Systems and methods are provided for dynamic configuration of interactive controls available on a dashboard. Interactive controls may be dynamically configured by manipulating network resource address information for a network resource that provides a dashboard, for example using query string parameters. For example, a dashboard that displays one type, source, or summary of information can be dynamically configured to allow interactive selection and display of another type, source, or summary of information depending on values passed in the network resource address information for the dashboard network resource.

A method and system for remote testing of a plurality of devices is disclosed. The method may include receiving a request from a client system to perform testing on a set of remote devices. The local system and the client system are connected via a first network connection and the plurality of remote devices are connected to the local system via a second network connection. The method may further include receiving an input from the client system with reference to a test-suite to perform a testing action on the set of remote devices, generating a test command corresponding to the input, and transmitting the test command to each of the set of remote devices. The method may further include receiving feedback from each of the set of remote devices and transmitting the feedback to the client system.

An information processor includes an operation history obtaining unit configured to obtain operation histories created user operations at a terminal device; a function identifying unit configured to, based on the obtained operation histories, identify a function performed by the user operations as an operation target function; an operation extracting unit configured to, based on information about the operation target function identified by the function identifying unit, extract predetermined operation histories from the obtained operation histories; an index calculating unit configured to calculate an index which indicates a level of efficiency of the operations for the operation histories extracted by the operation extracting unit; an operation selecting unit configured to, based on the index, select the operation histories having a predetermined efficiency; and an output controller configured to output a guide information based on the operation histories selected by the operation selecting unit.

Security related anomalies in the data related to network entities are identified, and a risk score is assigned to each entity based on the anomalies. Visualization data is generated for a color-coded interactive visualization. Generating the visualization data includes assigning each entity to a separate polygon to be displayed concurrently on a display screen; selecting a size of each polygon to indicate one of: a number of security related anomalies associated with the entity, or a risk level assigned to the entity, where the risk level is based on the risk score of the entity, and selecting a color of each polygon to indicate the other one of: the number of security related anomalies associated with the entity, or the risk level assigned to the entity; and causing, the color-coded interactive visualization to be displayed on a display device based on the visualization data.

An interface receives reported information from a system on chip (SOC), where the reported information includes: (1) hardware-reported information that is reported by a hardware functional module included in the SOC and (2) firmware-reported information that is reported by a firmware functional module included in the SOC. A processor receives one or more display settings and generates visual information based at least in part on: (1) the one or more display settings, (2) the hardware-reported information, and (3) the firmware-reported information. The visual information is displayed via a display.

A method may include obtaining at least one dataset that includes information corresponding to periods of usage of a plurality of components within a cloud infrastructure and usage cost for each component of the plurality of components within the cloud infrastructure. The method may include comparing the information corresponding to the periods of usage with at least a portion of the information corresponding to the usage cost for components. The method may include determining a cost for one or more of the components for a period of time. The cost may be determined based on the comparison of the information corresponding to the periods of usage of the components with at least the portion of the information corresponding to the usage cost for the components. The method may include generating a visualization that includes information representative of the cost of the components and displaying the visualization via a display screen.

A plurality of completion times associated with an application request may be obtained. The plurality of completion times may include a first completion time and a second completion time. A plurality of response times associated with a first asynchronous operation triggered by the application request may be obtained. The plurality of completion times may include a first response time associated with the first completion time and a second response time associated with the second completion time. A first correlation score may be determined describing an effect of the first asynchronous operation on the application request based on the first completion time, the second completion time, the first response time, and the second response time. Visualization data may be generated representing the first correlation score.

Systems and methods for generating, administering and analyzing a user experience study are provided. In particular, intents can be generated from a user experience study by applying one or more screener questions to participants and subjecting the screened participants to one or more tasks. Corresponding clickstreams and success data for each participant engaging in the tasks can be recorded. The success and clickstream data can also be aggregated for all the screened participants as aggregated results. Video data including audio for each of the screened participants can also be recorded.

A system and method for real-time or near real-time anomaly detection and root cause automation in production environments or in other environments using shrunk dynamic call graphs are provided. The system includes an instrumentation agent that generates shrunk dynamic call graphs and exceptions/errors by injecting monitoring code or probes or call-tags into monitored application, a data agent that forwards collected data to the analysis engine over a network, an analysis engine that performs continuous clustering using machine learning, anomaly, and root cause detection. The system also includes a reporting module to report the anomaly.

A system and process extract software application performance data from disparate ownership sources and make the various source data compatible for comparison data. A software application's performance in the marketplace may be compared to other applications in a same group with comparable data information. A M2M (mobile-to-mobile) technology is an interface layer connection to a backend server that builds machine learning pipelines and may use artificial intelligence to turn massive datasets into identifiable patterns, algorithms and statistical models. This layer is capable of cleaning, aggregating, and organizing data from disparate sources to produce meaningful conclusions to complex problems to inform strategic business decisions.