Abstract: A computing system module facilitates designing a cloud computing services application that comprises multiple disparate cloud computing services available from multiple sources, vendors, or platforms. A description, in textual or verbal form, of desired functionality of the application is converted into a context vector. A trained supervised learning model having a number of nodes corresponding to a number of available computing services, analyzes the context vector and determines a relative probability for each node with respect to probability thresholds. The learning model identifies in a recommendation report that the application should include a service if a probability corresponding to the service satisfies a respective criterion. Edges may be determined from the context vector and analyzed by the learning model to determine an architecture of recommended services. The architecture may be rendered as a visual diagram based on the edges.

Abstract: A method includes identifying a first event that has been at least partly performed, wherein the first event comprises an element of a sequence of events, and the first event comprises performance of a first computing function, predicting a second event expected to occur next in the sequence after completion of the first event, and the second event comprises performance of a second computing function, predicting a start time of the second event, based on information about the second event, identifying a particular container capable of implementing the second computing function associated with the second event, predicting a start time for start-up of the container, starting up the container, and completing start-up of the container prior to receipt of a request for the second computing function to be performed by the container, wherein the container is ready to perform the second computing function immediately after start-up has been completed.

Abstract: A method includes identifying a first event that has been at least partly performed, wherein the first event comprises an element of a sequence of events, and the first event comprises performance of a first computing function, predicting a second event expected to occur next in the sequence after completion of the first event, and the second event comprises performance of a second computing function, predicting a start time of the second event, based on information about the second event, identifying a particular container capable of implementing the second computing function associated with the second event, predicting a start time for start-up of the container, starting up the container, and completing start-up of the container prior to receipt of a request for the second computing function to be performed by the container, wherein the container is ready to perform the second computing function immediately after start-up has been completed.