SYSTEM FOR MONITORING AND OPTIMIZING COMPUTING RESOURCE USAGE OF CLOUD BASED COMPUTING APPLICATION

    公开(公告)号:US20230043579A1

    公开(公告)日:2023-02-09

    申请号:US17395994

    申请日:2021-08-06

    IPC分类号: G06F9/50 G06F9/48 G06F11/34

    摘要: A system of monitoring and optimizing computing resources usage for computing application may include predicting a first performance metric for job load capacity of a computing application for optimal job concurrency and optimal resource utilization. The system may include generating an alerting threshold based on the first performance metric. The system may further include, in response to a difference between the alerting threshold and a job load of the computing application within an interval exceeding a threshold, predicting a second performance metric for job load capacity of the computing application for optimal job concurrency and optimal resource utilization. The system may further include, in response to a difference between the first performance metric and the second performance metric exceeding a difference threshold, updating the alerting threshold with a job load capacity with the optimal resource utilization rate corresponding to the second performance metric.

    ENHANCED APPLICATION PERFORMANCE FRAMEWORK

    公开(公告)号:US20220413992A1

    公开(公告)日:2022-12-29

    申请号:US17360472

    申请日:2021-06-28

    摘要: This document describes a framework for measuring and improving the performance of applications, such as distributed applications and web applications. In one aspect, a method includes performing a test on an application. The test includes executing the application on one or more computers and, while executing the application, simulating a set of workload scenarios for which performance of the application is measured during the test. While performing the test, a set of performance metrics that indicate performance of individual components involved in executing the application during the test is obtained. A knowledge graph is queried using the set of performance metrics. The knowledge graph links the individual components to corresponding performance metrics and defines a set of hotspot conditions that are each based on one or more of the corresponding performance metrics for the individual components. A given hotspot condition is detected based on the set of performance metrics.