Abstract:
It is determined whether a user is authorized to carry out a management operation on a plurality of information technology assets in parallel, based on a role of the user and at least one characteristic of the management operation. A risk level of the management operation, and at least one characteristic of the plurality of information technology assets, are both determined. Based on the risk level and the at least one characteristic of the plurality of information technology assets, an execution pattern for the management operation is specified. In at least some cases, the management operation is carried out on the plurality of information technology assets in parallel, in accordance with the execution pattern.
Abstract:
In a method for provisioning a virtual machine, a processor rates a plurality of software images that include a first software image and a second software image. A processor provisions the virtual machine with the first software image in a first state and the second software image in a second state, wherein the second software image is rated higher than the first software image.
Abstract:
A method for predicting a computerized service delivery organization workload including collecting data of a computer implementing service delivery routine including overlapping samples of load values, overlapping samples of performance values, overlapping samples of event outputs, ticket values and ticket volumes, building a first correlation of said load values with said performance values for predicting new performance values based on new data, building a second correlation of said performance values with said event outputs, said ticket values and said ticket volumes, combining said first and second correlations into a third correlation for correlating said load values with a ticket volume and an event volume, and determining at least one projected event volume or projected ticket volume value using said third correlation and at least one projected load value of said computer.
Abstract:
Aspects of the present invention disclose a method for color reconstruction of individual detected objects of an underwater image using a library of reference images. The method includes one or more processors obtaining image data of a computing device that includes an underwater image. The method further includes determining a depth measurement corresponding to the underwater image. The method further includes identifying an object of the underwater image based at least in part on a shape of the object. The method further includes reconstructing one or more colors of the object of the underwater image based at least in part on a reference image.
Abstract:
Managing network asset incidents by receiving historical network asset incident data, analyzing the historical network asset incident data to correlate incident occurrence, receiving real time network asset incident data, generating a list of network assets predicted to be affected by a real time incident, in response to receiving the real time network asset incident data, monitoring the list of network assets, and remediating a network incident for a listed network as set.
Abstract:
A method and associated system for patching virtual machines in L redundancy groups in accordance with a patching schedule. The patching schedule is generated by scheduling, in W sequential time windows, P patches applicable to the virtual machines. Each redundancy group includes virtual machines and independently belongs to a respective software application x of X software applications, wherein P≧1, L≧1, Rm≧1, and X≧1. The L redundancy groups collectively comprise at least 2 virtual machines. The scheduling determines xwmk for T tuples (w, m, k) defined by (w=1, . . . , W) and (m=1, . . . , L) and (k=1, . . . , Rm), by maximizing an objective function subject to constraints. Determining xwmk includes setting xwmk=1 if virtual machine k in redundancy group m is to be patched in time window w or setting xwmk=0 otherwise.
Abstract:
It is determined whether a user is authorized to carry out a management operation on a plurality of information technology assets in parallel, based on a role of the user and at least one characteristic of the management operation. A risk level of the management operation, and at least one characteristic of the plurality of information technology assets, are both determined. Based on the risk level and the at least one characteristic of the plurality of information technology assets, an execution pattern for the management operation is specified. In at least some cases, the management operation is carried out on the plurality of information technology assets in parallel, in accordance with the execution pattern.
Abstract:
Managing network asset incidents by receiving historical network asset incident data, analyzing the historical network asset incident data to correlate incident occurrence, receiving real time network asset incident data, generating a list of network assets predicted to be affected by a real time incident, in response to receiving the real time network asset incident data, monitoring the list of network assets, and remediating a network incident for a listed network asset.
Abstract:
Aspects of the present invention disclose a method for color reconstruction of individual detected objects of an underwater image using a library of reference images. The method includes one or more processors obtaining image data of a computing device that includes an underwater image. The method further includes determining a depth measurement corresponding to the underwater image. The method further includes identifying an object of the underwater image based at least in part on a shape of the object. The method further includes reconstructing one or more colors of the object of the underwater image based at least in part on a reference image.
Abstract:
A method for predicting a computerized service delivery organization workload including collecting data of a computer implementing service delivery routine including overlapping samples of load values, overlapping samples of performance values, overlapping samples of event outputs, ticket values and ticket volumes, building a first correlation of said load values with said performance values for predicting new performance values based on new data, building a second correlation of said performance values with said event outputs, said ticket values and said ticket volumes, combining said first and second correlations into a third correlation for correlating said load values with a ticket volume and an event volume, and determining at least one projected event volume or projected ticket volume value using said third correlation and at least one projected load value of said computer.