US 12,153,683 B2
Automated conditional update
William Trevor King, Olympia, WA (US); Douglas Richard Hellmann, Atlanta, GA (US); Scott C. Dodson, Raleigh, NC (US); Benjamin Michael Parees, Raleigh, NC (US); Lalatendu Shishusankar Mohanty, Boston, MA (US); and Vadim Pavlovich Rutkovsky, Brno (CZ)
Assigned to Red Hat, Inc., Raleigh, NC (US)
Filed by Red Hat, Inc., Raleigh, NC (US)
Filed on May 24, 2022, as Appl. No. 17/752,063.
Prior Publication US 2023/0385421 A1, Nov. 30, 2023
Int. Cl. G06F 15/16 (2006.01); G06F 8/65 (2018.01); G06F 21/57 (2013.01); G06N 20/00 (2019.01)
CPC G06F 21/577 (2013.01) [G06F 8/65 (2013.01); G06N 20/00 (2019.01)] 20 Claims
OG exemplary drawing
 
1. A method comprising:
obtaining health data from each of a plurality of clients, the health data including attributes of a respective one of the plurality of clients, a health status of the respective one of the plurality of clients, and a software version of the respective one of the plurality of clients;
determining, by a processing device, a conditional risk that is associated with at least one of the attributes that is detected to have an adverse reaction to the software version, in view of the health data; and
storing the conditional risk in memory, wherein the conditional risk that is associated with the at least one of the attributes that is detected to have the adverse reaction to the software version, the at least one of the attributes, and the software version are transmitted to a client for the client to determine whether to upgrade to the software version.