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.

    Compliance-aware runtime generation based on application patterns and risk assessment

    公开(公告)号:GB2578066B

    公开(公告)日:2022-02-16

    申请号:GB202000336

    申请日:2018-06-18

    Applicant: IBM

    Abstract: Systems, computer-implemented methods and/or computer program products that facilitate compliance-aware runtime generation of containers are provided. In one embodiment, a computer-implemented method comprises: identifying, by a system operatively coupled to a processor, information used by a target application to containerize; determining whether one or more risk violations exist for the information within one or more defined thresholds; determining whether a compliance or a security violation exists in the information, wherein the determining whether the compliance or security violation exists is performed based on a determination by the risk assessment component that one or more risk violations do not exist; and generating a new container of components corresponding to defined components of the target application that allow the target application to execute without an underlying operating system, wherein the generating is based on a determination that no compliance or security violation exists in the information.

    Dynamic automation of selection of pipeline artifacts

    公开(公告)号:IL297210B1

    公开(公告)日:2025-03-01

    申请号:IL29721022

    申请日:2022-10-11

    Abstract: An artificial intelligence (AI) platform to support a continuous integration and deployment (CI/CD) pipeline for software development and operations (DevOps). One or more dependency graphs are generated based on application artifacts. A machine learning (ML) model is leveraged to capture a relationship between components in the dependency graph(s) and one or more pipeline artifacts. Responsive a change of an application artifact, the captured relationship is leveraged to identify an impact of the detected change on the pipeline artifact(s). The CI/CD pipeline is selectively optimized and executed based on the identified impact to improve the efficiency of the pipeline and the deployment time.

    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.

    Compliance-aware runtime generation based on application patterns and risk assessment

    公开(公告)号:GB2578066A

    公开(公告)日:2020-04-15

    申请号:GB202000336

    申请日:2018-06-18

    Applicant: IBM

    Abstract: Systems, computer-implemented methods and/or computer program products that facilitate compliance-aware runtime generation of containers are provided. In one embodiment, a computer-implemented method comprises: identifying, by a system operatively coupled to a processor, information used by a target application to containerize; determining whether one or more risk violations exist for the information within one or more defined thresholds; determining whether a compliance or a security violation exists in the information, wherein the determining whether the compliance or security violation exists is performed based on a determination by the risk assessment component that one or more risk violations do not exist; and generating a new container of components corresponding to defined components of the target application that allow the target application to execute without an underlying operating system, wherein the generating is based on a determination that no compliance or security violation exists in the information.

    Microservice decomposition strategy of monolithic applications

    公开(公告)号:GB2607528A

    公开(公告)日:2022-12-07

    申请号:GB202212227

    申请日:2021-01-18

    Applicant: IBM

    Abstract: Systems and techniques that facilitate automated recommendation of microservice decomposition strategies for monolithic applications are provided. In various embodiments, a community detection component can detect a disjoint code cluster in a monolithic application based on a code property graph characterizing the monolithic application. In various aspects, the code property graph can be based on a temporal code evolution of the monolithic application. In various embodiments, a topic modeling component can identify a functional purpose of the disjoint code cluster based on a business document corpus corresponding to the monolithic application. In various embodiments, a microservice component can recommend a microservice to replace the disjoint code cluster based on the functional purpose.

    Dynamic automation of selection of pipeline artifacts

    公开(公告)号:IL297210A

    公开(公告)日:2022-12-01

    申请号:IL29721022

    申请日:2022-10-11

    Abstract: An artificial intelligence (AI) platform to support a continuous integration and deployment (CI/CD) pipeline for software development and operations (DevOps). One or more dependency graphs are generated based on application artifacts. A machine learning (ML) model is leveraged to capture a relationship between components in the dependency graph(s) and one or more pipeline artifacts. Responsive a change of an application artifact, the captured relationship is leveraged to identify an impact of the detected change on the pipeline artifact(s). The CI/CD pipeline is selectively optimized and executed based on the identified impact to improve the efficiency of the pipeline and the deployment time.

    Method and system to identify and prioritize re-factoring to improve micro-service identification

    公开(公告)号:GB2600554A

    公开(公告)日:2022-05-04

    申请号:GB202113987

    申请日:2021-09-30

    Applicant: IBM

    Abstract: A computer system wherein there is a genetic manager to apply a genetic algorithm to parent re-factoring operations selected from an initial identified set of such operations for source code to produce an offspring population of the operations as a subset of the parent re-factoring operations. A score manager measures a fitness score of each re-factoring operation including collecting runtime traces of the source code and applies the traces to the subset such that a classifier can prioritise operations within the subset based on a corresponding fitness score. Responsive to the prioritisation one or more of the re-factoring operations can be applied to the source code to produce one or more micro-service candidates. A crossover operator may be applied to generate a combination of offspring re-factoring operations, and a mutation operator may be applied to introduce variability to the generated combination. The application of the genetic algorithm and fitness score measurement may be an iterative process wherein an operation is selected as the next parent re-factoring operation on an objective factor and iteratively applied to the process.

Patent Agency Ranking