Some embodiments are directed to a logging within a software application executed over an assembly of information processing devices. More particularly, some embodiments relate to a method allowing process logging in the case of a software application operating with several processes and/or threads.

A method for debugging a program, based on simulating an object program and comparing simulated waveforms with standard waveforms are applied in an electronic device. A simulated environment corresponding to the object program is established and multiple instructions from code of the object program are mapped against the standard waveforms. Trigger points are set in the object program, the object program is run from the trigger point and simulation waveforms are stored. The simulation waveforms are compared with the standard waveforms, and the location of a bug of the object program is found according a comparison. The bug may be resolved or cured. The electronic device utilizing the method is also disclosed.

Systems and methods are provided for detecting anomalies on multiple layers of a computer system, such as a compute server. For example, the system can detect anomalies from the lower firmware layer up to the upper application layer of the compute server. The system collects train data from the computer system that is under testing. The train data includes features that affect performance metrics, as defined by a selected benchmark. This train data is used in training machine learning (ML) models. The ML models create a train snapshot corresponding to the selected benchmark. Additionally with every new release, a test snapshot can be created corresponding to the selected benchmark or workload. The system can detect an anomaly based on the train snapshot and the test snapshot. Also, the system can recommend tunings for a best set of features based upon data collected over generations of compute server.

The present invention is a method and system for automatedly producing at least one desktop analytics trigger. Upon receiving at least one type of data input, the system analyzes the data input and produces at least one desktop analytics trigger based on the results of the analysis of the data input. The data input can include data on the programs, applications, or information a user utilizes during a task, to allow use of desktop process analytics. This process may be used to either generate a new desktop analytics trigger or update an existing desktop analytics trigger.

Methods and systems for managing notifications relating to execution of microservices are described herein. A format of notifications relating to execution of a plurality of microservices may be defined. The format may provide that all notifications generated based on the format comprise code. The code may indicate, for example, an identity of one of a plurality of microservices, a version of the code, an occurrence of an issue in execution of the one of the plurality of microservices, and/or one or more scripts which may be executed to address an issue of the notification. Two or more notifications may be received, and the one or more notifications may be formatted based on the defined format. A third notification may be generated based on a comparison of the two or more notifications. The third notification may be transmitted to a computing device.

The present invention is a method and system for automatedly producing at least one desktop analytics trigger. Upon receiving at least one type of data input, the system analyzes the data input and produces at least one desktop analytics trigger based on the results of the analysis of the data input. The data input can include data on the programs, applications, or information a user utilizes during a task, to allow use of desktop process analytics. This process may be used to either generate a new desktop analytics trigger or update an existing desktop analytics trigger.

Aspects of the disclosure provide for a circuit, in some examples, including a storage element, a co-processor, and a telemetry sequencer coupled to the storage element and the co-processor. The telemetry sequencer is configured to implement a digital state machine to receive configuration information indicating a type of telemetry data for generation, retrieve operations and operands, where the operations and the operands define a sequential series of actions for execution to generate the telemetry data, drive the co-processor with the operations and the operands by passing some of the operations and some of the operands to the co-processor for processing by the co-processor, receive, from the co-processor, and store an intermediate output of the series of actions as the telemetry data in a first format, and receive, from the co-processor, and store a final output of the series of actions as the telemetry data in a second format.

A method, electronic device, and computer program product for processing data is disclosed. The method includes acquiring a configuration file for generating and sending a structured report, the structured report involving analysis of an application. The method also includes acquiring, based on an address of a data source in the configuration file, data from the data source to add the data to the structured report, the data source including the same type of data generated by the application. The method includes sending, based on an identifier of a target server in the configuration file, the structured report to the target server for analyzing the application. With this method, the format of a structured report to be acquired can be adjusted at any time without version upgrade, thereby saving time.

A method for an exchange of equipment performance data including the steps of: obtaining performance data of a device not having Internet connectivity; converting the performance data into a scannable code; capturing an image of the scannable code; decoding the scannable code using a computing device to extract an address string encoded in the scannable code, the address string comprising an address of a remote server and the performance data; and initiating, by the computing device, an Internet connection with the remote server using the address string thereby to provide the performance data to the remote server.

Disclosed herein are system, method, and computer program product embodiments for operations related to intelligent action logging for cloud applications. An embodiment operates by identifying an event associated with an application executing on the processor. The event is compared to criteria for logging the event in one or more of a plurality of logs. The log includes its own unique criteria for logging the event. If it is determined that the event satisfies the criteria of the action log, then detail about the event are written onto an action log using a log format associated with the action log, which is different from a log format of a technical log.