Patent ID: 11966775
Assignee: SAP SE
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 0:
1. A computer-implemented method comprising:
receiving, by a cloud computing environment, a request to execute a job;
determining computing resources available to execute the job;
classifying the job as either new or recurring;
performing a first process flow responsive to classifying the job as new; and
performing a second process flow responsive to classifying the job as recurring,
wherein the first process flow includes:
creating a new job meta record for the job;
scheduling the job to be executed; and
monitoring resource usage metrics during execution of the job and adding the resource usage metrics to the new job meta record, and wherein the second process flow includes:
processing pre-existing job metadata information characterizing aspects of the job including at least one of a job tracker ID, frequency, job type, schedule time or the resource usage metrics for the job, the processing of the pre-existing job metadata information including retrieving historical computing resource consumption information for the job;
determining whether a job type of the job is seasonal or non-seasonal based on attributes of the job identified by parsing the pre-existing job metadata information, wherein seasonal jobs have a higher frequency of execution over non-seasonal jobs;
generating, using an ensemble model (seasonal autoregressive integrated moving average (S)ARIMA model) that combines an autoregressive moving average (ARMA) model and an autoregressive integrated moving average (ARIMA) model, a resource prediction characterizing resources to be consumed when executing the job based on the determined computing resources and the retrieved historical information, wherein a (S)ARIMA predictor is selected to be used to apply the (S)ARIMA model to estimate the resources to be consumed if the job type is determined to be seasonal and an ARIMA predictor is selected to be used to apply the ARIMA model to estimate the resources to be consumed if the job type is determined to be non-seasonal;
scheduling execution of the job by the cloud computing environment based on the generated resource prediction and the available computing resources to allocate capacity for the job in the cloud computing environment; and
executing, by the cloud computing environment, the job in accordance with the scheduled execution.