A method and/or system for automated detection and automated remediation of anomalies in Robotic Process Automation (RPA) environment is disclosed. The method comprises auto discovering resources (RPA components and its dependencies) in an RPA platform. The discovered resources are monitored though observation metrics whose values are obtained by executing pre-defined scripts. The obtained values are validated against threshold values to determine if there are any anomalies, wherein the threshold values may either be static values or dynamic values. If there is a breach of threshold, a remediation plan is automatically executed causing the remediation of anomalies. The system is trained to determine the dynamic threshold values through machine learning models which are developed and trained through metrics data and by determining error patterns from the historic unstructured log data.

During operation, an electronic device may store, in memory, information associated with operation of the electronic device, such as during communication and processing of one or more packets or frames. Furthermore, an error-event monitor in the electronic device may, during a time interval, analyze at least a portion of the stored information to detect an occurrence of an error event in one or more types of error events in the electronic device. When the error event occurs during the time interval, the electronic device may perform a remedial action and may persist, in the memory, at least a second portion of the stored information associated with the error event. Otherwise, when the error event does not occur during the time interval, the electronic device may overwrite, in the memory, the stored information with additional information associated with operation of the electronic device during subsequent communicating and processing.

A method of operating a telemetry system includes automatically populating a base field of a schema in an event definition using a logging library of the telemetry system for an event of an instrumented application, and automatically populating a conditional field of the schema in the event definition using the logging library in response to a selected condition for the event.

Event records from multiple computing devices are received at a managing unit. Individual event records include an event identifier field including an event identifier identifying a first event associated with a particular computing device, a parent event identifier field identifying a parent event that initialized the first event, and an entity identifier field including an entity identifier identifying the particular computing device. The managing unit generates log records associated with event identifiers included in the event records. The log records include state fields indicating a state of a particular event associated with a particular event identifier. Based on a correlation of the event and log records, the managing unit determines at least two computing devices associated with events resulting in an error state, and identifies parent events that initialized the events with errors. The managing unit generates a report linking the parent events to the events having an error state.

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. An improved approach is provided for identifying log files that have undergone a change in status that would require retrieve of its log data, by including a module directly into the operating system that allows the log collection component to be reactively notified of any changes to pertinent log files.

An instrumentation analysis system processes data streams by executing instructions specified using a data stream language program. The data stream language allows users to specify a search condition using a find block for identifying the set of data streams processed by the data stream language program. The set of identified data streams may change dynamically. The data stream language allows users to group data streams into sets of data streams based on distinct values of one or more metadata attributes associated with the input data streams. The data stream language allows users to specify a threshold block for determining whether data values of input data streams are outside boundaries specified using low/high thresholds. The elements of the set of data streams input to the threshold block can dynamically change. The low/high threshold values can be specified as data streams and can dynamically change.

Techniques are disclosed for capturing diagnostics data in a distributed computing environment comprising a plurality of computing devices executing a plurality of Kubernetes pods. A worker node is configured with a staging area for storing temporary diagnostics data. An agent is configured to upload the temporary diagnostics data. Each container in the worker node is assigned a directory in the staging area for writing the container's temporary diagnostics data. When a container in the worker node has written a temporary diagnostics data file to the container's directory in the staging area, the temporary diagnostics data file is uploaded to the persistent storage.

Systems, devices or methods provide for control of sensitive data in a computer system that includes at least one central server communicatively-coupled to a plurality of client computers. A particular method relates to the execution of software code on the at least one central server to monitor data communications of the plurality of client computers for sensitive data. A subset of the data communications is restricted when sensitive data is detected. Configuration data is provided to each of the plurality of client computers. Software code is executed on each of the plurality of client computers to detect accesses to sensitive data by one or more applications running on a client computer. Actions of the one or more applications running on a client computer are monitored to determine whether or not a trigger event has occurred. In response to determining that the trigger event has occurred, a notification is sent.

Disclosed herein are system, apparatus, article of manufacture, method, and/or computer program product embodiments for monitoring long-standing computing resources. An apparatus may operate by receiving a cloud monitoring notification, where the cloud monitoring notification may indicate an occurrence of a monitored condition. The apparatus may then operate by scanning a cluster computing system for resource having a client assigned resource identifier and a computing resource attribute based on a resource identifier scan parameter and a resource attribute scan parameter. The apparatus may further operate by generating a resource notification request based on the scanning of the cluster computing system and transmitting the resource notification request to a communications system to notify a user that the resource has a computing resource attribute that match the resource attribute scan parameter.

A network monitoring system may receive a configuration request to generate a configuration file associated with collecting feature or debug data associated with a feature, hardware, or software associated with a network device. The network monitoring system may determine a command profile associated with the feature, hardware, or software that identifies a set of commands associated with obtaining the feature or debug data from the network device. The network monitoring system may determine respective parameters of one or more commands of the set of commands. The network monitoring system may determine, based on the respective parameters, respective arguments of the one or more commands. The network monitoring system may generate the configuration file based on the respective arguments and may perform an action associated with the configuration file to permit the configuration file to be used to collect the feature or debug data from the network device.