Abstract: A specification of a client-side user interface behavior for a view of a computer application is received from a representative of an organization. The received specification is stored. A request for content of the view is received via a network from the computer application associated with a user that belongs to the organization. The received specification is identified as being associated with the requested content of the view. The requested content of the view and an identifier of the identified specification of the client-side user interface behavior are provided via the network. The computer application utilizes the received identifier of the identified specification of the client-side user interface behavior to modify the view of the computer application.

Abstract: A method of managing alerts in a client instance associated with a configuration management database (CMDB) platform is disclosed. The method includes: receiving a request identifying a particular CI and a particular alert; identifying related CIs from a plurality of CIs associated with the client instance based on the particular CI and the particular alert; identifying alerts, incidents (INTs), changes (CHGs), and problems (PRBs) of the client instance that are associated with either the particular CI or the related CIs; determining frequency data for the alerts, INTs, CHGs, and PRBs associated with the particular CIs and frequency data for the alerts, INTs, CHGs, and PRBs associated with the related CIs; and sending a response that includes the frequency data for the alerts, INTs, CHGs, and PRBs associated with the particular CIs to be presented alongside the frequency data for the alerts, INTs, CHGs, PRBs associated with the related CIs.

Abstract: A embodiment may involve receiving a contact tracing request for a first user identifier that corresponds to a first portable device identifier of a first portable device. The second example embodiment may also involve requesting and receiving, from a first computing device associated with the first user identifier, device adjacency data, wherein the device adjacency data contains a plurality of contact entries, wherein one of the contact entries identifies a second portable device identifier of a second portable device that was wirelessly detected by the first portable device and a timestamp of when the wireless detection of the second portable device occurred. The second example embodiment may involve determining, from the mappings, a second user identifier that corresponds to the second portable device identifier. The second example embodiment may further involve transmitting, to a second computing device associated with the second user identifier, a contact tracing notification.

Abstract: Systems and methods are disclosed for computer network threat assessment. For example, methods may include receiving from client networks respective threat data and storing the respective threat data in a security event database; maintaining affiliations for groups of the client networks; detecting correlation between a network threat and one of the groups; identifying an indicator associated with the network threat, and, dependent on the affiliation for the group, identifying a client network and generating a message, which conveys an alert to the client network, comprising the indicator; responsive to the message, receiving, from the client network, a report of detected correlation between the indicator and security event data maintained by the client network; and updating the security event database responsive to the report of detected correlation.

Abstract: A system may include memory containing: (i) a master data set representable in columns and rows, and (ii) a query expression. The system may include a software application configured to apply a machine learning (ML) pipeline to an input data set. The system may include a computing device configured to: obtain the master data set and the query expression; apply the query expression to the master data set to generate a test data set, where applying the query expression comprises, based on content of the query expression, generating the test data set to have one or more columns or one or more rows fewer than the master data set; apply the ML pipeline to the test data set, where applying the ML pipeline results in either generation of a test ML model from the test data set or indication of an error in the test data set; and delete the test data set from the memory.

Abstract: A computing system includes a processor and memory. The memory includes instruction code that causes the processor to generate first and second parser instances and associate the first parser and the second parser with respective first and second search queries. The processor controls the first parser to repeatedly obtain data from the data stream in blocks until the first parser finishes identifying elements in the data stream associated with its search path. The processor controls the second parser to repeatedly obtain blocks from the first parser when the blocks obtained by the first parser have not been searched by the second parser, and controls the second parser to obtain blocks from the data stream when the blocks obtained by the first parser have been searched by the second parser and the first parser has finished searching.

Abstract: A system includes a processor configured to create a rule repository instance. The rule repository instance specifies a plurality of different procedures that facilitate specifying a sequence of transformer rules by cascading each of the procedures together using a dot notation format. The processor configures the rule repository instance with a plurality of transformer rules using the dot notation format. The processor receives data from a file arranged according to a first structured data format. The processor executes the sequence of transformer rules to convert data elements in the file to a second structured data format. The processor then provides for display or storage the data as converted into the second structured data format by the sequence of transformer rules.

Abstract: An example embodiment performed by a scoped software application executable on a computing device of a computational instance of a remote network management platform may involve: requesting and receiving, from an application database associated with a third-party software application, alert rules that trigger alerts when associated events occur in a managed network; receiving data representing selection of a set of the alert rules and, based on the data, requesting and receiving, from the application database, a set of past alerts that have been triggered by the set of the alert rules; using mapping data to map fields of the set of the past alerts to fields of a sample security incident record; displaying a preview region including the sample security incident record; using the mapping data to create security incident records that map to the set of the past alerts; and writing, to a security incident database, the security incident records.

Abstract: A determination is made that the performance of a user database query to a database does not meet a first performance threshold. In response to the user database query not meeting the first performance threshold, one or more test queries of the database are performed. A second determination is made whether a performance of the one or more test queries meets a second performance threshold. In response to the one or more test queries meeting the second performance threshold, an analysis is performed to determine whether to resize a database buffer cache of the database.

Abstract: Systems and methods for processing computing jobs of a managed network are disclosed. Each of one or more worker nodes may implement a scheduler thread and a pool of worker threads. Upon waking up from a sleep state, the scheduler thread may determine a current number of jobs in an in-memory job queue that are waiting for processing by a worker thread, and may compute a job-completion rate of jobs processed by threads of the pool. Based on the job-completion rate, the scheduler thread may perform one or more of retrieving more jobs from a centralized database job queue and adding them to the in-memory job queue; removing one or more jobs from the in-memory job queue and returning them to the database job queue; leaving the in-memory job queue unchanged; or adjusting the duration of the sleep-interval timer. The scheduler thread may then return to a sleep state.

Abstract: A server receives a first hypertext transfer protocol (HTTP) from a client device that requests first and second items of content associated with a webpage and applies a defer directive to the second item. The server retrieves, from a database, via a single worker thread, first data associated with the first item and transmits a first message comprising the first data associated with the first item. The server retrieves, from the database, via the worker thread, second data associated with the deferred item and transmits a second message comprising the second data associated with the second item.

Abstract: An embodiment may involve server devices arranged into pods, each server device hosting computational instances, and a central computational instance configured to: (i) obtain per-pod lists of the instances hosted by the pods; (ii) determine a maximum number of the instances to arrange into batches; (iii) determine a group size for groups of the instances that are to be placed into the batches; (iv) execute a first phase that involves removing per-pod groups from the per-pod lists and adding them to the batches, until less of the instances than the group size remains in each of the per-pod lists; (v) execute a second phase that involves removing one of the instances from the per-pod lists and adding it to the batches, until none of the instances remains in any of the per-pod lists; and (vi) schedule one or more of the automations to take place in the data center.

Abstract: The present disclosure relates to importing license data from a license metric tool server (LMTS) into a configuration management database (CMDB). License records are requested and received from the LMTS and are subsequently imported as into the CMDB of a client instance as configuration item (CI) data. In certain circumstances, a license record may have an identifier field (ID) value that does not correspond to a CI of the CMDB, resulting in the license record failing to import. The disclosed process involves flagging license records that fail import, and then clustering the flagged license records into suitable groups. The flagged license records are then re-pulled from the LMTS in groups, rather than using individual requests for each flagged license record. By effectively clustering of the flagged license records into groups, the disclosed importation process enables a reduction in processing, memory, and/or communication overhead, improving operation of the client instance.

Abstract: A regular expression that is able to be used to identify an item as belonging to a specific group among a plurality of different groups is determined. The regular expression is tested against a sampling of items known to belong to the specific group to determine a true positive metric. The regular expression is tested against a sampling of items known to belong to other groups among the plurality of different groups outside the specific group to determine a false positive metric. An accuracy metric of the determined regular expression is calculated based at least in part on the true positive metric and the false positive metric. The accuracy metric is provided for use in evaluating the regular expression.

Abstract: Systems and methods for using instrumentation for maintenance of a user-configured program in a cloud computing environment are herein disclosed as comprising, in an implementation, intercepting operation data pertaining to the user-configured program, including a start time, an execution time interval, an operation, and an origin of the operation, canonicalizing the intercepted operation data by stripping operation-specific variable data from the operation data, aggregating the canonicalized operation data based on the start time, the canonicalized operation data, and the origin of the operation, and storing the aggregated operation data within a time series database in the execution time interval based on the start time.

Abstract: An agent automation system includes a memory configured to store a natural language understanding (NLU) framework and a processor configured to execute instructions of the NLU framework to cause the agent automation system to perform actions. These actions comprise: generating an annotated utterance tree of an utterance using a combination of rules-based and machine-learning (ML)-based components, wherein a structure of the annotated utterance tree represents a syntactic structure of the utterance, and wherein nodes of the annotated utterance tree include word vectors that represent semantic meanings of words of the utterance; and using the annotated utterance tree as a basis for intent/entity extraction of the utterance.

Abstract: The present approach relates to improving query performance in a database context. Examples of query improvement are described in the context of certain query patterns, one or more of which may be observed in a given query. When a given query pattern is observed, changes may be made to the query at the application or database level to improve performance of the respective query. Query improvements may be performed in a manner transparent to the user.

Abstract: A system and method for comparative performance monitoring of software release versions is disclosed. A remote network management platform may include a computational instance for managing a network. Transactions between a server of the computational instance and a client device in the managed network may be logged to a database. Transactions may be carried out by a release version of a set of program code units executing on the server. A software application executing on a computing device may retrieve and analyze a first set of transactions carried out by a first release version of the set of program code units to determine a first set of performance metrics, and do the same for a second set of transactions carried out by a second release version of the set of program code units to determine a second set of performance metrics.

Abstract: The disclosed subject matter relates to a service application that supports a client device to access a platform via a client instance. The service application enables the user to perform an operation related to management of a virtual resource. In some embodiments, the service application invokes a chat interface to place the client device in communication with a virtual agent. Via the chat interface, the service application prompts the user to select a topic, an operation, and a virtual resource to indicate a desired operation to be performed. When the service application receives the selections made by the user via the chat interface, the service application, such as the virtual agent, may access the platform to perform the desired operation.

Abstract: An embodiment may involve, based on a pre-defined trigger associated with a particular application, reading error data from a resource that is used by the particular application, wherein persistent storage contains definitions of a plurality of error scenarios, a plurality of fix scripts, and associations between each of the plurality of error scenarios and one or more of the plurality of fix scripts; applying one or more rules to the error data, wherein the rules involve pattern matching or parsing; based on applying the one or more rules, determining a particular error scenario represented in the error data, wherein the particular error scenario is one of the plurality of error scenarios; determining, based on the associations, a particular fix script associated with the particular error scenario, wherein the particular fix script is one of the plurality of fix scripts; and causing execution of the particular fix script.