are mapped to heat generation values of the infrastructure component, and based on the mapping a thermal load of the one or more applications on the infrastructure component is determined using data analytics. Using the third data, the computer identifies an execution priority for the one or more applications, generates a correlative mapping between the execution priority and the thermal load of the one or more applications, and generates a resolution plan based on the correlative mapping.

    Provenance based identification of policy deviations in cloud computing environments

    公开(公告)号:US11553005B1

    公开(公告)日:2023-01-10

    申请号:US17351737

    申请日:2021-06-18

    Applicant: Kyndryl, Inc.

    Abstract: Policy deviations for distributed computing environments are detected and recorded an immutable ledger of transaction provenance from end to end transactions performed in the distributed computing environment. From the immutable ledger, persona data for transaction types is plotted as an bipartite graph. Edge weights of the bipartite graphs are correlated to trust levels between personas from the persona data and the transaction types from the immutable ledger. Trust levels from the edge weights are correlated to rules illustrating when the transaction provenance indicate a policy deviation in the distributed computing environment. The rules are then employed to detect in real time end to end provenance when a policy deviation in the distributed computing environment is occurring. An alert of policy deviations may be sent to stakeholders for the distributed computing environment.

    DATA ANALYTICS FOR MITIGATION OF DATA CENTER THERMAL ISSUES

    公开(公告)号:US20220317744A1

    公开(公告)日:2022-10-06

    申请号:US17301378

    申请日:2021-03-31

    Applicant: KYNDRYL, INC.

    Abstract: Mitigating the impact of data center thermal environmental issues on production applications includes retrieving, by a computer, from a centralized repository first data corresponding to I/O and processing activities of an infrastructure component executing one or more applications, second data corresponding to an application-to-infrastructure map, and third data corresponding to a business priority of the one or more applications. Based on the first data and the second data, the one or more applications are mapped to heat generation values of the infrastructure component, and based on the mapping a thermal load of the one or more applications on the infrastructure component is determined using data analytics. Using the third data, the computer identifies an execution priority for the one or more applications, generates a correlative mapping between the execution priority and the thermal load of the one or more applications, and generates a resolution plan based on the correlative mapping.

Patent Agency Ranking