System for predicting memory resources and scheduling jobs in service-oriented architectures using database processors and a job ingestion processor

Abstract

A system comprising databases, database processors, a job ingestion processor, and a processor. The databases store job information for previously performed jobs. Each previously performed job comprises timestamp, job name, and amount of memory used information. The database processors detect changes to job information of the previously performed jobs and, in response, communicate the job information associated with the affected jobs to a job ingestion processor. The job ingestion processor parses the job information into timestamp, job name, and amount of memory used variables for each affected job. The parsed job information comprises timestamp values, job name values, and amount of memory used values. The processor stores the job information variables in a data log. The processor uses the job information variables to train a machine learning algorithm and the trained machine learning model to predict amounts of temporary memory needed to execute job requests.