Dynamic re-composition of patch groups using stream clustering

    公开(公告)号:GB2582460B

    公开(公告)日:2021-01-20

    申请号:GB202006140

    申请日:2018-09-25

    Applicant: IBM

    Abstract: Techniques for dynamic server groups that can be patched together using stream clustering algorithms, and learning components in order to reuse the repeatable patterns using machine learning are provided herein. In one example, in response to a first risk associated with a first server device, a risk assessment component patches a server group to mitigate a vulnerability of the first server device and a second server device, wherein the server group is comprised of the first server device and the second server device. Additionally, a monitoring component monitors data associated with a second risk to the server group to mitigate the second risk to the server group.

    Patch management in a hybrid computing environment

    公开(公告)号:GB2593657A

    公开(公告)日:2021-09-29

    申请号:GB202110941

    申请日:2020-01-22

    Applicant: IBM

    Abstract: Techniques for managing performing patches on a workload associated with a computing platform are presented. A patch identifier component can identify the workload associated with the computing platform. The workload can comprise a first workload portion upon which a first subset of patches can be performed offline and a second workload portion upon which a second subset of patches can be performed online. A patch management component can determine, for the first workload portion, a portion of the first subset of patches that can be performed within a maintenance time window while offline based on vulnerability scores of patches of the first subset of patches, and can determine, for the second workload portion, the second subset of patches that can be performed while online. The patch management component can determine the vulnerability scores of the patches of the first subset of patches based on importance levels of the patches.

    Dynamic re-composition of patch groups using stream clustering

    公开(公告)号:GB2582460A

    公开(公告)日:2020-09-23

    申请号:GB202006140

    申请日:2018-09-25

    Applicant: IBM

    Abstract: Techniques for dynamic server groups that can be patched together using stream clustering algorithms, and learning components in order to reuse the repeatable patterns using machine learning are provided herein. In one example, in response to a first risk associated with a first server device, a risk assessment component patches a server group to mitigate a vulnerability of the first server device and a second server device, wherein the server group is comprised of the first server device and the second server device. Additionally, a monitoring component monitors data associated with a second risk to the server group to mitigate the second risk to the server group.

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