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 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 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 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 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: 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: 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 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: 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.

Abstract: The described technology is generally directed towards predicting the survival of a storage device (e.g., a hard disk drive or a solid state drive) to a specified time point, expressed as a confidence score, via a prediction uncertainty quantifier framework with a machine learning classifier. The confidence score corresponds to the likelihood of a storage device surviving until a specified time point (e.g., for n hours). In one implementation, a conformal prediction framework provides the confidence score for a storage device, based on survival rate data predicted using recent telemetry data collected for that storage device by an online semi-parametric Mondrian survival forest classifier. Updated confidence scores based on updated telemetry data can be obtained at various evaluation stages to reevaluate whether to take remedial action with respect to a storage device (e.g., replace the storage device). Multiple storage devices can be ranked by their respective associated confidence scores.

Abstract: Methods, apparatus, and processor-readable storage media for predicting component lifespan information by processing user install base data and environment-related data using machine learning techniques are provided herein. An example computer-implemented method includes obtaining install base data associated with at least one system component and environment-related data associated with usage of the at least one system component; performing feature analysis on at least a portion of the obtained data using a first set of machine learning techniques; clustering, based on the feature analysis, at least a portion of the install base data and at least a portion of the environment-related data into one or more groups using a second set of machine learning techniques; generating at least one lifespan information prediction attributed to the at least one system component based on the clustering; and performing at least one automated action based on the at least one lifespan information prediction.

Abstract: An apparatus comprises a processing device configured to generate a model of a plurality of devices characterizing relationships between the devices, to build a device dependency chain for the devices based on the model, to predict workload for each of the devices in one or more time slots of a given time period, and to determine a deployment schedule for the devices based on the device dependency chain and the predicted workload. The processing device is also configured to utilize the deployment schedule to select a device of the devices on which to perform an operation, to determine whether the selected device corresponds to an additional device of the devices configured to operate in place of the selected device during performance of the operation, and to control performance of the operation on the selected device responsive to the determination of whether the selected device corresponds to the additional device.

Abstract: Various systems and methods are provided for using dummy characters to provide enhanced security of a user's login credentials. The functionality disclosed herein provides specific steps for the creation, evaluation, storage, and use of such dummy characters in conjunction with a user's login credentials. Dummy characters can be thought of as characters that are not part of a user's actual password, but which are mixed in and around the actual characters when the password is being entered, in order to protect a user's true password from prying eyes and nefarious actors. Dummy characters can be associated with a specific user and/or a specific device or devices associated with a specific user. The functionality provided herein prevents a nefarious actor from simply repeating an entire password string (including the dummy characters) on a device that is not associated with the user whose credentials the nefarious actor is attempting to misappropriate.

Abstract: An information handling system may obtain timing information for processing among layers of a first client-side information handling system, and compare the timing information to threshold values to provide a comparison. The information handling system may use the comparison to identify an area of the first client-side information handling system in which a problem exists, and initiate remedial action directed to the problem.

Abstract: An information handling system includes a processor configured to store a first module of a software application, the first module of the software application selected based on customer journey information pertaining to usage of the software application. The processor begins execution of the first module prior to receipt of a second module of the software application, the second module selected based on the customer journey information.

Abstract: A method comprises analyzing performance data of a system using one or more machine learning techniques. The system comprises a plurality of hardware components. In the method, a priority list of the plurality of hardware components is generated based on the analysis, and power from one or more power sources is distributed to one or more of the plurality of hardware components based on the priority list.

Abstract: In some examples, a server receives configuration data from a device. The server receives a software or firmware update from a vendor and determines, based on the configuration data, that the update is installable on the device. The server creates and configures a container, based on the configuration data, to create a replica of the device. The server installs the update in the replica and performs multiple tests that generate logs. If the logs indicate that the update caused no issues, the server sends the update to the device. If the logs indicate that the update caused an issue, the server sends the update to the vendor. In response, the server receives, from the vendor, a modified update that addresses the issue, installs the modified update in the replica, performs the tests, determines that the modified update causes no issues, and sends the modified update to the device.

Abstract: An access credential is modified at one device, wherein the device is part of a secure private network of multiple devices. Each other device in the secure private network receives notification of the modification. The credential modification is implemented when at least a subset of the other devices each accept the credential modification.