Point-based license sharing
    5.
    发明授权

    公开(公告)号:US11238551B2

    公开(公告)日:2022-02-01

    申请号:US15823671

    申请日:2017-11-28

    摘要: Systems, methods and tools directed toward point-based license sharing mechanism that allows resource providers to dynamically control the computing resources each customer consumes by assigning point values to the license agreements between the customers and resource providers. Customers can select the amount of available points in a personalized license agreement and instead of using a “pay as you go” model, the customer upgrades and downgrades resources and services through point transfers which convert points into the resources Using the point-based conversions, customers have greater control over each license without inadvertently spending more money than expected on resources because the resources are limited to the available points in the license agreement, unless the licenses are purposefully upgraded by user. User licenses may offer flexible options to dynamically de-provision unused or unwanted resources back into available points for reallocation of new resources that may currently be more important to the user.

    INTELLIGENT ORCHESTRATION AND FLEXIBLE SCALE USING CONTAINERS FOR APPLICATION DEPLOYMENT AND ELASTIC SERVICE

    公开(公告)号:US20180205616A1

    公开(公告)日:2018-07-19

    申请号:US15408550

    申请日:2017-01-18

    摘要: Orchestrating flexible scaling for large scale deployment and elastic service of an application of a service model with an orchestration. The orchestration: analyzes input received from a user to generate feature references and a service definition of the application of the service model to be generated, extracts key features of the application of the service model from the feature references; analyzing the key features and service definition to generate a deployment configuration file with service dependencies required; and comparing the deployment configuration file to known strategy patterns. When a strategy pattern is not found that matches, analyzing the service definition and deployment configuration file to determine an applicable strategy pattern. The determined strategy pattern analyzed to determine a deployment strategy and entry point with deployment order according to monitored resource usage of the service model and deploying the application of the service model according to the deployment strategy.

    Generating program analysis rules based on coding standard documents

    公开(公告)号:US11023210B2

    公开(公告)日:2021-06-01

    申请号:US16358743

    申请日:2019-03-20

    摘要: In an approach to generating program analysis rules, one or more computer processors identify one or more unassociated code standard documents. The one or more computer processors feed the one or more unassociated code standard documents into a cognitive model, wherein the cognitive model utilizes one or more historical code standard documents based on the unassociated code standard documents and associated program analysis rules based on the unassociated code standard documents, wherein the historical code standard documents are natural language documents and the program analysis rules are programmatic. The one or more computer processors generate, based on one or more calculations by the cognitive model, one or more program analysis rules. The one or more computer processors correct one or more programmatic errors or one or more stylistic errors based on the generated one or more program analysis rules.

    Predictively provisioning cloud computing resources for virtual machines

    公开(公告)号:US10365944B2

    公开(公告)日:2019-07-30

    申请号:US16057885

    申请日:2018-08-08

    摘要: Methods, computer program products, and systems are presented. The methods include, for instance: predictively provisioning, by one or more processor, cloud computing resources of a cloud computing environment for at least one virtual machine; and initializing, by the one or more processor, the at least one virtual machine with the provisioned cloud computing resources of the cloud computing environment. In one embodiment, the predictively provisioning may include: receiving historical utilization information of multiple virtual machines of the cloud computing environment, the multiple virtual machines having similar characteristics to the at least one virtual machine; and determining the cloud computing resources for the at least one virtual machine using the historical utilization information of the multiple virtual machines. In another embodiment, the predictively may include updating a provisioning database with the historical utilization information of the multiple virtual machines of the cloud computing environment.