Abstract: Systems and methods are presented for identifying and addressing anomalies in a system. An exemplary method comprises collecting parameters of one or more components of the system, assessing conformity of a state of the system by comparing the collected parameters to one or more state models, wherein the one or more state models describe normal and anomalous states, identifying one or more anomalies based on the assessment of conformity, obtaining a database of third party information for the one or more components, replacing the collected parameters with the third party information and interrogating the one or more state models using the third party information, responsive to identifying no further anomalies in the interrogation, identifying one or more components that are compatible with the system from the obtained database, and selecting a single component from the one or more components to address the identified anomalies, based on one or more criteria.

Abstract: A method, computer program product, and computing system for associating a local communications port on a local computing device with a DUT communications port on a Device-Under-Test. A user is enabled to remotely access the DUT communications port via the local communications port using a remote computing device.

Abstract: Systems and methods for implementing a lightweight checkpoint technique for resilience against soft errors are disclosed. The technique provides effective, safe, and timely soft error detection and recovery using software. In an exemplary aspect, resilience against data flow errors and control flow errors is provided in critical or mixed-critical applications in each basic block or at critical basic blocks. Verified register preservation is provided at each basic block, along with memory preservation checkpoints. In this manner, soft errors are quickly detected and addressed. The register and memory preservation further allows for safe re-execution from recoverable soft errors. Control flow errors can also be detected at the beginning and/or end of each basic block.

Abstract: In one or more embodiments, one or more systems, processes, and/or methods may determine that an external power supply coupling is coupled to an information handling system (IHS); may determine that power is not being received via the external power supply coupling; may, after determining that determining that power is not being received via the external power supply coupling, determine that a battery power supply of the IHS is able to power the IHS; may determine that a user is not present; may save a state of the IHS to a non-volatile memory medium; and may power down the IHS. In one or more embodiments, the one or more systems, processes, and/or methods may further receive power via the external power supply coupling; may power up the IHS; and may restore the state of the IHS from the non-volatile memory medium.

Abstract: Methods and apparatus for use in a dispersed storage network (DSN) to facilitate coordination between dispersed storage computing devices and dispersed storage integrity processing unit rebuild modules. In one example, data may be rebuilt in a DSN by determining a rebuild task to be executed based on an attempt to access data in the DSN. Status information regarding the rebuild task is then generated and forwarded to the dispersed storage computing device and/or one or more dispersed storage units for subsequent attempts to access data in the DSN.

Abstract: A method for controlling a storage device is provided. The method may include: transmitting an initial command conforming to a first communications protocol and a data payload including a command parameter conforming to a second communications protocol to the storage device; transmitting a setting command conforming to the first communications protocol to the storage device; transmitting a confirmation command conforming to the first communications protocol to the storage device; and according to a data payload corresponding to the confirmation command, confirming whether the initial command, the setting command, and the confirmation command are successfully executed.

Abstract: An improved core network that can monitor micro-level issues, identify specific services of specific nodes that may be causing an outage, and perform targeted node failovers in a manner that does not cause unnecessary disruptions in service is described herein. For example, the improved core network can include a failover and isolation server (FIS) system. The FIS system can obtain service-specific KPIs from the various nodes in the core network. The FIS can then compare the obtained KPI values of the respective service with corresponding threshold values. If any KPI value exceeds a corresponding threshold value, the FIS may preliminarily determine that the service of the node associated with the KPI value is responsible for a service outage. The FIS can initiate a failover operation, which causes the node to re-route any received requests corresponding to the service potentially responsible for the service outage to a redundant node.

Abstract: Systems and methods are presented for data quality monitoring. Data quality monitors may be created and configured to identify objects with specified data quality issues and/or property values. Objects identified by a data quality monitor can be presented to users for confirmation and resolution. Properties used by the data quality monitor to match objects may also be displayed to users.

Abstract: A data stream processing device includes a plurality of data providing units, a plurality of processing units, and control circuitry. The data providing units are configured to output data values received via a plurality of data inputs, respectively. The processing units are configured to generate data outputs based on the data values, respectively. The control circuitry includes a mode selection input and is configured to simultaneously provide data values of different data streams to the data inputs of the data providing units, respectively, in response to the mode selection input receiving a signal indicating a first mode, and simultaneously provide a plurality of successive groups of data values of one of the data streams to the data inputs of the data providing units, respectively, in response to the mode selection input not receiving the signal indicating the first mode.

Abstract: A storage system in one embodiment comprises a host processor, and a solid-state storage device coupled to the host processor and comprising a non-volatile memory and a storage controller. The host processor is configured to initiate an error scanning operation on a designated portion of the non-volatile memory by directing at least one read command to the storage controller. The read command is configured to indicate to the storage controller that data read from the non-volatile memory responsive to the read command is not to be returned to the host processor. For example, the read command may illustratively comprise a Scatter Gather List (SGL) bit bucket descriptor indicating that the data read from the non-volatile memory responsive to the read command is to be discarded rather than returned to the host processor. The storage controller records any detected errors in a media error log and notifies the host processor of such errors.

Abstract: A memory system may include: a nonvolatile memory device including a plurality of memory blocks, each of which includes a plurality of pages, and among which a subset of memory blocks are managed as a system area and remaining memory blocks are managed as a normal area; and a controller may store system data, used to control the nonvolatile memory device, in the system area, and storing boot data, used in a host and normal data updated in a control operation for the nonvolatile memory device, in the normal area, the controller may perform a checkpoint operation each time storage of N number of boot data among the boot data is completed, and may perform the checkpoint operation each time the control operation for the nonvolatile memory device is completed, ‘N’ being a natural number.

Abstract: A facility for event failure management is provided, which includes providing a failed event database containing failed event information relating to failed events and one or more components associated with each of the failed events. Upon modification to a component associated with a failed event, the failed event is retried. Based on a result of retrying the failed event, failed event information of the failed event database is updated. The failed event database may therefore be dynamically and/or automatically updated so that it contains up-to-date and appropriate information for predicting and/or managing event failures.

Abstract: In one example, a distributed cluster may include compute nodes having a master node and a replica node, an in-memory data grid formed from memory associated with the compute nodes, a first high availability agent running on the replica node, and a second high availability agent running on the master node. The first high availability agent may determine a failure of the master node by accessing data in the in-memory data grid and designate a role of the replica node as a new master node to perform cluster management tasks of the master node. The second high availability agent may determine that the new master node is available in the distributed cluster by accessing the data in the in-memory data grid when the master node is restored after the failure and demote a role of the master node to a new replica node.

Abstract: A system and method to balance computational loads across multiple computing systems, such as servers in a server cluster, is disclosed. The system includes a load balancer. Upon receiving a new computing request corresponding to an expected throughout, the load balancer identifies a computing system that is most likely to fail and sends the new computing request to a different computing system. The load balancer uses a mutational algorithm to identify potentially problematic throughputs for a given computing system in a given state. The mutational algorithm is used to determine latency-throughput curves that are fit to a data population that includes many diverse data points with relatively high slopes in a 2D latency-throughput space.

Abstract: A computer-implemented method according to one embodiment includes establishing a predetermined checkpoint and storing a log of duplicate read data in association with the predetermined checkpoint during a running of an application that is processing at least one data set, the duplicate read data including an image of all data retrieved from the at least one data set in response to a plurality of data reads made by the application before the predetermined checkpoint; identifying a first failure of the application; and restarting the application and performing a first replay of the application in response to the first failure.

Abstract: A system and method for automated computer system diagnosis and repair is provided. The system and method may allow for the automated diagnosis and repair of computer system errors without needing a user to manually engage a service desk, help desk, and/or the like. A user terminal may interact with a tech care module to generate a user repair request comprising the computer system error and data relating to the error. The system may analyze the user repair request and retrieve a repair script relating to the computer system error. The system may execute the repair script on the user terminal to resolve the computer system error. The system may also implement reporting modules to ensure that the computer system error is remediated and to update the repair scripts.

Abstract: A method for execution by one or more processing modules of a storage network (SN) begins with the one or more processing modules scanning a storage node of the SN at a predetermined interval to determine whether an erasure encoded data slice (EEDS) of a set of erasure encoded data slices (EEDSs) is corrupt, where the set of erasure encoded data slices (EEDSs) is generated from object data using an erasure error encoding dispersal function. The method continues with the one or more processing modules determining that an EEDS is corrupt and in response, rebuilding the EEDS in place in the storage node.

Abstract: A first tier of error correcting code operations on a data block may be performed. The first tier of error correcting code operations on the data block may be determined to be associated with an unsuccessful correction of an error of the data block. Responsive to determining that the first tier of error correcting code operations on the data block are associated with the unsuccessful correction of the error of the data block, a remix operation on the data block to change a logical to physical association of the data block from a first logical association to a second logical association may be performed.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for receiving a request to generate a backup of a distributed computing system; generating, by each of the plurality of components of the distributed computing system, one or more backup artifacts; generating, by each of the plurality of components of the distributed computing system, verification data, the verification data being metadata about the contents of the generated backup artifacts; obtaining a second request to validate the backup; provisioning a restore environment; processing the plurality of backup artifacts to restore the plurality of components in the provisioned restore environment; performing a verification process using respective verification data for the restored component, wherein each verification process determines whether contents of the restored component matches the respective verification data for the restored component; and outputting a result of the verification process.

Abstract: Aspects of the disclosure relate to using natural language processing to identify a context of failure associated with a channel error and analyzing the identified context of failure in relation to historic data by machine learning algorithms to identify one or more of a severity ranking, alternate channel, and solution for the channel error. In some instances, a computing platform may receive data corresponding to a system event associated with a channel of server infrastructure, identify a technical issue, customer intent, and customer sentiment of the system event, determine a context of failure of the system event, generate a mapping of the context of failure in relation to historic data, and identify a suggested solution, severity assignment, and alternate channel for the system event based on the mapping of the context of failure in relation to the historic data.