IP Library › Granted Patent US 12664015
Granted Patent B2
US 12664015 · App. 17/462,897 · Granted Jun 23, 2026

Container lifecycle management

Inventors: Nampreet Pal Singh (Pune, IN); Vishal Anand (Dublin, IE); Amit Deshpande (Pune, IN)
Assignee: International Business Machines Corporation
G06F9/485G06F9/5083
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Quick Facts
Patent No.
US 12664015
App. No.
17/462,897
Granted
Jun 23, 2026
Kind
B2
Abstract

A system may include a memory and a processor in communication with the memory. The processor may be configured to perform operations. The operations may include monitoring a container. The operations may further include identifying a usage variance of the container based on consumption information for the container. The operations may also include managing an uptime of the container based on the usage variance.

Claims (49)

1 . A system comprising:

a memory; and

a processor in communication with said memory, said processor being configured to perform operations, said operations comprising:

hosting a pod monitor on a container cluster;

monitoring a container in a pod with said pod monitor, wherein said container is hosted by said container cluster, and wherein said pod monitor monitors said container in said pod at a container level of granularity;

engaging in machine learning with said pod monitor to identify a usage variance of said container based on historical consumption information for said container;

managing, automatically with said pod monitor, a schedule of said container specific to said container based on said usage variance of said container; and

hibernating, automatically with said pod monitor, said container based on said schedule of said container, wherein said container is hibernated independent of said pod.

2 . The system of claim 1 , further comprising:

configuring said schedule of said usage variance.

3 . The system of claim 2 , wherein:

an uptime of said container aligns with said schedule.

4 . The system of claim 1 , further comprising:

detecting service requirements of said container.

5 . The system of claim 1 , wherein:

said container is in a first location and said pod monitor is in a second location.

6 . The system of claim 1 , further comprising:

injecting a custom configuration on said container.

7 . A method comprising:

hosting a pod monitor on a container cluster;

monitoring a container in a pod with said pod monitor, wherein said container is hosted on said container cluster, and wherein said pod monitor monitors said container in said pod at a container level of granularity;

engaging in machine learning with said pod monitor to identify a usage variance of said container based on historical resource consumption information for said container, wherein said usage variance is a difference of resource consumption of said container between a first time and a second time;

updating a control plane of said usage variance;

managing, automatically with said pod monitor, a schedule of said container specific to said container based on said usage variance of said container; and

hibernating, automatically with said pod monitor, said container based on said schedule of said container, wherein said container is hibernated independent of said pod.

8 . The method of claim 7 , further comprising:

configuring said schedule of said usage variance.

9 . The method of claim 8 , wherein:

an uptime of said container aligns with said schedule.

10 . The method of claim 7 , further comprising:

detecting service requirements of said container.

11 . The method of claim 7 , wherein:

said container is in a first location and said pod monitor is in a second location.

12 . The method of claim 7 , further comprising:

injecting a custom configuration on said container.

13 . A computer program product comprising a computer readable storage medium having program instructions embodied therewith, said program instructions executable by a processor to cause said processor to perform a function, said function comprising:

hosting a pod monitor on a container cluster;

monitoring a container in a pod with said pod monitor, wherein said container is hosted on said container cluster, and wherein said pod monitor monitors said container in said pod at a container level of granularity;

engaging in machine learning with said pod monitor to identify a usage variance of said container based on historical consumption information for said container;

managing, automatically with said pod monitor, a schedule of said container specific to said container based on said usage variance of said container; and

hibernating, automatically with said pod monitor, said container based on said schedule of said container, wherein said container is hibernated independent of said pod.

14 . The computer program product of claim 13 , further comprising:

configuring said schedule of said usage variance.

15 . The computer program product of claim 14 , wherein:

an uptime of said container aligns with said schedule.

16 . The computer program product of claim 13 , wherein:

said container is in a first location and said pod monitor is in a second location.

17 . The computer program product of claim 13 , further comprising:

injecting a custom configuration on said container.