US 12,008,411 B2
Dynamic container-based application resource tuning and resizing
Benjamin M. Parees, Raleigh, NC (US); Gabriel G. Montero, Raleigh, NC (US); and Cesar A. Wong, Raleigh, NC (US)
Assigned to Red Hat, Inc., Raleigh, NC (US)
Filed by Red Hat, Inc., Raleigh, NC (US)
Filed on Apr. 5, 2021, as Appl. No. 17/222,165.
Application 17/222,165 is a continuation of application No. 15/825,784, filed on Nov. 29, 2017, granted, now 10,996,991.
Prior Publication US 2021/0224131 A1, Jul. 22, 2021
This patent is subject to a terminal disclaimer.
Int. Cl. G06F 9/50 (2006.01); G06F 9/48 (2006.01)
CPC G06F 9/5055 (2013.01) [G06F 9/4881 (2013.01); G06F 9/5016 (2013.01)] 19 Claims
OG exemplary drawing
 
1. A method comprising:
generating, by a computing device comprising a processor device, cgroup data to associate one or more container resource constraint values with a first container;
initiating, by the computing device, the first container with the one or more container resource constraint values, the first container comprising a tuner;
prior to initiating a first application execution of an application, querying, by the tuner, the cgroup data to determine the one or more container resource constraint values, wherein the one or more container resource constraint values indicate a corresponding one or more limits on computing resource usage by the first container;
translating, by the tuner, the one or more container resource constraint values into one or more application resource constraint values;
initiating, by the tuner, the first application execution of the application in the first container;
providing, by the tuner, the one or more application resource constraint values to the first application execution;
performing an analysis of a plurality of resource usage metrics generated during the first application execution of the application, each resource usage metric quantifying a use of a corresponding computing resource associated with the first container during the first application execution; and
determining one or more optimized container resource constraint values based on the analysis.