Abstract: A discovery bundle component is applied in a virtual image deployed within a virtual environment, wherein the discovery bundle automatically discovers asset information about one or more application bundles applied to the virtual image. The discovery bundle component sends, to a discovery product service, the asset information wrapped with a trusted signed certificate for the discovery product service, wherein the discovery product service is located outside the virtual environment.

Abstract: A discovery bundle component is applied in a virtual image deployed within a virtual environment, wherein the discovery bundle automatically discovers asset information about one or more application bundles applied to the virtual image. The discovery bundle component sends, to a discovery product service, the asset information wrapped with a trusted signed certificate for the discovery product service, wherein the discovery product service is located outside the virtual environment.

Abstract: A discovery bundle component is applied in a virtual image deployed within a virtual environment, wherein the discovery bundle automatically discovers asset information about one or more application bundles applied to the virtual image. The discovery bundle component sends, to a discovery product service, the asset information wrapped with a trusted signed certificate for the discovery product service, wherein the discovery product service is located outside the virtual environment.

Abstract: A discovery bundle component is applied in a virtual image deployed within a virtual environment, wherein the discovery bundle automatically discovers asset information about one or more application bundles applied to the virtual image. The discovery bundle component sends, to a discovery product service, the asset information wrapped with a trusted signed certificate for the discovery product service, wherein the discovery product service is located outside the virtual environment.

Abstract: A technique for automating the construction of multiple virtual images with interdependencies includes creating a first virtual image (VI) instance by extending a first base VI based on input values associated with the first base VI and software bundles associated with the first base VI. A second VI instance is created by extending a second base VI based on input values associated with the second base VI, instance values received from the first VI instance, dependency instance values received from a deployed dependency instance, and software bundles associated with the second base VI. The first and second VI instances are then deployed to designated machines in a cloud environment for execution.

Abstract: A technique for automating the construction of multiple virtual images with interdependencies includes creating a first virtual image (VI) instance by extending a first base VI based on input values associated with the first base VI and software bundles associated with the first base VI. A second VI instance is created by extending a second base VI based on input values associated with the second base VI, instance values received from the first VI instance, dependency instance values received from a deployed dependency instance, and software bundles associated with the second base VI. The first and second VI instances are then deployed to designated machines in a cloud environment for execution.

Abstract: According to one aspect of the present disclosure a system and technique discovering and grouping related computing resources using machine learning is disclosed. The system includes a processor unit and logic executable by the processor unit to: receive a grouped unit of at least two configuration items of a computing environment; analyze the grouped unit to determine a correlation between the configuration items of the grouped unit; create a rule based on the determined correlation; apply the rule to the computing environment to identify another configuration item of the computing environment related to the configuration items of the grouped unit; and responsive to identifying another configuration item of the computing environment based on application of the rule, include the identified configuration item in the grouped unit.

Abstract: According to one aspect of the present disclosure, a method and technique for discovering a grouping related computing resources using machine learning is disclosed. The method includes: receiving, by a discovery engine executing on a processor unit, a grouped unit of at least two configuration items of a computing environment; analyzing, by the discovery engine, the grouped unit to determine a correlation between the configuration items of the grouped unit; automatically creating a rule, by the discovery engine, based on the determined correlation; applying the rule, by the discovery engine, to automatically identify another configuration item of the computing environment related to the configuration items of the grouped unit; and responsive to identifying another configuration item of the computing environment based on application of the rule, including the identified configuration item in the grouped unit.

Abstract: A method, computer program product, and system for defect closure is described. A method may allowing, via one or more computing devices, a user to define one or more parameters associated with a defect. The method may further comprise modifying, via the one or more computing devices, a care-value associated with the defect, as a function of time, based upon, at least in part, the one or more parameters defined by the user. The method may additionally comprise, in response to determining that the defect is unresolved after a configurable time period, closing, via the one or more computing devices, the defect.