US 12,445,530 B2
Microservice throttling based on learned demand predictions
Abhinay Nagpal, Fremont, CA (US); and Sujeet Mishra, Fremont, CA (US)
Assigned to Nutanix, Inc., San Jose, CA (US)
Filed by Nutanix, Inc., San Jose, CA (US)
Filed on Mar. 26, 2024, as Appl. No. 18/617,003.
Application 18/617,003 is a continuation of application No. 18/103,770, filed on Jan. 31, 2023, granted, now 11,973,839.
Claims priority of provisional application 63/478,043, filed on Dec. 30, 2022.
Prior Publication US 2024/0388640 A1, Nov. 21, 2024
Int. Cl. H04L 47/12 (2022.01); H04L 41/16 (2022.01); H04L 43/08 (2022.01); H04L 47/20 (2022.01); H04L 67/10 (2022.01); H04L 67/51 (2022.01)
CPC H04L 67/51 (2022.05) [H04L 41/16 (2013.01); H04L 43/08 (2013.01); H04L 47/20 (2013.01)] 29 Claims
OG exemplary drawing
 
1. A non-transitory computer readable medium having stored thereon a sequence of instructions which, when executed by a processor cause a set of acts comprising:
monitoring a system having a plurality of microservices;
determining that at least one of the plurality of microservices are to be throttled;
generating short-term and long-term demand predictions for the plurality of microservices; and
analyzing at least the short-term and long-term demand predictions to identify a microservice of the plurality of microservices to throttle, wherein respective long-term demand predictions correspond to a first time range that is longer than a second time range of a corresponding short-term demand predictions.