Determining an optimal computing environment for running an image based on performance of similar images

摘要

Aspects of the present invention provide an approach that evaluates a locally running image (e.g., such as that for a virtual machine (VM)) and determines if that image could run more efficiently and/or more effectively in an alternate computing environment (e.g., a cloud computing environment). Specifically, embodiments of the present invention evaluate the local (existing/target) image's actual and perceived performance, as well as the anticipated/potential performance if the image were to be migrated to an alternate environment. The anticipated/potential performance can be measured based on another image that is similar to the existing/target image but where that image is running in a different computing environment. Regardless, the system would display a recommendation to the end user if it were determined that the image could perform better in the alternate environment (or vice versa).

主权项

1. A method for determining an optimal computing environment for running an image, comprising:
registering a set of images with a registry service, each of the set of images running in a respective computing environment; measuring an existing performance of a current image running in a current computing environment based on performance metrics comprising at least one of: processing speed, storage capacity, response time, or latency; identifying a plurality of images similar to the current image from the set of images; receiving at least one rating based on user experience relating to actual performance of the plurality of images similar to the current image as the plurality of images are running in each of their respective computing environment; measuring a potential performance of the plurality of images as running in each of their respective computing environments based on the at least one rating and historical performance data; comparing the potential performance of the plurality of images in each computing environment to the existing performance of the current image based on the performance metrics as weighted by the user; ranking the current computing environment and the respective computing environments for running the current image based on the comparison; and determining an optimal computing environment for running the current image based on the ranking; and running the current image in the optimal computing environment.