Systems and methods for collecting performance data in high performance computing systems are disclosed. To prevent massive amounts of performance data from overwhelming the system and negatively impacting performance, collected performance data may be processed into two databases: (i) an aggregate database, and (ii) a time-series database holding the newest information for real time performance analysis. Storage space may be saved by using a FIFO buffer to store collected performance data. A real-time performance collection engine may adjust the performance sampling interval used and the particular performance counters used based on measured system impact and feedback from other system modules consuming the performance data.

The present invention provide a terminal device, including: at least one sensor, a data processing unit, a memory, a CPU, and a storage, where the sensor is configured to sense a corresponding measured object and generate corresponding sensing data; and the data processing unit is configured to collect the sensing data jointly with the CPU in a mutually complementary manner, store the collected sensing data in the memory, perform feature extraction on the sensing data stored in the memory, and store extracted feature data in the storage, where the mutually complementary manner refers to that, when one of the data processing unit and the CPU is in a working state, the other is in a dormant state. The terminal device provided by the embodiments of the present invention can improve a utilization rate of the CPU.

Techniques for monitoring performance of an OSGi-based application having multiple bundles are disclosed. In some embodiments, a computer system performs operations comprising: running an OSGi application having a plurality of adapter bundles, the running of the OSGi application comprising using each one of the plurality of adapter bundles to connect to a corresponding source database and replicate data from the corresponding source database; running a profiler bundle concurrently with the running of the OSGi application, the profiler bundle being generated using an AOP extension, the running of the profiler bundle comprising collecting performance data for selected ones of the plurality of adapter bundles during the running of the OSGi application, the selected ones of the plurality of adapter bundles being defined based on input provided by a user via a GUI during the running of the OSGi application; and performing a function using the collected performance data.

A non-intrusive interaction method includes an electronic device that obtains a description file of an application, where the description file indicates a function to be implemented by the application, and is defined using a non-intrusive protocol description; determines a first component based on the description file, where the first component is a component that is in components of the electronic device and that can implement the function that needs to be implemented by the application, and the component is configured based on a non-intrusive protocol to provide a device capability service and can implement an independent function; and runs, based on the description file to provide the device capability service for the application, the first component to implement the function.

According to at least one aspect of the present invention, a system for automatically generating a data-center network mapping for automated alarm consolidation is provided comprising a plurality of devices, and at least one computing device communicatively coupled to each of the devices, the at least one computing device being configured to receive operational data from each of the devices, the operational data being indicative of at least one of a power path, cooling or temperature zones, or communications paths, determine, based on the operational data, device relationships between each of the devices, receive, from each of the devices, a respective alarm of a plurality of alarms, determine alarm relationships between at least two of the plurality of alarms, consolidate, based on the determined device relationships and based on the determined alarm relationships, the plurality of alarms into a consolidated alert, and provide the consolidated alert to a user.

Aspects of the present disclosure relate to engagement-based communication session management. In examples, an interaction intent metric is generated for a user according to a variety of factors relating to the user (e.g., the semantic content and tone of the user's speech, a direction of the user's gaze, and historical user characteristics) and the meeting (e.g., whether the user's name was mentioned by another communication participant or whether another communication participant is soliciting input), among other examples. Accordingly, if a positive interaction intent is identified and the user is currently muted, an action can be recommended to address the mismatch between the positive interaction intent and the muted status of the user. Similarly, if a negative interaction intent is identified and the user is currently unmuted, an action can be performed to address the mismatch between the negative interaction intent and the unmuted status of the user.

An instrumentation overhead regulation technique regulates an amount of work performed by a client library of an investigative platform used to monitor, diagnose and solve errors associated with application development and production. The client library calculates processing resources utilized during its runtime activity to enable adjustment of the amount of work it performs based on the measured activity. An agent may determine the overhead activity impact to user application performance by monitoring processing resource metrics of the user application. The agent analyzes the calculated overhead and processing resource metrics to render decisions to automatically regulate the capture fidelity of the client library. Regulation of the capture fidelity may be implemented by modifying parameters of a dynamic configuration. If results of the analysis indicate a potential issue, the amount of work the client library performs may be trimmed to ensure that the calculated overhead of the client library and its impact on user application performance does not exceed a predetermined threshold.

Performing a targeted partial recording of an executable entity includes executing the executable entity at a processor. While executing the executable entity, it is determined that a target chunk of executable instructions are to be executed as part of the execution of the executable entity. Each input to the target chunk of executable instructions is identified, including identifying at least one non-parameter input. A corresponding value for each identified input is recorded into a trace, along with information identifying the target chunk of executable instructions.

A server management switch discovers and identifies its switch ports that are connected to communication ports of baseband management controllers (BMC's) of server computers. The server management switch isolates the identified BMC-connected switch ports such that network traffic on a BMC-connected switch port is restricted to a switch port that has a connection, either directly by a link or over a server management network, to a server management computer. Network traffic on BMC-connected switch ports are monitored and controlled in various ways to further protect the BMC's from security attacks.

An instrumentation overhead regulation technique regulates an amount of work performed by a client library of an investigative platform used to monitor, diagnose and solve errors associated with application development and production. The client library calculates processing resources utilized during its runtime activity to enable adjustment of the amount of work it performs based on the measured activity. An agent may determine the overhead activity impact to user application performance by monitoring processing resource metrics of the user application. The agent analyzes the calculated overhead and processing resource metrics to render decisions to automatically regulate the capture fidelity of the client library. Regulation of the capture fidelity may be implemented by modifying parameters of a dynamic configuration. If results of the analysis indicate a potential issue, the amount of work the client library performs may be trimmed to ensure that the calculated overhead of the client library and its impact on user application performance does not exceed a predetermined threshold.