Abstract: Techniques discussed herein relate to managing aspects of provisioning cloud-computing edge devices. In some embodiments, a user request specifying one or more resources to be provisioned at a cloud-computing edge device may be received by a cloud-computing device operated by a cloud-computing provider. An ephemeral credential may be generated for the edge device and used to determine whether access control policies exist that enable the edge device to access the resource(s). If the resource(s) are accessible, a manifest may be generated in accordance with the user request. The manifest may specify a configuration for the cloud-computing edge device and includes information related to the resource. Operations may be subsequently executed to provision the cloud-computing edge device in accordance with the manifest. However, if the resource(s) are not accessible, the user request may be denied.

Abstract: Techniques for modifying queries in a set of nested queries are disclosed. A graphical user interface displays a query detail region alongside a nested query display region. The graphical user interface includes functionality to provide for modification of queries in the nested set of queries. Based on a selection by a user, a query modification tool promotes a query attribute from a child query to one or more parent queries. Based on another selection by a user associated with one query in the set of nested queries, the system deletes an attribute from each query in the set of nested queries. Responsive to a selection to create multiple conditions for a query rule, the system modifies the functionality of the user interface to enable entry of multiple condition characteristics. Based on a further selection, the system creates the multiple conditions for the query rule.

Abstract: Techniques for identity management, and more particularly, to techniques for dynamically assigning membership to users in the system based on dynamic rules. In one aspect a computer-implement method is provided that breaks down the processing from a single large thread or operation into multiple minutest level threads or operations and makes use of event driven architecture used in distributed environments such as a cloud environment, to achieve a scalable model and can work seamlessly for multi-tenant applications. Every sub problem is assigned to a dedicated set of subscribers on a messaging service for processing.

Abstract: Disclosed is a system, method, and computer program product for implementing a log analytics method and system that can configure, collect, and analyze log records in an efficient manner. Machine learning-based classification can be performed to classify logs. This approach is used to group logs automatically using a machine learning infrastructure.

Abstract: A continuous query identified by an archived relation of an application may be received. A physical query plan may be generated for the continuous query and/or a child operator plan may be identified. A buffer operator may be inserted between the child operator and its parent operator and/or the event information from the child operator may be stored in the buffer operator. A query operator may be identified in the physical query plan. It may be determined that the query operator identified in the physical query plan is a same type as a second query operator in a second continuous query concurrently executing. Further, a combined query plan may be generated based at least in part on the query operator identified in the physical query plan being the same type as the second query operator in the second continuous query.

Abstract: Techniques discussed herein relate to implementing a distributed computing cluster (the “cluster”) including a plurality of edge devices (e.g., devices individually configured to selectively execute within an isolated computing environment). One edge device may be configured to operate as a head node of the cluster at a given time. A request for virtual resources of the cluster may be received from a user device and directed to the first edge device of the cluster. The first edge device may determine it is not operating as a head node of the cluster. The first edge device may determine that a second edge device of the cluster is operating as the head node. In response, the first edge device may forward the request to the second edge device, wherein forwarding the request to the second edge device causes the second request to be processed by the cluster.

Abstract: Client data corresponding to a single client can be stored. A decision to proceed with a defragmentation of two or more particular core groups can be determined. A destination core group to receive client data can be identified. At least one additional core group can be initiated to manage interim data write requests from the single client. Each of the two or more particular core groups can be closed to data write requests. A defragmentation of the two or more particular core groups can be performed by merging into the destination core group. The destination core group can be availed to data read and delete requests. The two or more fragmented core groups can be reallocated for other uses. The additional core groups continue to receive read and write requests. The destination core groups further can be merged and defragmented further.

Abstract: Methods, systems, and computer readable media for validating subscriber entities against spoofing attacks in a communications network are disclosed. One method includes receiving, by a proxy element, a subscriber authentication request message that is sent from an access and mobility management function (AMF) and is directed to a unified data management (UDM) function in a home network, creating, by the proxy element, a record entry including a subscriber identifier and a public land mobile network (PLMN) identifier contained in the subscriber authentication request message, wherein the record entry is stored in an authentication registry database prior to forwarding the subscriber authentication request message to the UDM function.

Abstract: A manager file system (MFS), implemented using an OS process, exposes a path in the native file system as the root of its file system (e.g., mount point). The MFS informs the OS kernel that any file system operation whose path contains the mount point as its prefix, should be handed over to the process by invoking an appropriate interface method that the process implements as part of its file system implementation. The MFS manages one or more applications and leverages the authentication mechanism of the OS to provide fined-grained access control of MFS managed applications.

Abstract: A data object has a lock and a condition indicator associated with it. Based at least partly on detecting a first setting of the condition indicator, a reader stores an indication that the reader has obtained read access to the data object in an element of a readers structure and reads the data object without acquiring the lock. A writer detects the first setting and replaces it with a second setting, indicating that the lock is to be acquired by readers before reading the data object. Prior to performing a write on the data object, the writer verifies that one or more elements of the readers structure have been cleared.

Abstract: Techniques for noise data augmentation for training chatbot systems in natural language processing. In one particular aspect, a method is provided that includes receiving a training set of utterances for training an intent classifier to identify one or more intents for one or more utterances; augmenting the training set of utterances with noise text to generate an augmented training set of utterances; and training the intent classifier using the augmented training set of utterances. The augmenting includes: obtaining the noise text from a list of words, a text corpus, a publication, a dictionary, or any combination thereof irrelevant of original text within the utterances of the training set of utterances, and incorporating the noise text within the utterances relative to the original text in the utterances of the training set of utterances at a predefined augmentation ratio to generate augmented utterances.

Abstract: A computer-implemented method includes: accessing a plurality of datasets, where each dataset of the plurality of datasets includes training examples; selecting datasets that include the training examples in a source language and a target language; and sampling, based on a sampling weight that is determined for each of the selected datasets, the training examples from the selected datasets to generate the training batches; training an ML model for performing at least a first task using the training examples of the training batches, by interleavingly inputting the training batches to the ML model; and outputting the trained ML model configured to perform the at least the first task on input utterances provided in at least one among the source language and the target language. The sampling weight is determined for each of the selected datasets based on one or more attributes common to the training examples of the selected dataset.

Abstract: The present disclosure is related to techniques for converting a natural language utterance to a logical form query and deriving a natural language interpretation of the logical form query. The techniques include accessing a Meaning Resource Language (MRL) query and converting the MRL query into a MRL structure including logical form statements. The converting includes extracting operations and associated attributes from the MRL query and generating the logical form statements from the operations and associated attributes. The techniques further include translating each of the logical form statements into a natural language expression based on a grammar data structure that includes a set of rules for translating logical form statements into corresponding natural language expressions, combining the natural language expressions into a single natural language expression, and providing the single natural language expression as an interpretation of the natural language utterance.

Abstract: Approaches of reassigning a home region from a first data center to a second data center as requested by a customer are described herein. The home region is able to implement write operations to a domain, whereas other data centers cannot implement write operations to the domain. The customer can request the home region being reassigned to another data center such that the customer can utilize the other data center to implement write operations to the domain.

Abstract: Techniques are described for a hierarchical caching mechanism enabling efficient cross-region replications. In some embodiments, replication-related information (e.g., key-value pairs) is stored in a particular layout in a binary tree (B-tree) of a file system for replication processing. A hierarchy of caches storing a first type of information (e.g., crypto keys associated with iNodes) may be arranged to match the particular layout in the B-tree to enable efficient parallel processing of a second type of information (e.g., files, file data, or symbolic links), where the replication-related information in the B-tree is partitioned into multiple key ranges for parallel processing. In some embodiments, the caches in different hierarchies may be shared by different parallel-processing key ranges and replication jobs in a file system.

Abstract: Techniques for perspective-preserving seamless application switching are disclosed. A system may display a first interface using a first application. The first interface includes interface elements representing a plurality of objects. The system may detect a zoom-in command, received by the first application, requesting a particular zoom level for a first interface element, corresponding to a first object in the first plurality of objects. The system may determine that the requested zoom level exceeds a threshold. Responsive to determining that the requested zoom level exceeds the threshold, the system may display, using a second application, a second interface corresponding to the first object. The second interface may include one or more of: (a) characteristics associated with the first object that were not displayed by the first application, or (b) user input elements for executing operations associated with the first object that were not displayed by the first application.

Abstract: The present invention relates to machine learning (ML) explainability (MLX). Herein are local explanation techniques for black box ML models based on coalitions of features in a dataset. In an embodiment, a computer receives a request to generate a local explanation of which coalitions of features caused an anomaly detector to detect an anomaly. During unsupervised generation of a new coalition, a first feature is randomly selected from features in a dataset. Which additional features in the dataset can join the coalition, because they have mutual information with the first feature that exceeds a threshold, is detected. For each feature that is not in the coalition, values of the feature are permuted in imperfect copies of original tuples in the dataset. An average anomaly score of the imperfect copies is measured. Based on the average anomaly score of the imperfect copies, a local explanation is generated that references (e.g. defines) the coalition.

Abstract: In accordance with an embodiment, described herein are systems and methods for use with an analytic applications environment, for determination of recommendations and alerts in such environments. A data pipeline or process can operate in accordance with an analytic applications schema adapted to address particular analytics use cases or best practices, to receive data from a customer's (tenant's) enterprise software application or data environment, for loading into a data warehouse instance. When provided as part of a software-as-a-service (SaaS) or cloud environment, the data sourced from a plurality of organizations can be aggregated, to leverage information gleaned from the collective or shared data. The system can be used to generate semantic alerts, including obtaining permission from; and analyzing the collective data of; the plurality of organizations, to determine operational advantages indicated by the data, and providing alerts associated with those operational advantages.

Abstract: A distributed computing system is described that leverages a nearline storage layer to minimize the downtime required for bootstrapping a new computing cluster in the distributed computing system. The system executes a computing cluster comprising a set of computing nodes and determines a set of one or more data segments to be written to a nearline storage system. The system writes the data segments to the nearline storage system. In certain examples, the system receives a request to create a second computing cluster and responsive to the request, bootstraps the second computing cluster using the set of data segments stored on the nearline storage system. The system additionally leverages the nearline storage layer to accelerate query processing by the computing nodes of a computing cluster.

Abstract: In accordance with an embodiment, described herein is a system and method for loading and transforming data to a cloud database, using a hybrid set-based extract, load, transform approach. During the loading and transforming of large amounts of data, from one or more data sources, a data synchronization application sends small batches of data, in parallel streams, to the database, which operates as a transformation engine to load the data. Each stream can be associated with a separate staging table in the database. For each staging table, the subset of data therein is transformed and loaded, before the next subset is processed. A transform and merge process operating at the database can then be used to transform and merge the data, from each of the staging tables, to the target table.