Abstract: A processing device detects a read operation at a memory device that is directed at a word line group from among multiple word line groups of the memory device. The processing device increments a read counter associated with the word line group based on the read operation being directed at the word line group. The processing device determines the read counter exceeds a read-disturb threshold and performs read-disturb handling on the word line group in response to determining the read counter exceeds the read-disturb threshold.

Abstract: A variety of applications can include apparatus and/or methods to preemptively detect defect prone memory blocks in a memory device and handle these memory blocks before they fail and trigger a data loss event. Metrics based on memory operations can be used to facilitate the examination of the memory blocks. One or more metrics associated with a memory operation on a block of memory can be tracked and a Z-score for each metric can be generated. In response to a comparison of a Z-score for a metric to a Z-score threshold for the metric, operations can be performed to control possible retirement of the memory block beginning with the comparison. Additional apparatus, systems, and methods are disclosed.

Abstract: A method and bot assistance system (101) for identifying ideal virtual assistant bots for providing response to user queries is disclosed. The bot assistance system receives user query. The user query is processed to identify context and intent using Natural Language Processing (NLP). The bot assistance system identifies at least one virtual assistant bot for responding to user query based on confidence score of each virtual assistant bot associated with intent of user query, using pretrained model. The identification of at least one virtual assistant bot includes either determining ideal virtual assistant bot based on context of user query, using predefined governance rules. Otherwise, initiating polling between plurality of predefined virtual assistant bots when context of user query is unidentified. The plurality of predefined virtual assistance bots is provided to user associated with user query if each of predefined virtual assistance bots are selected during polling.

Abstract: Systems and methods are disclosed for processing and executing queries in a data intake and query system. The data intake and query system receives a query identifying a set of data to be processed and a manner of processing the set of data. The data intake and query system identifies buckets that are to be searched and search nodes to execute the query. The data intake and query system maps the identified buckets to the search nodes and executes the query using the identified bucket and search nodes.

Abstract: Systems and methods are disclosed for processing and executing queries in a data intake and query system. The data intake and query system receives a query identifying a set of data to be processed and a manner of processing the set of data. The data intake and query system uses a search node catalog to identify search nodes that are available to execute the query and uses a bucket catalog to identify buckets to be searched. The data intake and query system executes the query using the identified bucket and search nodes.

Abstract: Systems and methods are disclosed for monitoring features of a computing device of a distributed computing system using a self-monitoring module. The self-monitoring module can include multiple feature-specific monitoring modules and one or more parent nodes for the feature-specific monitoring modules. A feature-specific monitoring module can identify or detect a fault status change, such as a fault condition or fault resolution, for one or more features. Based on the identified fault conditions or fault resolutions, the feature-specific monitoring module can determine an internal status and communicate an updated status to a parent node.

Abstract: Embodiments of the present disclosure provide solutions for determining an elected search head captain is unqualified for the position, identifying a more qualified search head, and transferring the captain position to the more qualified search head. A method is provided that includes referencing qualification parameters in an elected search head captain, determining whether the newly elected search head captain is qualified for the position based on the parameters, identifying a more qualified search head to be the search head captain if the newly elected search head captain is determined to be unqualified for the position, and transferring the position of captain to the more qualified search head. The qualification parameters may include, for example, a pre-determined static flag set by an administrator of the search environment, and configuration replication status that corresponds to the most recent configuration state of the search head as recorded by the previous search head captain.

Abstract: A method and bot assistance system (101) for identifying ideal virtual assistant bots for providing response to user queries is disclosed. The bot assistance system receives user query. The user query is processed to identify context and intent using Natural Language Processing (NLP). The bot assistance system identifies at least one virtual assistant bot for responding to user query based on confidence score of each virtual assistant bot associated with intent of user query, using pretrained model. The identification of at least one virtual assistant bot includes either determining ideal virtual assistant bot based on context of user query, using predefined governance rules. Otherwise, initiating polling between plurality of predefined virtual assistant bots when context of user query is unidentified. The plurality of predefined virtual assistance bots is provided to user associated with user query if each of predefined virtual assistance bots are selected during polling.

Abstract: A computer implemented system is described for assigning executable jobs to pipeline sets, whereby the jobs may be network based computer jobs. The assigning includes generating a weight for each pipeline set of multiple pipeline sets to obtain multiple weights. Generating a weight includes obtaining duty cycle metrics for pipeline software threads in the pipeline set. The duty cycle metrics include a measure of an amount of time that a corresponding pipeline thread is executing and actively processing data. Generating the weight further includes determining the weight for the pipeline set based at least in part on the duty cycle metrics. The method further includes assigning a job request to a target pipeline set selected from the pipeline sets according to a weighted random algorithm, wherein the weighted random algorithm uses the weights.

Abstract: In response to an operating system crash, a system may recovering by initiating a reboot and performing a dump of a core file for analysis which includes determining a root cause of the operating system crash and determining a patch for the root cause..

Abstract: Resource management includes storing, for multiple workload pools of a data intake and query system, a workload pool hierarchy arranged in multiple workload pool layers. After storing a processing request is assigned a selected subset of workload pools in a second layer of the workload pool hierarchy based on a type of processing request. The processing request is then assigned to an individual workload pool in the selected subset to obtain a selected workload pool. Execution of the processing request is initiated on the selected workload pool.

Abstract: Dynamic reassignment of search processes into workload pools includes receiving a search query to search at least one data store, assigning the search query to a first workload pool, and executing the search query using a first hardware resource in the first workload pool, the first hardware resource corresponding to a first portion of a hardware device. Dynamic reassignment further includes receiving, while executing the search query, an update command to move the search query to a second workload pool, moving, while executing the search query, the search query to the second workload pool; and continuing execution of the search query using a second hardware resource in the second workload pool. The second hardware resource corresponds to a second portion of the hardware device.

Abstract: A system described herein may generate and/or modify a model that correlates attributes of orders, users, and/or User Equipment (“UEs”) to order modification parameters. The order modification parameters may indicate whether to modify the position in an order queue of an order for which a modification has been received. One set of order modification parameters may indicate that a modified order should be placed in the same position in the order queue as an original order. Another set of order modification parameters may indicate that a modified order should be placed at the end of the order queue, and/or at some position between the end of the order queue and the position of the original order. UEs checking the status of the order may receive different options to modify or cancel the order, based on order modification parameters identified with respect to the order or the UE.

Abstract: Systems and methods are disclosed for processing and executing queries in a data intake and query system. The data intake and query system receives a query identifying a set of data to be processed and a manner of processing the set of data. The data intake and query system identifies buckets that are to be searched and stores a copy of buckets in memory associated with one or more search nodes. A search node performs a search on buckets residing in its memory.

Abstract: Aspects of the disclosure relate to a real-time dynamic container optimization computing platform. The real-time dynamic container optimization computing platform may receive a request to create a first processing block and first data associated with the first processing block. The real-time dynamic container optimization computing platform may utilize a plurality of models to select a first computing device for the first processing block. The real-time dynamic container optimization computing platform may generate and deploy a container to the first computing device. The real-time dynamic container optimization computing platform may monitor execution of the container on the first computing device. The real-time dynamic container optimization computing platform may migrate the container to the second computing device if an issue with execution of the container on the first computing device is detected.

Abstract: Systems and methods are disclosed for processing and executing queries in a data intake and query system. The data intake and query system receives a query identifying a set of data to be processed and a manner of processing the set of data. The data intake and query system identifies buckets that are to be searched. The data intake and query system performs a hash on bucket identifiers of the identified buckets to identify search nodes to search the buckets.

Abstract: A computer implemented system is described for assigning executable jobs to pipeline sets, whereby the jobs may be network based computer jobs. The assigning includes generating a weight for each pipeline set of multiple pipeline sets to obtain multiple weights. Generating a weight includes obtaining duty cycle metrics for pipeline software threads in the pipeline set. The duty cycle metrics include a measure of an amount of time that a corresponding pipeline thread is executing and actively processing data. Generating the weight further includes determining the weight for the pipeline set based at least in part on the duty cycle metrics. The method further includes assigning a job request to a target pipeline set selected from the pipeline sets according to a weighted random algorithm, wherein the weighted random algorithm uses the weights.

Abstract: Disclosed herein is a compound of formula I: where m, n and R1 are as defined herein. Also disclosed herein are uses of the compound.

Abstract: Systems and methods are disclosed for processing and executing queries against one or more dataset sources, where the queries identify a set of data to be processed and a manner of processing the set of data. To query the dataset sources, a query coordinator generates a query processing scheme that includes a dynamic allocation of multiple layers of partitions. The query is then executed based on the query processing scheme.

Abstract: Systems and methods are disclosed for monitoring features of a computing device of a distributed computing system using a self-monitoring module. The self-monitoring module can include multiple feature-specific monitoring modules and one or more parent nodes for the feature-specific monitoring modules. A feature-specific monitoring module can identify or detect a fault status change, such as a fault condition or fault resolution, for one or more features. Based on the identified fault conditions or fault resolutions, the feature-specific monitoring module can determine an internal status and communicate an updated status to a parent node.