International Business Machines Corporation

Kyndryl, Inc.

Thanh V Lam

Craig M Trim

Mary E Rudden

Daniel S Riley

Karen Cheng

Giampaolo Lauria

Rhonda L Childress

Anthony F Pioli

Data security across data residency restriction boundaries is provided by obtaining and profiling a dataset on which a desired analysis is to be performed, with some results of the desired analysis to be transferred from one location to another, the dataset subject to data residency restrictions that restrict transfer of the dataset across a boundary to the another location, and the profiling identifying a profile level for the dataset, then automatically generating a container image based on the profile level and the data residency restrictions that restrict the transfer of the dataset across the boundary, the container image configured for instantiation and execution to process the dataset into a reformatted dataset not restricted by the data residency restrictions for transfer across the boundary, and storing the container image to a container registry.

Data security across data residency restriction boundaries

A computer-implemented method includes: receiving, by a computing device, a container from a data requester server for processing data as part of an inference analysis; attaching, by the computing device, an input data volume and an output data volume associated with the container; processing, by the computing device, input data stored in the input data volume to produce output data; attaching, by the computing device, the output data in the output data volume; detaching, by the computing device, the input data volume based on attaching the output data to the output data volume; determining, by the computing device, whether sensitive data exists in the output data volume; and providing, by the computing device, the output data volume to the data requester server based on the determining that sensitive data does not exist in the output data volume.

Maintaining data protection compliance and data inference from data degradation in cross-boundary data transmission using containers

Data security across data residency restriction boundaries is provided by profiling a dataset on which a desired analysis is to be performed, with some results of the desired analysis to be transferred from one location to another, the dataset subject to data residency restrictions that restrict transfer of the dataset across a boundary to the another location, and the profiling identifying a profile level for the dataset, automatically generating, based on the profile level and the data residency restrictions that restrict the transfer of the dataset across the boundary, a container for processing the dataset into a reformatted dataset not restricted by the data residency restrictions for transfer across the boundary, instantiating the generated container on a data processing system at the one location, and processing the dataset into the reformatted dataset using the instantiated generated container, and transferring the reformatted dataset to the another location.

A system and method for performing event analysis includes a plurality of logical components (), each communicatively coupled to at least one other of the plurality of components. A transformer () receives from one or more of the logical components, one or more status messages describing a system state to form received status messages and transforms the received status messages into at least one transformed message such that the transformed message has at least one new substring which is not common with the received status messages. A processor () is coupled to the transformer () that receives one or more rules () and applies the one or more rules () to the one or more transformed status messages and an output () outputs at least one of a new rule and a new event.

Identification of relevant metrics

A technique is presented for integrating software components. The technique includes providing an application integration model capable of adapting to different environments by dynamically using different software components at application runtime. The software components are categorized into different stages, with the stages being indicative of when the software components are to be loaded and executed within an application by the application integration model. The technique further includes employing the application integration model to assemble software components into the application within a runtime environment. The application integration model includes an application runtime driver (ARD), which drives work flows of the application integration model through multiple predefined application stages, and a component runtime integration box (CRIB), which includes multiple common data structures employed by the software components during integration into the application.

Application integration model for dynamic software component assembly within an application at runtime

A remote monitor technique based on a client/server model is provided for a distributed computing system having a plurality of computing nodes. The remote monitor includes a server application for collecting jobs information on jobs in a queue of the system and a client application for presenting or employing the jobs information. The client application can display the jobs information in a single display window comprising multiple subwindows for various characteristics of the jobs information. Jobs information displayed by the client application can be periodically refreshed. The remote monitor enables a user to monitor in detail jobs of a state defined by the user. The remote monitor can also track usage of preselected filesystems and automatically trims filesystems if usage is higher than a defined threshold.

In-queue jobs information monitoring and filtering

A method, and a system applying the method, for submitting an instance of a job for execution by a processor and monitoring the job instance using a state model, including the following steps. Fetching a job instance, the job instance having associated job instance activate information. Submitting the job instance to a processor. Registering the job instance activate information with a job queuing subsystem application program interface (API). Determining a state of the job instance, the job instance automatically and continuously monitoring the state while the job instance is running and when the state matches a predetermined state value the job instance submitting a subsequent job instance to the processor and registering the subsequent job instance activate information with the API. Reporting, by the API, the state of the job instance to an application. Implementing an action on the subsequent job instance based on the reported state.

Self-submitting job for testing a job scheduling/submitting software

A test automation tool is provided which is operable to integrate a set of dynamic attributes and values into tests to be performed on a computing environment. The test automation tool includes a job submission engine (JSE) operable to receive input regarding first attributes unchanged from a first computing environment and second attributes representing change from the first computing environment. A job control file generator (JCFG) is provided in electronic communication with the job submission engine and is operable to automatically generate job control files (JCFs) for controlling testing of the computing environment according to attribute values including first attribute values and second attribute values. First attribute values are generated based on an automatic sampling of values of first attributes. The JSE is further operable to automatically submit the JCFs to the computing environment for execution and to automatically monitor execution according to the JCFs.

Test automation method and tool with dynamic attributes and value sets integration

An observable object represents a feature to be audited. The observable object provides a decentralized location that includes logic responsible for auditing its own data. Should the audit detect a change in the data, a modifier object is created, which includes modify logic to accommodate the change. The modifier object is added to a pool of modifier objects, and at the appropriate time, one or more observers retrieve the modifier object and run the modify logic.

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Aurora, CO, United States of America

Thanh V Lam