Jinho H Hwang, 52Leonia, NJ

2022023, Jul 21, 2022

Jan 15, 2021

17/150657

- Armonk NY, US
Michael Elton Nidd - Zurich, CH
Larisa Shwartz - Greenwich CT, US
Jinho Hwang - Ossining NY, US
Harshit Kumar - Delhi, IN

G06N 20/00
G06F 16/23
G06Q 10/06

Systems, computer-implemented methods, and computer program products to facilitate proactive operational risk assessment of a proposed change in a computing environment are provided. According to an embodiment, a system can comprise a processor that executes computer executable components stored in memory. The computer executable components can comprise an extraction component that identifies change events in historic operational data that induced one or more incidents in a computing environment. The computer executable components further comprise an assessment component that employs a model to assign a change risk assessment score to a defined change in the computing environment based on the change events.

2021037, Dec 2, 2021

May 26, 2020

16/882811

- Armonk NY, US
Jinho HWANG - Ossining NY, US
Qing Wang - Chappaqua NY, US
Larisa Shwartz - Greenwich CT, US
Michael Elton Nidd - Zurich, CH
Frank Bagehorn - Dottikon, CH
Jakub Krchák - Jindrichuv Hradec, CZ
Altynbek Orumbayev - Prague, CZ
Michal Mýlek - Vrane nad Vitavou, CZ
Ota Sandr - Praha, CZ
Tomás Ondrej - Prague, CZ

G06F 8/41
G06F 16/245
G06F 8/75

A computer implemented method for identifying an application topology includes identifying a sandbox environment corresponding to an application of interest, analyzing the sandbox environment to identify a set of communication links between services within the sandbox environment indicating a first topology, identifying a production system corresponding to the application of interest, querying the production system to identify a set of structural dependencies indicating a second topology, and creating a complete topology of the cloud application by combining the first topology and the second topology. A computer program product and computer system for identifying an application topology are additionally disclosed herein.

2021035, Nov 11, 2021

May 8, 2020

16/869647

- Armonk NY, US
Larisa Shwartz - Greenwich CT, US
Srinivasan Parthasarathy - White Plains NY, US
Jinho HWANG - Ossining NY, US
Tengfei Ma - White Plains NY, US
Michael Elton Nidd - Zurich, CH
Frank Bagehorn - Dottikon, CH
Jakub Krchák - Jindrichuv Hradec, CZ
Altynbek Orumbayev - Prague, CZ
Michal Mýlek - Vrané nad Vltavou, CZ
Ota Sandr - Praha, CZ
Tomás Ondrej - Prague, CZ

G06N 5/04
G06F 16/901
G06N 20/00

A method, a computer system, and a computer program product for mapping operational records to a topology graph. Embodiments of the present invention may include generating an event frequent pattern using operational records. Embodiments of the present invention may include integrating topology-based event frequent patterns. Embodiments of the present invention may include mapping the operational records with an embedding engine. Embodiments of the present invention may include predicting incident events. Embodiments of the present invention may include receiving labeled patterns to the embedding engine for an active learning cycle.

2021030, Sep 30, 2021

Mar 30, 2020

16/834463

- Armonk NY, US
Jinho Hwang - Ossining NY, US
Ali Kanso - Stamford CT, US

International Business Machines Corporation - Armonk NY

G06N 20/00
G06N 5/04
G06K 9/62
G06F 9/22

Embodiments relate to a computer system, computer program product, and computer-implemented method to train a machine learning (ML) model using artificial intelligence to learn an association between (regulatory) compliance requirements and features of micro-service training datasets. The trained ML model is leveraged to determine the compliance requirements of a micro-service requiring classification. In an exemplary embodiment, once the micro-service has been classified with respect to applicable compliance requirements, the classified micro-service may be used as an additional micro-service training dataset to further train the ML model and thereby improve its performance.

2021029, Sep 23, 2021

Mar 19, 2020

16/823649

- Armonk NY, US
Jin Xiao - White Plains NY, US
Jinho Hwang - Ossining NY, US
Maja Vukovic - New York NY, US
John Rofrano - Mahopac NY, US

G06F 8/76
G06F 16/245
G06N 3/04
G06N 3/08
G06F 8/71
G06F 8/65

A system can include a memory that stores computer-executable components and a processor, operably coupled to the memory, that can execute the computer-executable components stored in the memory. The computer-executable components can include a model generator component that can execute a search function on an application based on a set of application component topics to identify application components of the application that facilitate execution of the application. A configuration property extractor component can analyze the application based on the application components and can determine configuration properties associated with operating the application components. An application builder component can process the application components and the configuration properties and can generate instructions that facilitate execution of the application in a target computing environment.

2021027, Sep 9, 2021

Mar 6, 2020

16/811586

- Armonk NY, US
Anup Kalia - Elmsford NY, US
Jinho Hwang - Ossining NY, US
Maja Vukovic - New York NY, US
John Rofrano - Mahopac NY, US

G06F 9/38
G06F 9/30
G06F 9/50
G06F 9/455

Systems, computer-implemented methods, and computer program products to facilitate transformation of an enterprise application into a cloud native container are provided. According to an embodiment, a system can comprise a memory that stores computer executable components and a processor that executes the computer executable components stored in the memory. The computer executable components can comprise an analysis component that employs a model to discover attributes of an enterprise application. The computer executable components can further comprise a transformation component that generates artifacts based on the attributes to transform the enterprise application into a cloud native container.

2021015, May 20, 2021

Dec 28, 2020

17/135553

- Armonk NY, US
Jinho Hwang - Ossining NY, US
Vugranam C. Sreedhar - Yorktown Heights NY, US
Sai Zeng - Yorktown Heights NY, US

G06F 21/56
G06F 21/57
G06F 11/34

Techniques for dynamic server groups that can be patched together using stream clustering algorithms, and learning components in order to reuse the repeatable patterns using machine learning are provided herein. In one example, in response to a first risk associated with a first server device, a risk assessment component patches a server group to mitigate a vulnerability of the first server device and a second server device, wherein the server group is comprised of the first server device and the second server device. Additionally, a monitoring component monitors data associated with a second risk to the server group to mitigate the second risk to the server group.

2021014, May 13, 2021

Nov 7, 2019

16/677158

- Armonk NY, US
Jinho Hwang - Ossining NY, US
Maja Vukovic - New York NY, US
Komminist Weldemariam - Ottawa, CA

G06Q 10/06

Techniques regarding using a combination of goals and context to allocate workspaces to worker entities are provided. For example, one or more embodiments described herein can comprise a system, which can comprise a memory that can store computer executable components. The system can also comprise a processor, operably coupled to the memory, and that can execute the computer executable components stored in the memory. The computer executable components can comprise a data evaluating component that can evaluate data received from a data collection device associated with a task to be performed by a worker entity, and a goal determining component that can determine a goal of the worker entity for the task, based on the evaluated data. The system can further comprise a matching component that can select a workspace resource for the task based on the goal and a context of the task.