The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Apr. 19, 2022

Filed:

Nov. 07, 2019
Applicant:

Salesforce.com, Inc., San Francisco, CA (US);

Inventors:

Ashraya Raj Mathur, Fremont, CA (US);

Bruno Manuel Torres Gomez, San Francisco, CA (US);

Ronnie Fong, San Mateo, CA (US);

Steven Bougon, San Francisco, CA (US);

Jiten Oswal, San Francisco, CA (US);

Mihirsinh Raol, Fremont, CA (US);

Jianxun Jason Ding, Cupertino, CA (US);

Assignee:

salesforce.com, inc., San Francisco, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06F 11/34 (2006.01); G06F 11/30 (2006.01); G06F 11/32 (2006.01); G06F 9/50 (2006.01);
U.S. Cl.
CPC ...
G06F 11/3457 (2013.01); G06F 9/505 (2013.01); G06F 11/301 (2013.01); G06F 11/323 (2013.01); G06F 11/3442 (2013.01);
Abstract

Systems and methods for an elastic cost-to-serve system including a first module to orchestrate an elastic server set; a second module to orchestrate a load test and to apply one or more use-case scenarios for each orchestrated server set; a third module to generate a cost metrics model of the orchestrated server set for predictive cost modeling; a fourth module coupled to the third module to collect a plurality of performance metrics across the server resources and associated client devices; a fifth module to post-process the collected performance metrics across a load testing duration and to provide analytics of the server set performance; and a sixth module coupled to analyze the performance metrics adapting available resources and to apply a heuristic of the cost metrics model to predict a model of cost optimization of the server set.


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