IP Library Granted Patent US 12,499,002
Granted Patent B2
US 12,499,002 · App. 18/367,114 · Granted Dec 16, 2025

Anomaly detection during cloud application installation

Inventors: Ying Mo (Beijing, CN); Guangya Liu (Cary, NC); Xiaoli Duan (Beijing, CN); Hou Fang Zhao (Beijing, CN); Yan Wei Li (Beijing, CN); Zhi Li (Beijing, CN); Yao Chen (Beijing, CN)
Assignee: International Business Machines Corporation
G06F11/0775G06F11/0751G06F11/0757G06F11/076G06F11/323
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Quick Facts
Patent No.
US 12,499,002
App. No.
18/367,114
Granted
Dec 16, 2025
Kind
B2
Abstract

A method, system, and computer program product that are configured to: create a resource dependency graph that defines dependencies between resources created in an installation of a cloud native application, wherein the resource dependency graph includes a respective time range of each respective one of the resources; for each respective one of the resources, determine a condition of the respective one of the resources based on the respective time range of the respective one of the resources, a success condition of the respective one of the resources, and one or more failure conditions of the respective one of the resources; and create a cause analysis resource that includes the determined condition of each respective one of the resources.

Claims (60)

1 . A computer-implemented method, comprising:

initiating an installation of a cloud native application;

monitoring, by an operator in a container orchestration system, the installation of the cloud native application in a cluster;

creating, by the operator, a resource dependency graph that defines dependencies between resources created in the installation of the cloud native application, wherein the resource dependency graph includes a respective time range of each respective one of the resources;

for each respective one of the resources, determining, by the operator, a condition of the respective one of the resources based on the respective time range of the respective one of the resources, a success condition of the respective one of the resources, and one or more failure conditions of the respective one of the resources; and

creating, by the operator, a cause analysis resource that includes the determined condition of each respective one of the resources.

2 . The computer-implemented method of claim 1 , wherein the determined condition of each respective one of the resources comprises one of success, failure, and pending.

3 . The computer-implemented method of claim 1 , wherein the success condition of the respective one of the resources and the one or more failure conditions of the respective one of the resources are defined in a resource condition definition of the respective one of the resources.

4 . The computer-implemented method of claim 1 , wherein the one or more failure conditions comprise at least one selected from a group consisting of:

failure conditions with clear cause;

failure conditions without clear cause; and

errors in workload logs with clear cause.

5 . The computer-implemented method of claim 1 , wherein the respective time range of a respective one of the resources comprises:

a first time range that defines when the respective one of the resources is expected to be created relative to a base resource; and

a second time range that defines when the respective one of the resources is expected to be ready after it has been created.

6 . The computer-implemented method of claim 5 , further comprising determining a minimum and maximum for the first time range and a minimum and maximum for the second time range using models.

7 . The computer-implemented method of claim 6 , further comprising training the models using data of historic installations of the cloud native application.

8 . The computer-implemented method of claim 1 , further comprising:

creating a visualization using the cause analysis resource, wherein the visualization includes: the resources arranged in a diagram that shows the dependencies between the resources; and the determined condition for each of the resources; and

presenting the visualization via a user interface of a computer device.

9 . A computer program product comprising one or more computer readable storage media having program instructions collectively stored on the one or more computer readable storage media, the program instructions executable to:

initiate an installation of a cloud native application;

monitor, by an operator that is an extension of an application programming interface in a container orchestration system, the installation of the cloud native application in a cluster during the installation of the cloud native application;

create, by the operator, a resource dependency graph that defines dependencies between resources created in the installation of the cloud native application, wherein the resource dependency graph includes a respective time range of each respective one of the resources;

for each respective one of the resources, determine, by the operator, a condition of the respective one of the resources based on the respective time range of the respective one of the resources, a success condition of the respective one of the resources, and one or more failure conditions of the respective one of the resources;

create, by the operator, a cause analysis resource that includes the determined condition of each respective one of the resources; and

provide status updates to a user in real time during the installation of the cloud native application by:

creating a visualization, in real time during the installation of the cloud native application, using the cause analysis resource, wherein the visualization includes: the resources arranged in a diagram that shows the dependencies between the resources; and

the determined condition for each of the resources; and

providing the visualization to the user via a user interface of a computer device in real time during the installation of the cloud native application.

10 . The computer program product of claim 9 , wherein the determined condition of each respective one of the resources comprises one of success, failure, and pending.

11 . The computer program product of claim 9 , wherein the success condition of the respective one of the resources and the one or more failure conditions of the respective one of the resources are defined in a resource condition definition of the respective one of the resources.

12 . The computer program product of claim 9 , wherein the one or more failure conditions comprise at least one selected from a group consisting of:

failure conditions with clear cause;

failure conditions without clear cause; and

errors in workload logs with clear cause.

13 . The computer program product of claim 9 , wherein the respective time range of a respective one of the resources comprises:

a first time range that defines when the respective one of the resources is expected to be created relative to a base resource; and

a second time range that defines when the respective one of the resources is expected to be ready after it has been created.

14 . A system comprising:

a processor set, one or more computer readable storage media, and program instructions collectively stored on the one or more computer readable storage media, the program instructions executable to:

initiate an installation of a cloud native application;

monitor, by an operator in a container orchestration system, the installation of the cloud native application in a cluster, wherein the operator is an extension of an application programming interface and uses custom resources to manage one or more applications in the cluster;

create, by the operator, a resource dependency graph that defines dependencies between resources created in the installation of the cloud native application, wherein the resource dependency graph includes a respective time range of each respective one of the resources;

for each respective one of the resources, determine, by the operator, a condition of the respective one of the resources based on the respective time range of the respective one of the resources, a success condition of the respective one of the resources, and one or more failure conditions of the respective one of the resources;

create, by the operator, a cause analysis resource that includes the determined condition of each respective one of the resources;

determine a minimum and maximum for the respective time range using a trained and dynamically updated machine learning model; wherein the program instructions are executable to train the machine learning model using data of historic installations of the cloud native application to improve the accuracy of the respective time range, and thereby reduce false anomalies; and

provide status updates to a user in real time during the installation of the cloud native application, wherein the status updates are based on the cause analysis resource and include notifying the user of a failure of a respective one the resources without waiting a full installation time of the cloud native application.

15 . The system of claim 14 , wherein the determined condition of each respective one of the resources comprises one of success, failure, and pending.

16 . The system of claim 14 , wherein the success condition of the respective one of the resources and the one or more failure conditions of the respective one of the resources are defined in a resource condition definition of the respective one of the resources.

17 . The system of claim 14 , wherein the one or more failure conditions comprise at least one selected from a group consisting of:

failure conditions with clear cause;

failure conditions without clear cause; and

errors in workload logs with clear cause.

18 . The system of claim 14 , wherein the respective time range of a respective one of the resources comprises:

a first time range that defines when the respective one of the resources is expected to be created relative to a base resource; and

a second time range that defines when the respective one of the resources is expected to be ready after it has been created.

19 . The system of claim 14 , wherein the program instructions are executable to create a visualization using the cause analysis resource, wherein the visualization includes:

the resources arranged in a diagram that shows the dependencies between the resources; and

the determined condition for each of the resources.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Sep 12, 2023
From: MO, YING; LIU, GUANGYA; DUAN, XIAOLI; ZHAO, HOU FANG; LI, YAN WEI; LI, ZHI; CHEN, YAO
To: INTERNATIONAL BUSINESS MACHINES CORPORATION
Reel/Frame 064876/0064 →
Continuity (1)
Related Publication 20250086043A1 · Mar 13, 2025
References Cited (27)
US 7587299B2 · Miyasaka et al. · 2009 [cited by applicant]
US 8060934B2 · Cabuk et al. · 2011 [cited by applicant]
US 8209564B2 · Vidal et al. · 2012 [cited by applicant]
US 8996916B2 · Huang · 2015 [cited by examiner]
US 9152484B2 · Vidal et al. · 2015 [cited by applicant]
US 10379985B1 · White · 2019 [cited by examiner]
US 10445311B1 · Saurabh et al. · 2019 [cited by applicant]
US 10673885B2 · Muthukrishnan et al. · 2020 [cited by applicant]
US 11461721B2 · Ramakrishnaraja et al. · 2022 [cited by applicant]
US 11632383B2 · Oliner et al. · 2023 [cited by applicant]
US 20050278273A1 · Uthe · 2005 [cited by examiner]
US 20060101308A1 · Agarwal · 2006 [cited by examiner]
US 20080141240A1 · Uthe · 2008 [cited by applicant]
US 20110225461A1 · Wookey · 2011 [cited by applicant]
US 20160364224A1 · Tuukkanen · 2016 [cited by examiner]
US 20170116059A1 · Wolf · 2017 [cited by examiner]
US 20170235558A1 · Saenz · 2017 [cited by examiner]
US 20180157550A1 · Ivanov · 2018 [cited by examiner]
US 20220060371A1 · Paradkar · 2022 [cited by examiner]
US 20220129337A1 · Hermanns · 2022 [cited by examiner]
US 20230094140A1 · Kruempelmann · 2023 [cited by examiner]
US 20230185556A1 · Chen · 2023 [cited by examiner]
US 20230236818A1 · Saeki · 2023 [cited by examiner]
US 20230281098A1 · Hesse · 2023 [cited by examiner]
CN 115712443 · 2023 [cited by applicant]
Logic Monitor, “Log Anomaly Detection”, https://www.logicmonitor.com/support/log-anomaly-detection, May 11, 2023; 5 Pages. [cited by applicant]
IBM, “What is cloud native?”, https://www.ibm.com/topics/cloud-native, Aug. 12, 2023; 15 Pages. [cited by applicant]