International Business Machines Corporation

Piotr P Godowski

Michal S Paluch

Szymon Kowalczyk

Tomasz Hanusiak

Andrzej Pietrzak

Piotr Kania

Tomasz Andrzej Stopa

Luigi Pichetti

Artur Obrzut

Artur Zezula

Krzysztof Pienkowski

Bartlomiej Tomasz Malecki

Szymon M Brandys

Adam Babol

Jacek Midura

Jan Galda

Cezary Gorka

Agnieszka Matecka

Norbert Chocko

Pawel Tadeusz Januszek

Piotr Kalandyk

Hubert Kompanowski

Grzegorz Majka

Lukasz Tomasz Jeda

David Warren Knapp, Jr

Jacek J Stezowski

Tomasz P Zeller

Dariusz P Glocki

Lukasz Tomasz Jȩda

Lukasz Józef Matyasik

Kacper Krzyżak

An example operation may include one or more of identifying a pod that is within a namespace of a host platform, reading a file from a metadata storage of the pod, wherein the file that includes software definition data of the pod, identifying a field within the configuration data of the pod that contains an invalid entry based on a comparison of a value stored in the field to a predefined list of annotations, and in response to the identification of the invalid field, generating and store a log entry into a log of the pod which identifies the invalid field.

System and method for validation and correction of metadata in containerized software enviornments

Containerized software discover and identification can include discovering a plurality of container remnants by electronically scanning portions of computer memory of at least one computer system of one or more of computing nodes, the portions of computer memory being allocated to persistent storage of computer data, and each container remnant containing computer data providing a record of system-generated execution attributes generated in response to execution of one or more containerized applications. One or more inactive container remnants unutilized by a currently running containerized application can be identified among the plurality of container remnants. Each inactive container remnant can be categorized, the categorizing being based on system-generated execution attributes contained in each inactive container remnant. Based on the categorizing, a previously run containerized application can be identified by reference to a database comprising data whose structures map identities of containerized applications to patterns of execution attributes.

Containerized software discovery and identification

In an approach to improve chatbot workspaces by updating chatbot workspaces through documentation updating and chatbot skill updating. Embodiments determine a chatbot knowledge base contains a set of updated information and updates a chatbot dialog decision tree based on one or more identified new topics in a set of updated information using natural language processing techniques to determine a set of intents, a set of entities, and a set of keywords. Further, embodiments identify a starting decision for traversing the chatbot dialogue decision tree based on the updated set of entities and the updated set of keywords. Additionally, embodiments interact, via a user interface, with an end user according to one or more interactions traversing the chatbot dialogue decision tree for a response.

Updating chatbot workspaces

One or more computer processors responsive to a hypervisor data request, generate an encrypted set of hypervisor data indicating hypervisor hardware details using a plurality of respective asymmetric encryption keys to tag the generated set of encrypted hypervisor data with a timestamp at a time of encryption. The one or more computer processors decrypt the tagged set of encrypted hypervisor data utilizing a software asset manager and the plurality of respective asymmetric encryption keys determined valid based on a threshold time period and the tagged timestamp. The one or more computer processors validate the set of decrypted hypervisor data utilizing corresponding checksums to determine whether the set of encrypted hypervisor data was successfully decrypted. The one or more computer processors sanitize the validated hypervisor data based on a corresponding software license.

Secure virtual machine software management

A computer implemented method and related system determine a current load result of a software container executing on a compute node in a container system. In response to determining that the current load result exceeds a predetermined scale-up threshold for the software container, the method adds a first plurality of replicas of the software container to the compute node, where a quantity of the first plurality of replicas is related to the current load result. In response to determining that the current load result is less than a predetermined scale-down threshold for the software container, the method deletes a second plurality of replicas of the software container from the compute node, where a quantity of the second plurality of replicas is related to the current load result.

Service load independent resource usage detection and scaling for container-based system

Provided are a computer program product, system, and method for scanning a computing system to determine a computing system profile and problems to recommend actions to initiate with the computing system. A package is transmitted to the computing system including package code to scan the computing system to determine a computing system profile comprising a computing architecture and installed applications at the computing system. The computing system profile is processed to determine a recommended action to perform with respect to the computing system to improve operations of the computing system based on the computing system profile. A display element is generated in a user interface with information on the recommended action to enable a user of the computing system to implement the recommended action. The package code executes within the computing system without communicating over the network to an external system outside of a computing environment of the computing system.

Scanning a computing system to determine computing profile and problems to recommend an action to initiate with the computing system

An image for a containerized application is created. From the image, one or more main processes of the containerized application are identified. The one or more main processes comprise a first subset of a plurality of processes of the containerized application. Within a sandbox environment, the containerized application is started. Based on the started application within the sandbox environment, a second subset of processes within the plurality is determined. The second subset includes one or more dependent processes associated with the first subset. A third subset of processes within the plurality is determined. The third subset excludes the first and second subsets and is associated with a vulnerability list. According to the third subset, a mitigated image for the containerized application is generated.

Automatic vulnerability mitigation

A technique to manage software licensing in an environment that provides virtual desktop infrastructure (VDI). A license manager is configured to receive first information identifying software applications associated with a virtual machine template used in the infrastructure, as well as second information that a user has logged into the VDI from a client device, thereby creating a VDI session. For a particular time period of interest, the license manager calculates software application usage information from the first and second information. Preferably, the software application usage information represents an application count that is based on the user and the client device 'pair' when the user has the VDI session during at least some portion of the time period. The software application usage information is provided to one or more other computing systems to take a given action, such as tracking, managing, auditing, enforcing and accounting for software usage in the VDI environment.

Template-based software discovery and management in virtual desktop infrastructure (VDI) environments

A first computer system is scanned at configured, default time intervals by a software asset management ('SAM') software application installed on the first computer system, wherein the scanning detects other software applications installed on the first computer system. The SAM software application generates a list of the other software applications installed on the first computer system and stores the list on a computer readable storage medium. An override software module triggers the SAM software application to perform an early scan of the first computer system, before a scan of the first computer system that the SAM software application would otherwise perform at a next default scan time. The triggering is in response to information obtained from a source external to the first computer system about a triggering one of the software applications on the list.

Technology for adaptive software discovery scan

Provided are techniques for automated software application license usage. Global detection results that indicate, for each of a plurality of end user computers, one or more installed software applications, one or more running software applications, and a user account. Unique pairs are identified using the global detection results, wherein each pair of the unique pairs comprises a software application name for a software application and a user name for a user. For a unique pair, a query is run against a user registry to get a list of user groups that the user name is a member of, a user group is selected that corresponds to the software application name, and a number of users in the selected user group is designated as a license demand for authorized users for the software application. Then, based on the global detection results and the license demand, one or more recommendations are provided.

Determining software application license usage

An example operation may include one or more of detecting a web session within an open window of a web browser on a user device, monitoring for user activity on the user device with respect to the web browser, determining there has been a lack of user activity with respect to the web browser for a predetermined amount of time based on the monitoring of the user activity, and temporarily concealing content within the open window of the web browser in response to the lack of user activity.

Automated web session timeout enforcement

A computer system performs software discovery on a shared resource in a network. A logical group is generated for the shared resource, wherein the logical group includes a plurality of devices accessing the shared resource. A designated device is selected from the plurality of devices for performing a software discovery operation on the shared resource, wherein the selection is based on one or more performance factors. Results of the software discovery operation on the shared resource are received from the designated device. The results of the software discovery operation are distributed by the designated device to the plurality of devices. Embodiments of the present invention further include a method and program product for performing software discovery on a shared resource in a network in substantially the same manner described above.

Control of scanning shared resources by devices for software discovery

A virtual scan group manager (VSGM) can receive a plurality of respective sets of data from a plurality of respective devices. The VSGM can allocate respective portions of the plurality of respective sets of data to respective virtual scan groups (VSGs). The VSGs can be processed by storing the data contained in each VSG in a data repository. Respective sets of data stored in the data repository can be catalogued in a VSGM logfile.

Dynamic data ingestion

The systems and methods provided herein determine at least one first file system path related to a specific software package. A second file system path associated with a computing process running on the computer system is determined, and use of the specific software package on the computer system is detected based on comparing the first file system path with the second file system path. Thus, the present techniques determine the installation director(ies) of the application(s) and then compare active processes to determine whether an application is in use or is only installed.

Growing community of inventors

Cracow, Poland

Piotr P Godowski