A method for managing specialized hardware resources includes obtaining, by a disaster recovery (DR) virtual resource agent, a request for a DR environment for a set of virtual resources in a primary site, in response to the request: monitoring the primary site to obtain virtual workload information corresponding to the set of virtual resources, performing a workload analysis on the set of virtual resources in the primary site using the virtual workload information to obtain a virtual resource mapping of each virtual resource in the primary site to a tiered component in the DR environment, and initiating a DR environment allocation of DR virtual resources based on the virtual resource mapping.

One example method includes performing a machine learning process that involves performing an assessment of a state of a computing system, and the assessment includes analyzing information generated by an IoT edge sensor in response to a sensed physical condition in the computing system, and identifying an entity in the computing system potentially impacted by an event associated with the physical condition. The example method further includes identifying a preemptive recovery action and associating the preemptive recovery action with an entity, and the preemptive recovery action, when performed, reduces or eliminates an impact of the event on the entity, determining a cost associated with implementation of the preemptive recovery action, evaluating the cost associated with the preemptive recovery actions and identifying the preemptive recovery action with the lowest associated cost, implementing the preemptive recovery action with the lowest associated cost, and repeating part of the machine learning process.

An indication is received from a storage device that an attempt to read a portion of data from a block of the storage device has failed. A command is transmitted to the storage device to perform a scan on data stored at the block comprising the portion of data to acquire failure information associated with a plurality of subsets of the data stored at the block. The failure information associated with the plurality of subsets of the data stored at the block is received from the storage device.

An electronic evaluation device and method thereof for optimizing an operation of computer-controlled metric appliances in a network. The method includes determining whether a fault associated with computer-controlled metric appliance is valid based on a feedback received in real time from a validation entity and updating pre-defined programmable instructions assigned to the computer-controlled metric appliance in response to determining that the fault is invalid. The predefined programmable instructions are used to determine whether the computer-executable metric is achieved or not. The method includes applying a machine learning model on the plurality of parameters and the computer-executable goal to determine a computer-executable task list to be assigned to the computer-controlled metric appliance in order to achieve the computer-executable goal.

An electronic evaluation device and method thereof for optimizing an operation of computer-controlled metric appliances in a network. The method includes determining whether a fault associated with computer-controlled metric appliance is valid based on a feedback received in real time from a validation entity and updating pre-defined programmable instructions assigned to the computer-controlled metric appliance in response to determining that the fault is invalid. The predefined programmable instructions are used to determine whether the computer-executable metric is achieved or not. The method includes applying a machine learning model on the plurality of parameters and the computer-executable goal to determine a computer-executable task list to be assigned to the computer-controlled metric appliance in order to achieve the computer-executable goal.

A memory system and a memory controller are disclosed. By determining whether an error has occurred in target data stored in a predetermined target memory area of the memory device and determining, in response to whether an error has occurred in the target data, the magnitude of the supplied power based on a first operation parameter selected among predetermined candidate operation parameters in connection with the magnitude of the supplied power, the memory controller may stably drive a firmware, and may handle an operation error of the firmware due to a change in external environment.

Aspects described herein may relate to a transaction exchange platform using a streaming data platform (SDP) and microservices to process transactions according to review and approval workflows. The transaction exchange platform may receive transactions from origination sources, which may be added to the SDP as transaction objects. Microservices on the transaction exchange platform may interact with the transaction objects based on configured workflows associated with the transactions. Processing on the transaction exchange platform may facilitate clearing and settlement of transactions. Some aspects may provide for dynamic and flexible reconfiguration of workflows and/or microservices. Other aspects may provide for data snapshots and workflow tracking, allowing for monitoring, quality control, and auditability of transactions on the transaction exchange platform.

A method for execution by a storage network begins by issuing a decode threshold number of read requests for a set of encoded data slices to a plurality of storage units of a set of storage units and continues by determining whether less than a decode threshold number of read requests has been received in a time window. The method continues by identifying one or more encoded data slices encoded data slices associated with read requests of the decode threshold number of read requests that have not been received and for an encoded data slice of the one or more encoded data slices, issuing a priority read request to a storage unit storing a copy of the encoded data slice. The method then continues by receiving a response from the storage unit storing the copy of the encoded data, where the storage unit storing the copy of the encoded data slice is adapted to delay one or more maintenance tasks in response to the priority read request.

A computer system is provided. The computer system includes a memory, a network interface, and at least one processor configured to monitor a user interface comprising a plurality of user interface elements; detect at least one changed element within the plurality of user interface elements; classify, in response to detecting the at least one changed element, the at least one changed element as either indicating or not indicating an error; generate, in response to classifying the at least one changed element as indicating an error, an error signature that identifies the at least one changed element; identify, using the error signature, a remediation for the error; and provide the remediation in association with the at least one changed element.

A computer system is provided. The computer system includes a memory and at least one processor coupled to the memory. The at least one processor is configured to scan session data representative of operation of a user interface comprising a plurality of user interface elements; detect, at a point in the session data, at least one changed element within the plurality of user interface elements; classify, in response to detecting the at least one changed element, the at least one changed element as either indicating or not indicating an error; store an association between the error and the point in the session data; and provide access to the point in the session data via the association.