Abstract: A disclosure for management of multiple information management cells running different versions of software applications using a gateway system is provided herein. The disclosure addresses the drawbacks associated with the current environment of managing multiple information management cells through a separate URL by centralizing the user interfaces (UI) to a single front-end administrative UI that is specific to the version of software application operating on that cell. The gateway system comprises a mapping module, a storage module, a UI module, and a communication module that interoperate to retrieve the version of a software application operating on the targeted cell, the UI running that version of software application, and presenting a user interface that can view and manage the operations of that targeted cell. The gateway system serves the UI specific for the version of software application for that cell from its local collection.

Abstract: A method and a drug delivery system for transdermally administering parathyroid hormone (PTH) in a pulsatile fashion are provided, where the drug delivery system comprises an array of microprojections each comprising PTH.

Abstract: Methods, apparatus, and processor-readable storage media for cognitive device management using artificial intelligence are provided herein.

Abstract: Techniques are provided for dynamic snapshot scheduling. In an example, a dynamic snapshot scheduler can analyze historical data about storage system resources. The dynamic snapshot scheduler can use this historical data to predict how the storage system resources will be used in the future. Based on this prediction, the dynamic snapshot scheduler can schedule snapshot activities for one or more times that are relatively unlikely to experience system resource contention. The dynamic snapshot scheduler can then initiate snapshot activities at those scheduled times.

Abstract: Embodiments for storing digital data in DNA storage by receiving input file data, encoding the input file data into an oligonucleotide sequence to produce sequence data through a transformation of text to binary to Base_3 encoding, organizing the Base_3 sequence data into chunks of a defined chunk size, and storing the chunks in a block of a blockchain. The oligonucleotide sequence may comprise metadata for the input file data that refers to actual data stored in the DNA storage, where the actual data is formed by synthesizing the oligonucleotide sequence in a DNA synthesis process. The chunks may be stored in the blockchain only if the block agrees with a smart contract defined for the oligonucleotide sequence.

Abstract: Embodiments include a method of storing digital data in a blockchain by receiving the digital data from a user, deduplicating the data in a deduplication system of the user to form deduplicated data, and encoding the deduplicated data into an array format for storage on a blockchain. A smart contract is deployed for deduplication on the destination side of the data, and the deduplicated data is encoded into a Binary Aligned Map (BAM) format for storage on the blockchain. A process on the destination side stores the deduplicated array data as a next block in the blockchain only if the next block agrees with the smart contract, and the blockchain is stored in system storage comprising hard disk, solid state, tape, or optical devices.

Abstract: An apparatus comprises a processing device configured to detect that a given software upgrade is available for a given computing device, to identify other computing devices on which the given software upgrade has been installed that exhibit at least a threshold level of similarity to the given computing device, and to determine whether any issues were encountered on the other computing devices as a result of the given software upgrade. The processing device is also configured to generate a recommendation as to whether to initiate download of the given software upgrade on the given computing device based at least in part on whether any issues were encountered on the other computing devices as a result of the given software upgrade, and to initiate download of the given software upgrade on the given computing device based at least in part on the generated recommendation.

Abstract: An apparatus comprises at least one processing device that is configured to implement a data collection agent and obtain a telemetry data collection specification. The at least one processing device is configured to train the data collection agent based at least in part on the telemetry data collection specification and to obtain an issue description corresponding to a technical support issue associated with a source device of an information processing system. The at least one processing device is configured to generate a telemetry data collection query based at least in part on the obtained issue description using the trained data collection agent and to submit the query to the source device. The at least one processing device is configured to obtain from the source device, telemetry data generated based at least in part on the query and to present the telemetry data to a user via a graphical user interface.

Abstract: A method, comprising: detecting that a storage device is experiencing a failure, the storage device being part of a computing device; identifying a cooling fan that is associated with the storage device, the cooling fan being part of the computing device, the cooling fan being identified based on one or more data structures that map the cooling fan to the storage device; and increasing a speed of the cooling fan from a first speed level to a second speed level, the speed of the cooling fan being increased in response to detecting that the storage device is experiencing the failure, wherein the speed of the cooling fan is increased proactively.

Abstract: A system and method reorder execution of a test suite to be performed on a given device according to an initial testing order. Each testing sequence in the test suite is analyzed for dependencies between test cases, and these dependencies are recorded in directed graphs. Next, a machine learning algorithm, such as the random forest algorithm, is trained on multi-dimensional historical testing data according to several testing parameters to predict success or failure of any given test. The trained algorithm is used to predict, for a given device under test, which of the test cases are likely to fail, and to compute a confidence value for each such prediction. The directed graphs then are reorganized so that graphs containing tests most likely to fail are executed early in the test suite, according to a modified testing order that accounts for both test dependencies and the confidence values.

Abstract: A system, method, and computer-readable medium are disclosed for attesting determining computer system fan usage and maintenance. A determination is made as to the architectural diagram or layout of a computer system. The diagram or layout shows components and fans that support the components. The architectural diagram or layout, where each virtual section shows a fan and the components. Operational load is determined for each virtual section over a period of time. A threshold value for particular periods to time, where the threshold value either is to low load periods or as to periods to increase or decrease speed of the fan to address operational load of the components.

Abstract: Embodiments include a method of storing digital data in DNA storage by receiving the digital data from a user, deduplicating the data in a deduplication system of the user to form deduplicated data, and encoding the deduplicated data into a DNA string into a format for storage on a blockchain. A smart contract is deployed for deduplication on the destination side of nucleotide sequences comprising the DNA string, and the deduplicated nucleotide sequences are encoded into a Binary Aligned Map (BAM) format for storage as metadata on the blockchain. A process on the destination side synthesizes the deduplicated nucleotides for storage in the DNA storage, and stores the deduplicated nucleotides in the DNA storage as a next block in the blockchain only if the next block agrees with the smart contract.

Abstract: A method for managing applications in a production host environment includes obtaining, by an application upgrade management system, an upgrade issue report for the application, applying a self-healing classification model to the upgrade issue report to obtain a state of the upgrade issue report, making a determination that the state indicates a self-healable state, based on the determination, performing a self-healing process on the application based on the upgrade issue report, and storing a resolution report based on results of the self-healing process.

Abstract: In one aspect, an example methodology implementing the disclosed techniques includes receiving an input to register a device for tracking, the input comprising registration data specifying the device and one or more components in the device to register for tracking and a minimum acceptance criterion for each of the one or more components, the minimum acceptance criterion for a registered component defines a minimum threshold percentage of votes needed to approve a modification to the registered component. The method also includes recording the device identifier and the registration data related to the device in a device ledger, generating a rule execution set for the device ledger, the rule execution set comprising one or more rules pertaining to approval of requests to modify the device, and processing requests to modify the device or the one or more registered components in the device based on the specified minimum acceptance criterion and the rule execution set.

Abstract: A method comprises receiving a notification of an issue with at least one component of a plurality of components in a computing environment. One or more machine learning algorithms are used to determine one or more components of the plurality of components impacted by the issue with the at least one component. The method further comprises collecting operational data for the at least one component and the one or more impacted components.

Abstract: In one aspect, an example methodology implementing the disclosed techniques includes receiving, by a systems management console, a network address of a device in a virtual environment, and determining a network address associated with a virtual environment management console based on the received network address of the device in the virtual environment. The method also includes sending, by the systems management console via a systems management agent to the virtual environment management console using the determined network address associated with the virtual environment management console, a request for network addresses of virtual machine (VM) host servers and VMs in the virtual environment. The method also includes receiving, by the systems management console via the systems management agent from the virtual environment management console, the network addresses of the VM host servers and the VMs in the virtual environment and providing a notification of the discovered VM host servers and VMs.

Abstract: In one embodiment, at least one processing device is configured to assign a plurality of devices of a cluster to a logical host group where at least one of the devices assigned to the logical host group has a network time parameter that is different than another of the devices assigned to the logical host group. The at least one processing device is further configured to determine a target network time parameter for the logical host group based at least in part on network time parameter related information about a given device of the plurality of devices assigned to the logical host group and to cause the plurality of devices to configure their respective network time parameters to the target network time parameter based at least in part on the assignment of the plurality of devices to the logical host group.

Abstract: An apparatus comprises a processing device configured to receive a request to boot a given computing device to a primary environment and, responsive to receiving the request, to obtain first inventory information for components of the given computing device utilizing a preinstallation environment of the given computing device. The processing device is also configured to analyze the first inventory information and second inventory information to determine whether there any changes in the components of the given computing device prior to booting the given computing device to the primary environment, the second inventory information being previously stored in a support environment of the given computing device. The processing device is further configured to generate notifications based at least in part on determining that there are one or more changes in the components of the given computing device, and to provide the notifications at a user interface of the given computing device.

Abstract: A method comprising: receiving a configuration file that identifies a plurality of first log patterns, each of the first log patterns being associated with a respective component of an application and a respective malfunction of the respective component of the application; retrieving, by an application monitor, one more execution logs that are generated while the application is being executed; identifying, by the application monitor, a malfunction of the application based on the configuration file and the one or more execution logs, the malfunction being identified in response to a given one of the plurality of first log patterns matching an execution log pattern that is identified in the one or more execution logs; and reporting, by the application monitor, the malfunction to a technical support system.

Abstract: A system and method model activities in the production environment as sequences of microservices, and identify unusual activities by analyzing these sequences. In particular, a directed graph of usual activity is formed as a basis for determining unusual activities. Next, activities that were actually performed are determined by statistically analyzing records of microservice invocation in application diagnostic files. These activity sequences are overlaid on the directed graph to determine relative fit by using a trace coverage percentage score. Application instances or activities with low relative fit are deemed suspicious. If the low fit persists for an extended duration, then the instances or activities are deemed unusual and an individual is alerted to begin a manual review.