Abstract: A system and method for providing access to third-party software tools as a service. A service access manager can communicate with one or more third parties to manage licenses associated with third-party software tools. A machine learning model can be trained using logs generated by the system and causes of detected errors to automatically determine the cause of errors occurring in the future. Vendor logs generated by software instances instantiated by third-party systems can be collected and used to improve error attribution.

Abstract: Mechanisms for reducing the impact of drive parameter writes on solid state drive (SSD) performance are provided, the methods including: saving one or more SSD drive parameters of an SSD to volatile memory of the SSD using an SSD controller; detecting a power-loss condition in the SSD; and copying the one or more SSD drive parameters from the volatile memory of the SSD to non-volatile memory of the SSD. In some embodiments, the SSD is a NAND SSD. In some embodiments, the one or more SSD drive parameters include one or more of: a drive health parameter, a drive internal statistic, drive thermal information, drive debug information, a number of host and non-volatile memory read and writes, media error handling data, temperature and throttle information, and firmware download information. In some embodiments, the volatile memory is one or more of: random-access memory and dynamic random-access memory.

Abstract: A read scrub management system of a data storage device maintains and updates information associated with one or more Cell Voltage threshold Distribution (CVD) time tags. Each time tag is associated with one or more memory blocks and includes information about operating parameters associated with the memory blocks. Each time tag also includes its own read scrub counter. The read scrub management system increments the read scrub counter associated with a particular time tag each time one or more memory blocks associated with the particular time tag are accessed. When the read scrub counter reaches or exceeds a threshold value, the read scrub management system initiates a read scrub operation on the memory block(s) associated with the particular time tag.

Abstract: A method for repairing faulty memory locations of a memory while a program from the memory is being executed by a computer. The program controls a technical device. When the program is being executed, addresses of faulty memory locations in the memory and correct values of the faulty memory locations are detected. The program provides time periods for repairing the faulty memory locations. The time periods are selected such that the control of the technical device is not hindered. For the repair, the correct values are written to the faulty memory locations.

Abstract: A storage device includes a memory storage region and a controller having a processor. The processor retrieves user data from the memory storage region using a physical block address corresponding to a logical block address (LBA), in response to a read command. The retrieved user data includes a first hash received through a host interface in a prior host data transmission. The processor further performs error correction on the user data to generate error-corrected user data. The processor further causes a cryptographic engine to produce a second hash of the error-corrected user data. The first hash is compared to the second hash associated with the error-corrected user data to determine a match result. A notification is generated in response to the match result.

Abstract: Real system devices (RSD's) emulate virtual system devices (VSD's); system elements can use RSD's and manipulate VSD's, while users can only use VSD's. Identifying when RSD's have erroneous data. Providing a mapping of RSD's to VSD's, to recover a maximum set of VSD's. Providing a mapping of VSD's to RSD's, to recover a specified most valuable VSD. Reconstructing VSD's from RSD's having erroneous data, and coordinating with a user's assistance to couple RSD's in an order allowing data recovery. Metadata is maintained coupling data identifiable on VSD's with corresponding data on RSD's; it is possible to trace connections between RSD's and VSD's even without complete data.

Abstract: Methods, systems, and products for health signature based load shifting for part longevity may include monitoring one or more variables associated with each of multiple redundant parts of a computing system, where one or more of the redundant parts are experiencing a load, generating, based on the monitored variables, a health signature for each of the redundant parts, and shifting, based on the health signatures, the load between the redundant parts.

Abstract: Instead of incurring interface errors caused by power drops, continuously track all the channels between the controller and the storage device (both in-band and side-band channels). The tracking will include extracting relevant indications and use a prediction model that correlates between the tracked indications to later occurrence of power drop events. In response to the prediction results, the system may perform different rehabilitation operations (countermeasures). The controller will monitor different indications from the storage element and power supply to predict a signal integrity degradation marginality event on the interface. The monitoring and mitigation strategy relies on an open-ended system. The controller does not employ a real-time continuous return channel from the storage device that may signal pass/fail conditions.

Abstract: The present disclosure relates to systems, methods, and computer-readable media for identifying anomalies of failure events on a cloud computing system and determining cross-component and cross-layer correlation between change events that occur on the cloud computing system and the failure events associated with the anomalies. In particular, this disclosure describes a system that receives telemetry related to change events and failure events across any number of computing layers of a distributed computing environment (e.g., a cloud computing system) and detects anomalies based on counts of failure events that are manifested over discrete periods of time. Based on these detected anomalies, the anomaly correlation system can determine cross-layer and cross-component correlations between selective change events and the detected anomalies of failure events.

Abstract: Methods, systems, and devices for persistent health monitoring for volatile memory devices are described. A memory device may determine that an operating condition associated with an array of memory cells on the device, such as a temperature, current, voltage, or other metric of health status is outside of a range associated with a risk of device degradation. The memory device may monitor a duration over which the operating condition is outside of the range, and may determine whether the duration satisfies a threshold. In some cases, the memory device may store an indication of when (e.g., each time) the duration satisfied the threshold. The memory device may store the one or more indications in one or more non-volatile storage elements, such as fuses, which may enable the memory device to maintain a persistent indication of a cumulative duration over which the memory device is operated with operating conditions outside of the range.

Abstract: A method for monitoring a nonlinear dynamic process and a computing system are provided. The method includes training a model based on sample data, wherein the model comprises: a first layer, wherein the first layer is configured to linearize the sample data using one or more dimension lifting techniques; a second layer, wherein the second layer is configured to extract reduced-dimension dynamic latent variables (DLVs) from the linearized sample data using a reduced-dimension model; and a third layer, wherein the third layer is configured to parameterize the extracted reduced-dimension DLVs using a latent state space model; and inputting data from the nonlinear dynamic process into the trained model for monitoring the nonlinear dynamic process.

Abstract: Systems and methods are provided for implementing system object tracking for rule violation detection. In various examples, in response to a trigger event, a computing system may track a system object by tracking a tracker object corresponding to a memory address range of a database that has been allocated to the system object. Contemporaneous with the trigger event, the computing system determines, based on tracking of the tracker object, whether a system rule associated with the system object has been violated. Based on a determination that a system rule associated with the system object has been violated, the computing system triggers at least one action associated with the system object, including performing a contemporaneous error check, sending messages indicating an error caused by violation of the system rule, identifying a system component or driver that caused the error, and/or causing an immediate system crash.

Abstract: The present application discloses a health degree evaluation method of a software product. For a software product to be evaluated, a usage condition of using the software product to be evaluated by a client may represent a health degree of the software product to be evaluated. Therefore, when the health degree of the software product to be evaluated is evaluated, usage parameters for target clients to use the software product to be evaluated may be obtained, the usage parameters may represent the condition of usage by target clients of the software product to be evaluated, wherein the usage parameters may include at least two of a usage depth parameter, a usage breadth parameter and a usage frequency parameter. After the usage parameters is obtained, the health degree of the software product to be evaluated may be determined according to the usage parameters.

Abstract: Methods, systems, and apparatuses include determining, by a memory subsystem, use model statistics for a memory portion of the memory subsystem, where the use model statistics include a count of commands received by the memory subsystem from a host system targeting the memory portion and details about the memory subsystem. It is determined that the memory subsystem is powering down. The use model statistics are stored in a use model statistics storage of the memory subsystem by the memory subsystem in response to determining that the memory subsystem is powering down.

Abstract: A computer-implemented system and method can be used to identify policy information applicable to a compute resource within a specified time range, the policy information related to data management for the compute resource. Based on the identified policy information, a set of expected data management events for the compute resource is generated within the specified time range. The set of expected data protection events is modified based on information related to exceptions to the data management indicated by the policy information. The modified set of data protection events provides lineage information for the compute resource.

Abstract: Methods, systems, and devices for error log indication via error control information are described. For instance, a memory device may transmit, to a host device, a first signal including a set of error control bits indicating that an error log of the memory device includes information for use by the host device. The memory device may receive, from the host device in response to the first signal, a second signal including a request to retrieve the information of the error log. The memory device may transmit, to the host device in response to the second signal, a third signal including the information of the error log.

Abstract: Systems and methods are provided for managing logging and telemetry data in a cloud provider network including block storage volumes (“disks”) and virtual machine instances by scanning data written to the block storage volumes by the virtual machine instances. The disk recycler system can receive configuration information to scan for, obtain, and upload data to logging and telemetry services hosted by the cloud provider network. For example, in the scenario of a virtual machine instance failure, the disk recycler system may upload leftover data from the block storage volume to the relevant logging and telemetry services to avoid gaps in data required by the services of the cloud provider network.

Abstract: Techniques are provided for persistent memory file system reconciliation. As part of the persistent memory file system reconciliation, high level file system metadata associated with a persistent memory file system of persistent memory is reconciled. Client access to the persistent memory file system is inaccessible until reconciliation of the high level file system metadata has completed. A first scanner is executed to traverse pages of the persistent memory in order to fix local inconsistencies associated with the pages. A local inconsistency of a first set of metadata or data of a page is fixed using a second set of metadata or data of the page. The first scanner is executed asynchronously in parallel with processing client I/O directed to the persistent memory file system.

Abstract: A method and an apparatus for assessing a risk caused by improper use of a cluster data resource, an electronic device and a storage medium are provided. A high-risk diagnosis indicator in a storage assessment dimension and a high-risk diagnosis indicator in a computation assessment dimension are obtained. The amount of high-risk diagnosis indicators in the storage assessment dimension that are satisfied in the use process of the data storage resource and the amount of high-risk diagnosis indicators in the computation assessment dimension that are satisfied in the use process of the data computation resource are counted, and are recorded as high-risk indicator trigger quantities. Risk on the data storage resource is assessed based on the high-risk indicator trigger quantity in the storage assessment dimension, and risk on the data computation resource is assessed based on the high-risk indicator trigger quantity in the computation assessment dimension.

Abstract: A data management system may support a configuration backup of a first backup system that manages backup procedures for data of a host environment that is separate from the first backup system. The data management system may transmit, to the first backup system, a request to generate the configuration backup that includes information for the one or more backup procedures managed by the first backup system. The data management system may cause the configuration backup to be stored in a separate storage location. In response to first backup system failure, the data management system may transmit, to a second backup system, a request to apply one or more configurations for the first backup system to the second backup system based on the stored configuration backup for the first backup system.