Abstract: A set of virtual machines is deployed on a hypervisor. At each virtual machine, one or more local scans is performed to generate a set of computing resource consumption data. In response to receiving a set of hypervisor resource consumption data, a stability factor is generated. Based on the set of resource consumption data, the set of hypervisor resource consumption data, and the stability factor, a determination is made that a default consumption metric exceeds a threshold. In response to the determination, a custom consumption metric is generated, based on at least the set of computing resource consumption data. A user is notified of the custom consumption metric.

Abstract: A computer-implemented method includes: connecting, by a computing device, to a database using an outbound connection, wherein the computing device is an information technology (IT) product in a private network and the database is outside the private network; receiving, by the computing device, a response from the database, the response including a command; executing, by the computing device, the command; and sending, by the computing device, result data to the database, wherein the result data is data that results from executing the command on the computing device.

Abstract: Support queries are automatically provided. An error is identified during execution of an application. A support query for the error is produced using the source code for the application with the support query including context information for the error. The support query is displayed to a user.

Abstract: Resource load balancing for eNodeB includes identifying reduced workload conditions for an underutilized processor (CPU) core and transferring dedicated traffic channel (DTCH) communication to a target CPU core. Upon migrating each DTCH from the selected CPU core, the underutilized CPU core is caused to go into sleep mode, not to receive DTCH request until activated.

Abstract: A method, computer program, and computer system are provided for improving accessibility to computer reader tools. Data corresponding to one or more words to be displayed to a user is received. The received data is converted into synthesized speech. One or more words exceeding an understanding threshold value are identified from the synthesized speech. The understanding threshold value corresponds to a probability of difficulty associated with understanding the one or more words. One or more replacement words are retrieved for the one or more words exceeding the understanding threshold value. The synthesized speech is updated with the one or more replacement words.

Abstract: A first backend housekeeping operation of a backend storage system is detected by a storage virtualization system. The first backend housekeeping operation is related to a first backend storage portion of the backend storage system. The storage virtualization system transfers data to the backend storage system for storage and retrieval. The storage virtualization system issues commands to the backend storage system. A first virtualized operation related to a first virtualized storage portion of the storage virtualization system is identified. A storage overhead condition is determined based on the first backend storage portion and based on the first virtualized operation. A storage corrective action is performed based on the storage overhead condition. The storage corrective action prevents the potential performance of one or more additional backend housekeeping operations.

Abstract: A computer-implemented method for software detection is disclosed. The computer-implemented method includes scanning a list of file systems present on a computer system and described by a respective mount point for a signature from a set of predetermined signatures. The computer-implemented method further includes responsive to detecting the signature from the set of predetermined signatures, selecting a particular plugin from a predetermined list of plugins based, at least in part, on the detected signature. The computer-implemented method further includes querying, using the plug-in, an operating environment of the filesystem for data indicative of software running in the operating environment. The computer-implemented method further includes determining software running in the operating environment based, at least in part, on the data returned from querying the operating environment of the filesystem.

Abstract: Resource load balancing for eNodeB includes identifying reduced workload conditions for an underutilized processor (CPU) core and transferring dedicated traffic channel (DTCH) communication to a target CPU core. Upon migrating each DTCH from the selected CPU core, the underutilized CPU core is caused to go into sleep mode, not to receive DTCH request until activated.

Abstract: A method, a computer system, and a computer program product for tiering migration for storage system optimization is provided. Embodiments of the present invention may include determining to move data based on access counters to balance a workload between storage drives and storage tiers. Embodiments of the present invention may include establishing a connection with an interconnect application program interface. Embodiments of the present invention may include collecting and converting physical access counters. Embodiments of the present invention may include collecting heat map data. Embodiments of the present invention may include calculating a tiering migration plan for an internal map change event.

Abstract: Aspects of the present invention disclose a method, computer program product, and system for determining a response to a query from a user. The method includes one or more processors receiving a query associated with a software product. The query includes an indication of an error. The method further includes one or more processors determining whether a response to the query is available in an accessible knowledge base. In response to determining that a response to the query is not available, the method further includes one or more processors identifying content in program code of the software product that corresponds to the indicated error of the received query. The method further includes one or more processors determining a response to the query based on the identified content in the program code. The determined response to the query includes diagnostic information corresponding to the indicated error.

Abstract: In an approach to improve the field of multi-cloud environments by detecting data corruption between storage systems. Embodiments perform information tunneling on data transferring between a source storage system and a target storage system. Further, embodiments determine a checksum data of a data payload does not match an Internet Protocol (IP) packet extracted checksum and a blockchain based checksum and compare the checksum data at the target storage system with the IP packet extracted checksum and the blockchain based checksum to identify one or more checksum mismatches. Additionally, embodiments identify a corruption in a data payload based on the comparison between the checksum data at the target storage system and the IP packet extracted checksum and the blockchain based checksum, validate the corruption in the data payload, and update respective entities of identified corruption in the data payload.

Abstract: Processing user queries using a bot program by executing a bot program, wherein executing the bot program further comprises: processing output data of an application program; detecting status messages in the output data; generating bot queries related to the status messages; providing the bot queries to a user, in response to the providing of the bot queries to the user, receiving a user query from the user, wherein the user query is based at least in part on the bot queries, determining one or more solutions to the user query using a knowledge base, and applying a selected solution of the solutions.

Abstract: Provided are techniques for collecting capacity data of virtual machines by leveraging agent data. A list of one or more virtual machines for which capacity data is to be retrieved is obtain from an asset server, where the one or more virtual machines are identified using a licensing measurement. Infrastructure data and hypervisor data are obtained from an infrastructure server. For each of the one or more virtual machines, the infrastructure data and the hypervisor data are used to request, from a capacity scanner on each of the one or more virtual machines, capacity data for that virtual machine. The capacity data for each of the one or more virtual machines is sent to the asset server, and the asset server performs load balancing of software that is to be executed on the one or more virtual machines using the capacity data.

Abstract: Metadata can be generated for documentation accessed from at least one knowledge source. Intents for main topics of the documentation can be generated using content structure information for the documentation. Dialogs for the intents can be generated. Sub-dialogs can be created for each of the dialogs based, at least in part, on the metadata for the documentation. The dialogs can be configured to be used to modify existing dialogs of a problem-solution data set.

Abstract: At least one knowledge source for use in updating a first problem-solution data set can be selected. From data provided by the at least one knowledge source, a plurality of dialogs can be automatically generated. Existing dialogs in the first problem-solution data can be updated set using the plurality of dialogs that are generated.

Abstract: A computer-implemented method includes: connecting, by a computing device, to a database using an outbound connection, wherein the computing device is an information technology (IT) product in a private network and the database is outside the private network; receiving, by the computing device, a response from the database, the response including a command; executing, by the computing device, the command; and sending, by the computing device, result data to the database, wherein the result data is data that results from executing the command on the computing device.

Abstract: When a system receives sensitive data, it can request an encryption key from an encryption/decryption unit. A central processing unit (CPU) of the system can encrypt the sensitive data using the encryption key before writing the sensitive data to memory. Thus, the sensitive data is encrypted when written to memory.

Abstract: A first backend housekeeping operation of a backend storage system is detected by a storage virtualization system. The first backend housekeeping operation is related to a first backend storage portion of the backend storage system. The storage virtualization system transfers data to the backend storage system for storage and retrieval. The storage virtualization system issues commands to the backend storage system. A first virtualized operation related to a first virtualized storage portion of the storage virtualization system is identified. A storage overhead condition is determined based on the first backend storage portion and based on the first virtualized operation. A storage corrective action is performed based on the storage overhead condition. The storage corrective action prevents the potential performance of one or more additional backend housekeeping operations.

Abstract: When a system receives sensitive data, it can request an encryption key from an encryption/decryption unit. A central processing unit (CPU) of the system can encrypt the sensitive data using the encryption key before writing the sensitive data to memory. Thus, the sensitive data is encrypted when written to memory.

Abstract: Processing user queries using a bot program by executing a bot program, wherein executing the bot program further comprises: processing output data of an application program; detecting status messages in the output data; generating bot queries related to the status messages; providing the bot queries to a user, in response to the providing of the bot queries to the user, receiving a user query from the user, wherein the user query is based at least in part on the bot queries, determining one or more solutions to the user query using a knowledge base, and applying a selected solution of the solutions.