352 results about "Event (computing)" patented technology

Disclosed are systems and methods that ingest substantial volumes of data from a variety of sources associated with a computing system network to create integrated, intuitive, efficient, and coherent adaptive workspace display interfaces. The ingestion includes event data generated by event source software applications running on end user computing devices as well as call and end user attribute data that is used to determine state, presence, and performance data for the end user computing devices that is formatted for display on the adaptive workspace interfaces and used during performance monitoring and collaboration between system end users. The adaptive workspace interfaces provide functions that facilitate real time collaboration between end users that enhances shared experiences between system end users and customers.

Embodiments are directed to security analysis agents. Events associated with a computing environment may be provided. Prompt fragments may be determined based on the events. A prompt may be generated for a large language model (LLM) based on a prompt template and the prompt fragments such that the prompt fragments may be included in the prompt and provided to the LLM. Actions for evaluating the events may be determined based on the LLM response. These actions may be executed to evaluate the events. Portions of the response that correspond to the prompt fragments may be determined. A performance score may be determined for each prompt fragment based on its corresponding portion of the response such that the prompt may be modified to exclude a portion of the prompt fragments that have a performance score less than a threshold value.

Embodiments are directed to security analysis agents. Events associated with a computing environment may be provided. Prompt fragments may be determined based on the events. A prompt may be generated for a large language model (ELM) based on a prompt template and the prompt fragments such that the prompt fragments may be included in the prompt and provided to the ELM. Actions for evaluating the events may be determined based on the ELM response. These actions may be executed to evaluate the events. Portions of the response that correspond to the prompt fragments may be determined. A performance score may be determined for each prompt fragment based on its corresponding portion of the response such that the prompt may be modified to exclude a portion of the prompt fragments that have a performance score less than a threshold value.

A system and method for reducing data record processing in incident report generation is provided. The method includes: accessing a plurality of event records, each event record generated based on an event in a computing environment; parsing each event record based on a predetermined data field; extracting from each predetermined data field a data value; correlating a group of event records of the plurality of event records based on at least an extracted data value; generating an incident data record based on the extracted data values of the correlated group of event records; generating a prompt based on the incident data record; and generating an incident report by configuring a large language model (LLM) to execute the generated prompt.

The invention discloses a server-free workflow engine implementation method based on event orchestration, which relates to the technical field of server-free computing, and comprises the following steps: continuously monitoring a predefined event source; when an event is received, matching is performed according to a preset event triggering rule; if the event matching is successful, starting a corresponding predefined workflow according to an event triggering rule; mapping each task in the workflow to a server-free function according to the workflow definition, and triggering the server-free function to execute according to an event; recording the execution state of the workflow, updating the state, and performing flow control and error processing according to the execution state information. According to the method, the real-time response capability is improved, the execution efficiency is enhanced, and the reliability of process control and error processing is ensured, so that the requirements of an automatic complex business process are better met.

Techniques for using machine learning (ML) model(s) to generate a textual summary of a stream of events at least in part by receiving information corresponding to the stream of events corresponding to interactions between a user and application program(s) executing on a computing device, the information comprising, for each of multiple events in the stream of events associated with a process, metadata associated with the event, wherein metadata for a particular event specifies values for attributes of the particular event; processing, using at least one ML model, the metadata associated with the multiple events to generate multiple corresponding textual summaries of the multiple events; generating, using the textual summaries of the multiple events, a textual summary of the process performed by the user through the interactions between the user and the application program(s) executing on the computing device; and outputting the textual summary of the process.

Aspects of the present disclosure are directed to systems, methods, and computer readable media for executing actions for events associated with use of applications. A computing system can identify free text associated with an application to be evaluated for at least one of a plurality of events associated with a use of the application. The computing system can apply the free text to a machine learning (ML) architecture. The computing system can determine, based on applying the free text to the ML architecture, a value indicating a likelihood of occurrence of an event associated with the use of the application. The computing system can provide to a generative ML model, a model input based on the free text and the value, to obtain data for an electronic document characterizing the event. The computing system can execute an action using the data for the electronic document.

An event prioritization system and methods are provided that are configured to dynamically prioritize incoming events reported by a plurality of event ticketing systems while the incoming events are live or ongoing. The system includes a processor and a computer readable medium operably coupled thereto, the computer readable medium comprising a plurality of instructions stored in association therewith that are accessible to, and executable by, the processor, to perform event prioritization operations which include receiving an event associated with a computing issue affecting a customer entity, extracting a plurality of event prioritization factors from event data of the event, calculating scores for the plurality of event prioritization factors, determining a customer impact score of the event based on the scores, determining a criticality of the event based on the customer impact score and a service level agreement, and prioritizing the event in an event handler queue.

Certain aspects provide techniques and apparatus for executing queries in a computing system using machine learning models. An example method generally includes receiving a plan to satisfy a request in the computing system and event log data associated with execution of the plan. The plan generally specifies a first plurality of function calls at a first level of granularity. Using a plan refinement machine learning model, a refined plan is generated when the event log data indicates that execution of the generated plan results in one or more execution errors and the one or more execution errors are solvable. Generally, the refined plan specifies a second plurality of function calls at a second level of granularity, the second level of granularity being finer than the first level of granularity.

A computer-implemented method, computer program product and computing system for defining a formatting script for use with a Generative AI Model; receiving a plurality of notifications of a security event, wherein each of the plurality of notifications includes a computer-readable language portion that defines one or more specifics of the security event, thus defining a plurality of computer-readable language portions; processing at least a portion of each of the plurality of computer-readable language portions using the Generative AI Model and the formatting script to summarize each of the computer-readable language portions and generate a plurality of event summaries; and′ processing at least a portion of each of the plurality of event summaries using the Generative AI Model and the formatting script to summarize the plurality of event summaries and generate a summarized human-readable report.

A system and method for initiating remediation actions in a computing environment based on similar incident detection is presented. The method includes: generating a first incident record, based on a correlated plurality of event records, each event record indicating an event in a computing environment; generating a first vector based on the first incident record; detecting a similar incident record based on the first vector and a corresponding vector of the similar incident record; detecting a remediation action associated with the similar incident record, the remediation action previously executed in the computing environment; generating an adapted remediation action based on data extracted from the first incident record; and initiating the adapted remediation action in the computing environment.

A method, to manage an event invitation in a computer network environment, comprises presenting, using one or more processors, an event invitation creation indicium to a first user on a user interface of a computing device. Responsive to user selection of the event invitation creation indicium, an event creation interface is presented to receive event details. Responsive to receipt of the event details, an event invitation message is generated for communication, via a messaging system, by the first user to a second user of the messaging system, the event invitation message including a join indicium that is user-selectable to join a group chat related to the event. Responsive to a message send input from the first user, the event invitation message is sent, via the messaging system, from the first user to the second user. A request is received, from the second user, a request to join the group chat related to the event. A group chat message thread, associated with an event group including at least the first user and the second user, is then stored within the messaging system.

Examples of the present disclosure describe systems and methods for automating the identification of events in a text file. In examples, a computing system identifies a subset of a text file that comprises an unknown event using a set of rules. Each rule of the set of rules specifying a first pattern of characters is compared to the subset of the first text file. When the set of rules does not identify the unknown event, the subset of the text file is provided to a language model to generate a new rule with a second pattern of characters and an identifier of the new rule. The system then generates an updated set of rules by adding the new rule to the set of rules.

Certain aspects provide techniques and apparatus for executing queries in a computing system using machine learning models. An example method generally includes receiving a plan to satisfy a request in the computing system and event log data associated with execution of the plan. The plan generally specifies a first plurality of actions to be performed by the computing system at a first level of granularity. Using a plan refinement machine learning model, a refined plan is generated when the event log data indicates that execution of the generated plan results in one or more execution errors and the one or more execution errors are solvable. Generally, the refined plan specifies a second plurality of actions to be performed by the computing system at a second level of granularity, the second level of granularity being finer than the first level of granularity.

A computer-implemented method, a computer system and a computer program product orchestrate event-driven workloads in a satellite environment. The method includes receiving a workload from a client for deployment to a satellite in a plurality of satellites, where the workload includes requirements. The method also includes obtaining satellite data for each satellite in the plurality of satellites, where the satellite data includes a capability of the satellite and a current status of the satellite. The method further includes determining that the capability of the satellite satisfies the requirements of the workload. In addition, the method includes identifying a relevant satellite in the plurality of satellites based on the current status of the satellite. Lastly, the method includes deploying the workload to a ground station associated with the relevant satellite.

An endpoint coupled in a communicating relationship with an enterprise network may include a data recorder configured to store an event stream of data indicating events on the endpoint including types of changes to computing objects, a filter configured to locally process the event stream into a filtered event stream including a subset of types of changes to the computing objects, and a local security agent. The local security agent may be configured to transmit the filtered event stream to a threat management facility, respond to a filter adjustment from the threat management facility by adjusting the filter to modify the subset of types of changes included in the filtered event stream, and respond to a query from the threat management facility by retrieving data stored in the data recorder over a time window before the query and excluded from the filtered event stream.

Techniques for a service provider network to communicatively couple services and / or applications in a serverless computing environment. A pipe component can configure a pipe to integrate two services by transmitting data between services and / or applications using the pipe. The pipe may also be configured to transform how a service processes an event, control timing of event transmissions using the pipe, define an event structure for an event, and / or batch events. Pipes enable an application or service to exchange data with a variety of services provided by the service provider network while controlling what type of data is generated, stored, or transmitted.

A data platform monitors a compute environment by performing multi-stage heuristic analysis of event data representing a plurality of events occurring within the environment. The platform utilizes multiple event analyzers, each configured according to a distinct analysis heuristic, to evaluate different subsets of the event data and generate corresponding output signals. A higher-level event analyzer applies a further heuristic to the multiple output signals to generate a composite alert signal, indicating whether the combination of analyzed events collectively represents a security intrusion or other anomalous condition of sufficient severity to warrant alerting. Based on the composite alert signal, the platform performs an alert-based operation, such as generating a user-facing alert, initiating an automated mitigation, or updating a contextual model of system behavior. By combining the analytical outputs of heterogeneous heuristics, the disclosed architecture enhances the accuracy and contextual relevance of automated intrusion detection within complex computing environments.

Provided herein are systems and methods for simulating testing environments for digital therapeutic applications to address conditions over spans of time. A computing system may select a trigger from a plurality of triggers of an event scheduler for addressing a condition. The computing system may set a clock to a timestamp of the trigger, wherein the clock is accessible to the service and to the user device. The computing system may cause the service to transmit a message for addressing the condition to the user device, responsive to the timestamp of the clock corresponding to the timestamp of the trigger. The computing system may identify that the message is communicated between the service and the user device in accordance with the trigger. The computing system may determine that the trigger of the event scheduler is validated, responsive to identifying that the message is communicated.

Systems and methods for automatically populating documents about special entities are disclosed herein. An example method is performed by one or more processors of a computing system. The example method may include receiving user data, extracting a list of entities associated with the user and a list of events that occurred between the user and the entities, transforming metadata for the events associated with entities of interest into vectorized embeddings, selectively classifying, using a binary classifier model, ones of the entities as special entities and ones of the events as special events for a set of documents, assigning, using a multi-class classifier model, one of a plurality of categories to each special event associated with each special entity, each of the categories mapping to a corresponding section within the set of documents, and populating, for each special entity, the corresponding sections within the set of documents based on the categories.

Systems and methods are described for analyzing information relating to technical events associated with client devices in an organization (e.g., hardware and / or software malfunctions or performance inefficiencies originating at a client device or elsewhere in an organizational computing system). Particularly, machine learning techniques may use one or more trained artificial neural networks to classify technical events. Classifications of technical events may include, for example, causes of technical events, identifications of other affected devices, and / or steps for resolving technical events. Additionally, systems and methods are described for analyzing information relating to organizational ideas conceived of by client device users within the organization.

A method of monitoring a network for linked events includes receiving an indication of an occurrence of a first event in a computing environment, calculating a first estimated rate of occurrence of the first event based on a first cache associated with the first event, and identifying an occurrence of a second event within a threshold amount of time prior to the occurrence of the first event. The method further includes calculating a second estimated rate of occurrence of the second event based on a second cache associated with the second event and determining, based on the first estimated rate of occurrence of the first event and the second estimated rate of occurrence of the second event, whether the occurrence of the first event and the occurrence of the second event have a common cause.

A system and method for ingesting delayed logs for cybersecurity detection is presented. The method includes detecting a resource deployed in a computing environment, the resource configured to generate a local log on a disk of the resource; periodically fetching the local log from the disk, the local log including a plurality of event records written by at least a software application executed on the resource; applying a control on the fetched local log; and detecting a cybersecurity issue on the resource based on a result of applying the control.

The invention provides a security detection method and device, equipment, a medium and a product, and the method comprises the steps: obtaining a first code file related to a target file event in response to the detection of the target file event of first computing equipment; wherein the first code file is used for being executed in the first computing device; generating a first prompt word; wherein the first prompt word comprises a first code file; indicating information for detecting the following target data: external input in the first code file, a target execution function in the first code file and a transmission path of the external input in the first code file; the information is used for indicating a detection mode for detecting the first code file based on the target data; and sending the first prompt word to the first language model, and receiving a detection result of the first code file returned by the first language model. According to the method, whether the code file is related to the rebound shell behavior or not is accurately judged, rebound shell detection of cross-programming languages is achieved, and expansibility and applicability are improved.

Systems and methods include an Information Handling System (IHS) that is adapted to diagnose root causes of issues reported by hardware and / or software of the IHS. Telemetry is monitored that specifies operating status information for hardware components of the IHS. Stress event are detected that are related to the hardware components. One or more stress tests are identified for evaluation of each hardware component that is related to stress event. While monitoring the telemetry, the stress tests are conducted in order to replicate the detected stress event. When the detected stress event is replicated, a root cause hardware component of the IHS is determined based on machine learning evaluation of the telemetry generated during replication of the stress event.

An operations computing system receives event data for one or more events and generates, based on the event data, an incident object for an incident. The incident object includes incident data including a priority level. The operations computing system generates an incident workflow for the incident object. The operations computing system applies, using an application programming interface, a machine learning model to determine an adjusted priority level for the incident object, in which the machine learning model is configured to receive one or more valid natural language prompts related to incident priority level. The operations computing system receives the adjusted priority level for the incident object, and updates the incident object associated with the incident workflow with the adjusted priority level. The operations computing system performs one or more actions included in the incident workflow for the incident object based on the adjusted priority level for the incident workflow.

Automation solutions for event logging and debugging on KUBERNETES are disclosed. A system for event logging and debugging on a distributed application cluster includes a user interface and at least one processor for executing instructions. The instructions, when executed, instruct the at least one processor to provide an edge module configured to deploy a Berkeley Packet Filter (BPF) probe and a BPF program in a computing environment. The BPF probe is triggered based on an event associated with a distributed application running in a user space of the computing environment. Data associated with the event is collected in a kernel space of the computing environment via the BPF program and transferred from the BPF program to the edge module. A query request associated with the collected data is sent to the edge module. A response corresponding to the collected data is received at the user interface.

A targeted event monitoring and alert service may be implemented by a computing system. The system can provide a live dashboard on a graphical user interface for a respective user. The live dashboard can provide (i) real-time, localized contextual information of an event for a location corresponding to the respective user, and (ii) a set of real-time risks to the property of the respective user. The computing system executes an engagement monitor comprising a machine learning computer model to (i) monitor the respective user's interactions with the live dashboard, and (ii) dynamically adapt content flows of the live dashboard based on learned response information corresponding to the respective user's interactions with the targeted event monitoring and alert service.

Provided herein are systems and methods for methods for detecting expected reductions of interactions across sessions. A computing system can identify event data identifying interactions by a user with a first session for digital therapeutic content to address a condition. The computing system can apply the event data to a machine learning (ML) model. The computing system can generate a likelihood of the user interacting with a second session for digital therapeutic content based on applying the event data to the ML model. The computing system can detect an expected reduction in interactions by the user with the second session, responsive to the likelihood of the user not satisfying a threshold. The computing system can provide an output for the user based on detecting the expected reduction in interactions. In this manner, the efficacy of the medication that user is concurrently taking to address the condition may be improved.

A computing system comprising one or more computing devices can access a file comprising documentation that includes a textual description and a source code snippet written to comply with a programming language syntax. The computing system can identify the source code snippet. The computing system can generate an executable based on the source code snippet. The computing system can initiate a test process that accesses the executable, the test process causing the executable to cause an event. The computing system can determine that the event is a valid event or an invalid event.