Abstract: A redundant processing fabric in an autonomous vehicle may include: processing, by a first processing unit of a plurality of processing units, sensor data from a first sensor of a plurality of sensors, where the plurality of processing units are coupled to the plurality of sensors via a switched fabric, wherein the plurality of processing units and plurality of sensors are included in the autonomous vehicle, wherein the sensor data corresponds to an environment external to the autonomous vehicle; determining a failure in processing the sensor data by the first processing unit; and severing, in the switched fabric, a first communications path between the first sensor and the first processing unit; and establishing, in the switched fabric, a second communications path between the first sensor and a redundant processing unit.

Abstract: Apparatuses, methods, systems, and program products are disclosed for analytics-based anomaly detection. An apparatus includes a processor and a memory that stores code executable by the processor. The code is executable by the processor to receive measurement data for a component of a device, determine a compression rate of the received measurement data by applying a compression algorithm to the measurement data, and generate an alert indicating a possible anomaly in an operation of the component represented by the measurement data in response to the determined compression rate satisfying a threshold compression rate for the at least one condition of the component.

Abstract: A method and system for health rank based virtual machine restoration using a conformal framework. With respect to enterprise data protection, solutions need to address two primary responsibilities: at the onset of failure or disaster, restore any running applications, as well as any lost or damaged data; and minimize (if not eliminate) the future occurrence of such failures or disasters. In tackling the latter responsibility, the disclosed method and system leverage health-score assessments to ensure the restoration of virtual machines onto healthy infrastructure. The aforementioned health-score assessments employ clustering to identify, and a conformal framework to rank, healthy hosts onto which virtual machines may be restored.

Abstract: An orchestration controller in a storage solution may establish namespaces, assign each namespace to a host, and establish software-defined storage controllers to handle input-output operations between the hosts and the namespaces. Each namespace is assigned to a given host and the input-output operations to and from the namespace are handled by a specific primary software-defined storage controller. In response to failure of the software defined controller, a secondary software-defined storage controller will take over handling of the input-output operations to and from the namespace. Also, in response to the failure of the software-defined storage controller, the host will direct subsequent input-output operations destined for the namespace to the secondary software-defined storage controller.

Abstract: Techniques regarding adaptive data recovery schemes are provided. For example, one or more embodiments described herein can comprise a system, which can comprise a memory that can store computer executable components. The system can also comprise a processor, operably coupled to the memory, and that can execute the computer executable components stored in the memory. The computer executable components can comprise a data management component that can modify a data recovery scheme based on performance data exhibited by a network of data centers and a data recovery requirement. The data recovery scheme can direct a relocation of data within the network.

Abstract: Aspects of the invention include receiving system data associated with a first system, the first system comprising a plurality of system components, wherein the system data comprises component data for each system component in the plurality of system components, obtaining historical performance data for each system component in the plurality of system components, determining at least one testing constraint associated with the first system, determining a test environment for the first system, the test environment comprising a plurality of test cases for the first system based on the system data, the historical performance data, and the at least one testing constraint, and executing the test environment on the first system.

Abstract: A cluster system has nodes connected by a first network, including a master node, a first node performing an IO request with respect to a first volume of a storage device capable of including a plurality of volumes through a second network, and a second node taking over processing of the first node at the time of a failure of the first node. When a failure of the first network occurs in the first node, the master node transmits a connection release instruction through the second network. When the connection release instruction is received, the storage device releases the connection between the first node and the first volume, and updates connection state management information for managing such a connection state. The first node acquires the connection state to be managed through the second network, and executes post-processing relevant to the first volume that is associated with the connection release instruction.

Abstract: In a method for data placement in a storage device including one or more blocks and a controller, the method including: receiving, by the controller of the storage device, a request to write data; determining, by the controller, a data status of the data; calculating, by the controller, one or more vulnerability factors of the one or more blocks; determining, by the controller, one or more block statuses of the one or more blocks based on the one or more vulnerability factors; selecting, by the controller, a target block from the one or more blocks based on the data status and the one or more block statuses; and writing, by the controller, the data to the target block.

Abstract: A method and an apparatus for migrating virtual machine includes monitoring a status of a compute node; determining whether the compute node meets a trigger condition; wherein the trigger condition comprising a time period of lost connection of the compute node reaches a predetermined time period, or an unstable status of the compute node; and if the compute node meets the trigger condition, transmitting a message to a control node to migrate the VM.

Abstract: A method may include receiving a communication from a user device, determining whether to forward the communication to a first computer system or a second computer system and forwarding the communication to the first computer system based on the determining. The method may also include generating, by the first computer system, a first response to the communication, determining whether an error occurred when processing the communication at the first computer system and forwarding the communication to the second computer system, in response to determining that an error occurred. The method may further include generating, by the second computer system, a second response to the communication and comparing the first response from the first computer system to the second response from the second computer system.

Abstract: Methods, systems, apparatuses, and computer-readable storage mediums are described for machine learning-based techniques for reducing the visual complexity of a dependency graph that is representative of an application or service. For example, the dependency graph is generated that comprises a plurality of nodes and edges. Each node represents a compute resource (e.g., a microservice) of the application or service. Each edge represents a dependency between nodes coupled thereto. A machine learning-based classification model analyzes each of the nodes to determine a likelihood that each of the nodes is a problematic compute resource. For instance, the classification model may output a score indicative of the likelihood that a particular compute resource is problematic. The nodes and/or edges having a score that exceed a predetermined threshold are provided focus via the dependency graph.

Abstract: A system detects failed service tier in cluster of servers, which are controlled by master node to execute applications and store data, in service tiers, which correspond to sets of server performance characteristics, in storage domains, which correspond to server racks, in cluster. The system identifies, by accessing database, applications installed on servers in failed service tier and any affinities that identified applications have for any type of server, any service tier, and/or any storage domain. The system updates, based on current configuration of cluster, identified affinities for identified applications. The system enables, by providing updated affinities for identified applications in database, master node to identify replacement servers, for identified applications, corresponding to set of server performance characteristics and server rack, and install identified applications in replacement servers, thereby enabling replacement servers to substitute for failed service tier and store data.

Abstract: System, apparatus, and/or a method for checking hardware components in an information handling system is disclosed that includes selecting a hardware component for testing; supplying power to the hardware component independent from the power supply provided by the information handling system; performing testing on the selected hardware component using power supplied by the independent power supply; determining the success or failure of the testing on the selected hardware component; indicating the result of the testing on the selected hardware component; and if the result of the testing on the selected hardware component is successful indicate the hardware component passed the testing, and if the result of the testing on the selected hardware component is not successful re-seat the hardware component and perform the testing on the selected hardware again.

Abstract: A quantum failsafe service (QFS) is disclosed herein. In one example, a first quantum computing device executes a QFS that receives a system stress indicator from a system monitor that tracks a status of the first quantum computing device and/or a status of qubits maintained by the first quantum computing device. The QFS determines, based on the system stress indicator, that a quantum service backup is to be performed for a quantum service running on the first quantum computing device, and obtains a profile snapshot representing a current state of the quantum service. The QFS service then performs superdense encoding of the profile snapshot using a first set of qubits entangled with a second set of qubits of a second quantum computing device, and the first set of qubits are sent to the second quantum computing device (e.g., for storage in a classical data repository, according to some examples).

Abstract: In response to receiving data to be stored in a storage system that includes a plurality of N drives, a method may include storing a first quantity of the data in a first N portions across a first half of the N drives; storing a second quantity of the data in a second N portions across a second half of the N drives; determining first parities to be stored on a first parity drive; determining second parities and storing them on a second parity drive; and calculating third parities based on both the first quantity of the data and the second quantity of the data, wherein the third parities are calculated in a diagonal fashion based on distinct elements of the first N portions and distinct elements of the second N portions, and storing the third parities on a third parity drive.

Abstract: Methods and systems are disclosed herein for using anomaly detection in timeseries data of user sentiment to detect incidents in computing systems and identify events within an enterprise. An anomaly detection system may receive social media messages that include a timestamp indicating when each message was published. The system may generate sentiment identifiers for the social media messages. The sentiment identifiers and timestamps associated with the social media messages may be used to generate a timeseries dataset for each type of sentiment identifier. The timeseries datasets may be input into an anomaly detection model to determine whether an anomaly has occurred. The system may retrieve textual data from the social media messages associated with the detected anomaly and may use the text to determine a computing system or event associated with the detected anomaly.

Abstract: A system and method of detecting defects in an analog circuit is provided. A method includes identifying a channel connected block (CCB) from a netlist, creating defect for the CCB to be injected during a simulation, obtaining a first measurement of an output node of the CCB by performing a first analog circuit simulation for the CCB based on providing excitations as inputs to the CCB and obtaining a second measurement of the output node of the CCB by performing a second analog circuit simulation for the CCB based on providing the excitations as the inputs to the CCB and injecting the defect. The method can further include determining a defect type based on the first measurement and the second measurement.

Abstract: Techniques for managing data involve receiving a write request to write a data block into a first stripe in a disk array, the write request comprising a first storage address for storing the data block. The techniques further involve determining, based on the first storage address, a first group of disks related to a data portion of the first stripe and a second group of disks related to a parity portion of the first stripe. The techniques further involve, in response to a first disk in the first group of disks being unavailable, storing a data sub-block related to the first disk into a first parity portion of the parity portion such that the data block is stored in the first stripe, the first parity portion being located at a second disk in the second group of disks. The techniques further involve returning a response to the write request, the response comprising a first indication indicating a status of the disks in the disk array.

Abstract: A plurality of computing devices are communicatively coupled to each other via a network, and each of the plurality of computing devices is operably coupled to one or more of a plurality of storage devices. One or more of the computing devices and/or the storage devices may be used to rebuild data that may be lost due to a power failure.

Abstract: A method for protecting data in a storage system is disclosed. In one embodiment, such a method includes detecting, by a first hardware management console, first battery-on status associated with a first uninterruptible power supply. The method further detects, by a second hardware management console, second battery-on status associated with a second uninterruptible power supply. The method communicates, from the first hardware management console to the second hardware management console, the first battery-on status. The method then triggers, by the second hardware management console, a dump of modified data from memory to more persistent storage upon detecting both the first battery-on status and the second battery-on status. A corresponding system and computer program product are also disclosed.