View source for US Patent Application 18366200. TESTING OF A RESOURCE MANAGER OF AN APPLICATION MANAGEMENT SYSTEM simplified abstract

=TESTING OF A RESOURCE MANAGER OF AN APPLICATION MANAGEMENT SYSTEM=


==Organization Name==

[[:Category:Microsoft Technology Licensing, LLC|Microsoft Technology Licensing, LLC]]


[[Category:Microsoft Technology Licensing, LLC]]==Inventor(s)==

[[Category:[[:Category:Justin G. Moeller of Eden Prairie MN (US)|Justin G. Moeller of Eden Prairie MN (US)]]]]

[[Category:[[:Category:Willis Lang of Edina MN (US)|Willis Lang of Edina MN (US)]]]]

==TESTING OF A RESOURCE MANAGER OF AN APPLICATION MANAGEMENT SYSTEM - A simplified explanation of the abstract==


This abstract first appeared for US patent application 18366200 titled 'TESTING OF A RESOURCE MANAGER OF AN APPLICATION MANAGEMENT SYSTEM

==Simplified Explanation==

The patent application describes testing methods and systems for a resource manager in an application management system.
* Load orchestrator obtains an artificial metric based on a utilization model.
* The artificial metric is transmitted to applications in a computing node cluster.
* Applications transmit the artificial metric to the resource manager.
* The resource manager generates control output for managing applications based on the artificial metric.
* The utilization model includes executable code for generating artificial metric values.
* The model may be received through an API call.
* The load orchestrator can be instantiated in an orchestration framework or in each node of the cluster.


==Original Abstract Submitted==

Testing methods and systems are provided for testing a resource manager of an application management system. The testing systems include a load orchestrator configured to obtain an artificial metric that is determined based on a utilization model (e.g., CPU usage, memory allocation, or disk usage, number of webserver sessions). The load orchestrator transmits the artificial metric to applications in a cluster of computing nodes. The applications transmit the artificial metric to the resource manager. In response, the resource manager generates control output for managing applications in the cluster based on the artificial metric (e.g., scaling, load balancing, application placement, failover of applications, or defragmenting data). The utilization model may include executable code for generating artificial metric values. The model may be received as a result of an API call. The load orchestrator may be instantiated in an orchestration framework or in each node of the cluster.



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