Abstract: Harmonization of failure domains in a distributed system is provided herein. A data storage system as described herein can include a memory that stores computer executable components and a processor that executes computer executable components stored in the memory. The computer executable components can include a node assignment component that assigns computing nodes in the data storage system to respective failure domains of a set of data failure domains, a hashing component that generates hashing information associated with respective computing nodes of the computing nodes assigned to a selected failure domain of the set of failure domains, and a group update component that designates at least one computing node of the computing nodes in the selected data failure domain to perform an operation associated with the hashing information.

Abstract: A method for execution by dispersed storage failure detection unit of a dispersed storage network includes generating a storage unit weights and storage set weights based on the storage unit weights. One storage unit that meets a weight-adjustment trigger condition is identified, and a new storage unit weight for the identified storage unit is generated. A first data migration within the storage set that includes the identified storage unit is facilitated based on the storage unit weights. A failing set of storage units in a second storage set is identified. A new storage set weight for the second storage set is generated when the number of storage units in the failing set compares favorably to a failure threshold number. A second data migration that includes transferring data slices stored in the second storage unit to other storage sets is facilitated based on the storage set weights.

Abstract: In a system having at least two data storage and processing sites, each capable of alternatively serving as a primary site and a backup or target site, disaster recovery migration is optimized by cognitively analyzing at least one system parameter. Using machine learning, at least one pattern of that system related parameter is predicted, and planned or unplanned migration procedures are performed based on the predicted parameter patterns. The analyzed parameter may be data traffic at the sites, and the predicted data traffic pattern is used to assign primary and backup site status to those sites. The analyzed parameter may be the occurrence of events or transactions at the sites, and the predicted event or transaction patterns may be used to determine times of disaster recovery procedure processing so as to not interrupt a critical event or transaction.

Abstract: A memory device includes a memory array having at least one memory bank, where the at least one memory bank includes a target memory array and a clone memory array. The clone memory array corresponds to the target memory array and is configured to store the same data as in the target memory array. When a command that is applied to the target memory array to perform an operation, the command is also applied to the clone memory array. An error detection method adapted to a memory device having at least one memory bank that comprises a target memory array and a clone memory array is also introduced.

Abstract: An example operation may include one or more of receiving, by a disaster recovery orchestrator, configuration changes independent from a disaster recovery test schedule, from one or more monitoring agents at each of an information technology system, analyzing incremental configuration changes since a previous disaster recovery test for potential to limit a need for unnecessary disaster recovery retest, determining component level changes at each information technology system that impact disaster recovery test readiness, initiating a partial disaster recovery retest without regard to periodic disaster recovery test schedules, in response to incremental configuration changes that are at the information technology system component-level, and invoking a blockchain service to generate blockchain transactions, the blockchain transactions committing configuration changes, disaster recovery testing actions, and disaster recovery testing results to a shared ledger of a blockchain network.

Abstract: Technologies are generally described to provide a passive monitoring system employing a logging schema to track usage data in order to analyze performance and reliability of a service. The logging schema may be configured to track user requests as each request is received and processed at individual subsystems of the collaborative service. A logging entry may be created at a data store of the service, where the logging entry includes a subsystem name, an operation performed by the subsystem to fulfill the request and start and end times of the operation. The logging schema may also detect errors fulfilling the requests, and may classify detected errors into a bucket, where each bucket denotes a failure scenario. Reliability of the service may be calculated based on analysis of the buckets to compute error rates. Reports may be generated to enable continuous monitoring of a performance and reliability of the system.

Abstract: A computer-implemented method includes detecting that a first script has been modified to an updated script and that the first script is currently running. A data key point is selected from among a set of data key points available in the first script. At the selected data key point in the first script, a current state of the first script is saved in a storage object external from the first script, responsive to detecting that the first script has been modified. An execution point is selected in the updated script. The current state of the first script is loaded into the updated script. The updated script is run from the execution point, with the current state of the first script.

Abstract: In an embodiment, automatic verification of a system backup operation is provided. This verification is achieved by copying executable files to a writeable file system representing a backup recovery point and configuring an operating system within the writeable file system to execute a particular service upon startup of the operating system. Moreover, a validation virtual machine (VM) associated with a backup recovery point is launched from the writeable file system and a first and second validation operation are performed by the validation VM. Results of the first validation operation are used to select the second validation operation, and the validation VM is determined to have completed successfully based on the results of the second validation operation. In one embodiment, a repair operation may be performed, based on the first set of results, to repair the operating system of the computing device and/or backup data of the computing device.

Abstract: Techniques are described for modeling variations in correlation to facilitate analytic operations. In one or more embodiments, at least one computing device receives first metric data that tracks a first metric for a first target resource and second metric data that tracks a second metric for a second target resource. In response to receiving the first metric data and the second metric data, the at least one computing device generates a time-series of correlation values that tracks correlation between the first metric and the second metric over time. Based at least in part on the time-series of correlation data, an expected correlation is determined and compared to an observed correlation. If the observed correlation falls outside of a threshold range or otherwise does not satisfy the expected correlation, then an alert and/or other output may be generated.

Abstract: A checking module is coupled to one or more registers to verify data written to the one or more registers. The checking module includes a memory coupled to an arbiter to receive data and an address (corresponding to the data) from the arbiter. The data is written to the one or more registers at the address. Comparator logic is coupled to the memory and to the one or more registers to compare the data written to the one or more registers and the data in the memory. An error flag circuit is coupled to the comparator logic, and in response to a difference between the data in the memory and the data written to the one or more registers, the error flag circuit outputs an error signal.

Abstract: In one example of the technology, via a first independent execution environment of a set of independent execution environments in an integrated circuit, a first watchdog timer is caused to reset on a periodic basis. The set of independent execution environments is configured to have a defense-in-depth hierarchy. The set of independent execution environments includes a first independent execution environment and a second independent execution environment. The first independent execution environment is a most trusted execution environment on the integrated circuit. Via the second independent execution environment: a second watchdog timer is periodically caused to reset on a periodic basis. In response to the second watchdog timer timing out, an interrupt is communicated from the second watchdog timer to the first independent execution environment. In response to the first watchdog timer timing out, at least a portion of the integrated circuit is reset.

Abstract: According to some embodiments, a backup storage system receives a request from a client to access a data segment. The system looks up an in-memory index for a first entry based on a fingerprint of the data segment, such that the in-memory index includes a number of entries, each entry mapping a fingerprint to a storage location of a solid state device (SSD) storing a corresponding data segment. In the event a first entry is found, the system retrieves the data segment from the SSD device based on the first entry. In the event of a read failure while accessing the SSD device, the system determines failed data blocks of the SSD device associated with the failure event and invalidates the failed data blocks of the SSD device such that subsequent access to the failed data blocks are denied without having to access a corresponding SSD device.

Abstract: Methods and systems for dynamic handling of call home data are provided. A system for providing dynamic handling of call home data includes an event detection module that detects one or more events in the operation of one or more components. The system may also include a data request module that requests call home instructions from an upload data manager in response to the detected one or more events. Also, the upload data manager provides call home instructions. The system may further include a call home transmission module that collects call home data based on the call home instructions and provides the collected data to an upload server.

Abstract: A computer-implemented method, according to one embodiment, includes: receiving a write request at a storage system which includes more than one storage device, determining a storage location for data included in the write request, and determining a storage location for parity information corresponding to the data included in the write request. A first copy of the data included in the write request is sent to a first storage device which corresponds to the storage location for the data included in the write request. Moreover, a second copy of the data included in the write request is sent to a second storage device which corresponds to the storage location for the parity information. One or more instructions to compute the parity information via a decentralized communication link with the remaining storage devices are sent to the second storage device. The first storage device is different than the second storage device.

Abstract: A technique for handling uncorrected memory errors (UEs) inside a kernel text section, the kernel text section being stored in a memory that is operably coupled to a CPU executing kernel program instructions. In an embodiment, a UE is detected that affects the kernel text section. The current instruction affected by the UE is identified. The UE-affected instruction is recovered by loading a copy thereof into the memory from a kernel image maintained in persistent storage. The UE-affected instruction is emulated using the copy of the UE-affected instruction. The instruction pointer of the CPU is then incremented to point to a next instruction in the memory that would normally be executed by the UE-affected instruction had there been no UE.

Abstract: An approach is provided in which an information handling system detects a reduced capacity on a PCIe link that interfaces a host system to a PCIe I/O expansion drawer over a first/second physical cable. The information handling system verifies a first/second connection to a first/second connector on the PCIe I/O expansion drawer, receives a first/second set of vital product data over the first/second physical cable, and determines that the first physical cable and the second physical cable are connected to the same PCIe I/O expansion drawer based on analyzing the first/second set of vital product data. The information handling system then suspends operation of one or more components corresponding to the PCIe link and trains the PCIe link to an increased capacity. In turn, the information handling system resumes operation of the one or more components and restores the PCIe link to the increased capacity.

Abstract: Systems, apparatus and methods for intelligent deployment(s) of application objects are provided. The systems, apparatus and methods may include one or more dynamic parameters retrieved from metadata table(s). The parameter(s) may be used to calibrate the deployment(s). The parameter(s) may be associated with previous failed deployment(s). Calibration may be automatic. Calibration may include email sending and/or email previewing components. A testing environment may be used prior to actual deployment.

Abstract: A method for creating a common platform graphical user interface is provided. The interface may enable a user to trigger a data load job from a tool. The tool may monitor file upload events, trigger jobs and identify lists of missing or problematic file names. The tool may run on a single thread, thereby consuming relatively less system resources than a multi-thread program to perform its capabilities. The tool may enable selection of file names using wildcard variables or keyword variables. The tool may validate a list of files received against a master file list for each data load job. The tool may receive user input relating to each data load job. The tool may generate a loop within the single thread to receive information. The tool may analyze the received information and use the received information to predict future metadata associated with future data load jobs.

Abstract: A memory system for a data processing apparatus includes a fault management unit, a memory controller (such as a memory management unit or memory node controller), and one or more storage devices accessible via the memory controller and configured for storing critical data. The fault management unit detects and corrects a fault in the stored critical data, a storage device or the memory controller. A data fault may be corrected using a copy of the data, or an error correction code, for example. A level of failure protection for the critical data, such as a number of copies, an error correction code or a storage location in the one or more storage devices, is determined dependent upon a failure characteristic of the device. A failure characteristic, such as an error rate, may be monitored and updated dynamically.

Abstract: In a system having at least two data storage and processing sites, each capable of alternatively serving as a primary site and a backup or target site, disaster recovery migration is optimized by cognitively analyzing at least one system parameter. Using machine learning, at least one pattern of that system related parameter is predicted, and planned or unplanned migration procedures are performed based on the predicted parameter patterns. The analyzed parameter may be data traffic at the sites, and the predicted data traffic pattern is used to assign primary and backup site status to those sites. The analyzed parameter may be the occurrence of events or transactions at the sites, and the predicted event or transaction patterns may be used to determine times of disaster recovery procedure processing so as to not interrupt a critical event or transaction.