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.

Abstract: An apparatus comprises a processing device configured to generate a model characterizing relationships between devices in an information technology infrastructure, to build a device dependency chain for the devices based at least in part on the generated model, and to predict workload for each of the devices in each of two or more time slots of a given time period. The processing device is also configured to determine a deployment schedule for the devices based at least in part on the device dependency chain and the predicted workload for each of the devices in each of the two or more time slots of the given time period, to identify an operation to be performed on the devices, and to utilize the deployment schedule to select ones of the devices on which to perform the identified operation in each of the two or more time slots of the given time period.

Abstract: A method includes extracting data pertaining to a plurality of user actions in connection with one or more changes to one or more of a plurality of applications, and training one or more machine learning models with the extracted data. The one more machine learning models are used to predict whether a user should receive a given notification in connection with a given change to a given application of the plurality of applications. In response to predicting that the user should receive the given notification, content of the given notification is determined. The method further includes generating the given notification for the user, and transmitting the given notification to the user.

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: Data theft protection for a computing device is provided by flagging a suspicious user within the pre-boot environment by systematic evaluation to determine suspicious location and/or anomalous user behavior. Depending on a suspicion score and a risk evaluation, the system automatically triggers one or more actions with respect to the data on the computing device.

Abstract: A system, method, and computer-readable storage medium provide single sign-on (SSO) in a nested virtualization environment by routing authentication tokens received from an authentication server through the hierarchy of virtual machines (VMs) using secure data communications tunnels between each hypervisor and its respective VMs. A key store stores SSO authentication tokens for users of the nested VMs, and a key controller ensures that each login by a user to a separate VM is associated with its own token. Each login request is uniquely tagged to identify the particular VM requesting credentials, so that the responsive authentication token can be properly routed through the hierarchy. Moreover, session preferences may be associated with each user and/or each VM, enabling a rules evaluator to determine, for each login request, whether SSO functionality should be provided or whether the user should be required instead to provide new login credentials.

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: A processing platform comprises at least one processor coupled to at least one memory, and is configured to obtain a set of profiles for configuring a set of devices in an information processing system wherein, for a given device, a given profile comprises one or more configuration attribute values corresponding to one or more components of the given device. The processing platform divides each of at least a portion of the profiles of the set of profiles into two or more sub-profiles to form a set of sub-profiles wherein, for a given divided profile of a given device, two or more sub-profiles respectively correspond to two or more components of the given device. The processing platform stores the set of sub-profiles for use in configuring another device in the information processing system.

Abstract: A method comprises collecting data from a computing environment comprising one or more storage devices, wherein the data comprises information identifying assignments of the one or more storage devices to one or more servers in the computing environment. In the method, the data is analyzed using one or more machine learning algorithms, wherein the analyzing comprises predicting whether a given configuration of the one or more storage devices in combination with the one or more servers is a specified configuration. The method also includes generating a storage configuration recommendation for a user based on the analysis, and transmitting the storage configuration recommendation to the user.

Abstract: A method comprises collecting device data and connection data corresponding to a plurality of connected devices in a system, and identifying a plurality of network connections between two or more of the plurality of connected devices from the device data and the connection data. In the method, one or more configuration issues across one or more of the plurality of network connections are detected, and a visualization of a topology of the plurality of connected devices in the system is generated. The visualization comprises a depiction of the plurality of connected devices, the plurality of network connections and the one or more configuration issues.

Abstract: An apparatus comprises at least one processing device comprising a processor coupled to a memory. The at least one processing device is configured to receive, at a first microservice, context information for a second microservice, the context information characterizing a current state of execution of one or more tasks by the second microservice. The at least one processing device is also configured to detect, by the first microservice, failure of the second microservice. The at least one processing device is further configured to re-initiate, by the first microservice, the second microservice utilizing the received context information for the second microservice. Re-initiating the second microservice utilizing the received context information for the second microservice enables the re-initiated second microservice to continue execution of the one or more tasks from the current state.

Abstract: An information handling system (IHS) includes spatially diverse IHS components and temperature sensors disposed with respect to the spatially diverse IHS components. A fan controller defines cooling sections of the IHS for spatially diverse fans based on topological information as to locations of the spatially diverse IHS components, and selectively controls the spatially diverse fans according to component temperatures obtained from the temperature sensors and according to the cooling sections.

Abstract: One example method includes receiving, from a VM, a request for a software license, in response to the request, transmitting a UUID to the VM, receiving, from the VM, a response that comprises a first encrypted UUID corresponding to the request, and transmitting a client object that includes the first encrypted UUID, and the client object serves as a request for entry of the client object in a database of a cloud computing site.

Abstract: A method comprises extracting data for one or more assets corresponding to a user, and analyzing the data using one or more machine learning models. The analyzing comprises predicting whether the one or more assets will require at least one of replacement and service. In the method, one or more entitlement recommendations for the user are generated based on the analysis, and the one or more entitlement recommendations are transmitted to the user.

Abstract: A method comprises collecting browsing activity data of at least one user in connection with at least one electronic commerce item, and collecting feature data of the at least one electronic commerce item. In the method, the browsing activity data and the feature data are analyzed using one or more machine learning models. At least one of a title and a description for the at least one electronic commerce item is generated based on the analysis, and are displayed on an interface for viewing by the at least one user.

Abstract: Methods, apparatus, and processor-readable storage media for artificial intelligence-based redundancy management are provided herein. An example computer-implemented method includes obtaining telemetry data from one or more client devices within at least one system; predicting one or more hardware component failures in at least a portion of the one or more client devices within the at least one system by processing at least a portion of the telemetry data using a first set of one or more artificial intelligence techniques; determining, using a second set of one or more artificial intelligence techniques, one or more redundant hardware components for implementation in connection with the one or more predicted hardware component failures; and performing at least one automated action based at least in part on the one or more redundant hardware components.

Abstract: In some examples, a computing device may determine, based on sensor data, that the computing device is in a public environment. In response, the computing device may display an entry wheel to enable a user to enter a password. The entry wheel may include multiple input symbols arranged equidistant around a circle. In some cases, one or more geometric patterns linking a portion of the input symbols may be displayed. After receiving an individual character of the password, the computing device may display the entry wheel rotated a number of positions in either a clockwise or counter-clockwise direction and display zero or more of the geometric patterns. After all the characters of the password have been received, the computing device may determine if the password matches a previously stored password. If the password matches, the computing device may transition from a low power state to an active state.

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: Various systems and methods are provided for using a response tracking plugin to detect and inform users in real time when one or more recipients of an email are actively responding to that email. In one embodiment, the functionality disclosed herein can be applied to an email that was sent to a plurality of recipients, including at least a first and second recipient, and where the email comprises a plugin that is configured to enable response tracking. One such embodiment comprises receiving the email; monitoring for a first pulse from the second recipient of the email, where the pulse is configured to indicate that the second recipient of the email has begun a reply to the email; and in response to receiving the first pulse, displaying an indication that comprises information about the second recipient of the email.