The present disclosure is related to Virtual Desktop Infrastructure (VDI) that discloses a method and system for performing dynamic patch management in VDI platform. A patch managing system retrieves operational data and vulnerability remediation data related to IT services and infrastructures of the VDI platform from first and second data sources. Thereafter, the patch managing system detects gap in patching level based on operational data, vulnerability remediation data and corresponding industrial standard, and rolls out patches based on detected gap in patching level. Further, a patch prediction score that facilitates in identifying a probability of rolling back the patches rolled out for patching IT services and infrastructures of VDI platform is determined based on prediction parameters. A plan is generated based on the patch prediction score and executed to optimally patch the patches to IT services and infrastructures of the VDI platform, based on patching rules.

A memory system includes dynamic random-access memory (DRAM) components that include interconnected and redundant component data interfaces. The redundant interfaces facilitate memory interconnect topologies that accommodate considerably more DRAM components per memory channel than do traditional memory systems, and thus offer considerably more memory capacity per channel, without concomitant reductions in signaling speeds. The memory components can be configured to route data around defective data connections to maintain full capacity and continue to support memory transactions.

A process includes determining, by an operating system agent of a computer system, a first profile that is associated with an input/output (I/O) peripheral of the computer system. The first profile is associated with an error register of the I/O peripheral, and the first profile represents a configuration of the computer system that is associated with the I/O peripheral. The process includes, responsive to a notification of an error being associated with the I/O peripheral, determining, by the operating system agent, a second profile that is associated with the I/O peripheral. The second profile is associated with the error register. Moreover, responsive to the notification of the error, the process includes comparing, by a baseboard management controller of the computer system, the second profile to the first profile. Based on the comparison, the process includes determining, by the baseboard management controller, whether the error is attributable to a driver for the I/O peripheral.

Several embodiments of systems incorporating memory components are disclosed herein. In one embodiment, a memory system can include a memory component and a processing device configured to access quality metrics corresponding to memory regions of the memory component. In some embodiments, the processing device can compare the quality metrics to one or more memory management thresholds. In some embodiments, when the quality metrics meet and/or exceed a first threshold, a refresh operation can be scheduled and/or performed on a corresponding memory region. In these and other embodiments, when the quality metrics meet and/or exceed a second threshold, the memory region is retired and removed from an active pool of memory regions.

Apparatus and methods an artificial intelligence method of reducing failure in an informational flow of a data stream controlled by an Extract Transform Load process using a machine learning (“ML”) model training system are provided. The method may include deploying a software sensor that periodically captures data points for an extract job executed during an extract phase of the process. The method may also include building a behavior profile concurrently with the receipt of each of the data points. The method may further include comparing the behavior profile to behavior profiles stored in an Adverse Behavior Model database and behavior profiles stored in a Normal Behavior Model database. When the behavior profile is determined to have a threshold number of match points matching the behavior profile to behavior profiles in the Adverse Behavior Model database, the method may include increasing a target database storage capacity.

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.

Reliability, availability, and serviceability (RAS)-based memory domains can enable applications to store data in memory domains having different degrees of reliability to reduce downtime and data corruption due to memory errors. In one example, memory resources are classified into different RAS-based memory domains based on their expected likelihood of encountering errors. The mapping of memory resources into RAS-based memory domains can be dynamically managed and updated when information indicative of reliability (such as the occurrence of errors or other information) suggests that a memory resource is becoming less reliable. The RAS-based memory domains can be exposed to applications to enable applications to allocate memory in high reliability memory for critical data.

Methods, systems, and devices for host-configurable error protection are described. A host system may receive an indication of a set of logical addresses supported by the memory system and available for use by the host system. The host system may divide the set of logical addresses into subsets of logical addresses. Each subset of logical addresses may be associated with a different type of data. The host system may determine an error protection configuration for a subset of logical addresses based at least in part on the type of data associated with the subset of logical addresses. The host system may then send to the memory system an indication of the subset of logical addresses and an indication of the error protection configuration for the subset of logical addresses.

A scheduling scheme configuration method includes performing state verification on a plurality of operation dimensions involved in generating a scheduling scheme, and, in response to one or more of the operation dimensions being abnormal, removing the one or more abnormal operation dimensions to generate a new scheduling scheme.

a computing system that receives and stores configuration information for the application in a data store. The configuration information comprises (1) identifiers for a plurality of cells of the application that include at least a primary cell and a secondary cell, (2) a defined state for each of the plurality of cells, (3) one or more dependencies for the application, and (4) a failover workflow defining actions to take in a failover event. The computing system receives an indication, from a customer, of a change in state of the primary cell or a request to initiate the failover event. The computing system updates, in the data store, the states for corresponding cells of the plurality of cells based on the failover workflow and updates, in the data store, the one or more dependencies for the application based on the failover workflow.