An interaction tracking system tracks user interactions with an application. The tracked interactions may be stored in a data structure along with information describing an application state of the tracked application resulting from the tracked interactions. The interaction tracking system stores the data structure in a database for subsequent search and retrieval, which allows different users to activate the stored data structure and initiate the application in application state described in the data structure. The interaction tracking system also transmits the data structure to other communication devices, where the data structure is activated on the receiving communication device.

When a restart event is detected within a technology landscape, restart-impacted performance metrics and non-restart-impacted performance metrics may be identified. The non-restart-impacted performance metrics may continue to be included within a performance characterization of the technology landscape. The restart-impacted performance metrics may be monitored, while being excluded from the performance characterization. The restart-impacted performance metric of the restart-impacted performance metrics may be transitioned to a non-restart-impacted performance metric, based on a monitored value of the restart-impacted performance metric following the restart event.

A method for detecting system problems in a distributed control system including a plurality of computational devices is suggested. The method includes:—deploying one or more software agents on one or more devices of the system;—monitoring, via the one or more software agents, a system configuration and/or a system functionality;—detecting a problem in the monitored system configuration and/or a system functionality;—adding one or more new software agents and deploying the one or more new software agents on one or more devices of the system associated with the problem;—collecting data associated with the problem, via the added software agents.

A system selects a telemetry allocation for the transmission of data from multiple transmitters. An allocation matrix defines a split ratio for data generated by a data source that is split between transmitters. The split ratio is defined for each data source of a plurality of data sources. (A) A storage buffer model is executed based on the allocation matrix to simulate a buffer that stores data from each data source that exceeds a download bandwidth value. (B) Performance parameter values are stored in association with the allocation matrix. (C) The allocation matrix is updated to redefine at least one split ratio. (D) (A) through (C) is repeated with the allocation matrix replaced with the updated allocation matrix until each unique permutation of values for the split ratio is processed. An allocation matrix is selected from allocation matrices stored in (B) based on the plurality of performance parameter values.

Techniques related to communication between independent containers are provided. In an embodiment, a first programmatic container includes one or more first namespaces in which an application program is executing. A second programmatic container includes one or more second namespaces in which a monitoring agent is executing. The one or more first namespaces are independent of the one or more second namespaces. A monitoring agent process hosts the monitoring agent. The monitoring agent is programmed to receive an identifier of the application program. The monitoring agent is further programmed to switch the monitoring agent process from the one or more second namespaces to the one or more first namespaces. After the switch, the monitoring agent process continues to execute in the second programmatic container, but communication is enabled between the application program and the monitoring agent via the monitoring agent process.

A device that may communicate with at least one device is disclosed. The device may include a communication component to communicate with the devices over a channels about data associated with the devices. The device may also include reception component that may receive a request for information from a host. The device may also include a transmission component to send the data about the devices to the host.

Systems, methods and computer program products for simulating workflows and activities of physical assets using digital twin models. User-defined simulations are performed by selectin digital twin components being analyzed during the simulation, concentrating the analysis on the selectively defined components and bypassing components that will not be simulated. Users can design the digital twin simulation using one or more available digital twin models. The model can be the most current digital twin model, a previous version of a model or a hybridized model comprising components or portions from multiple versions of the available digital twins. Users can further customize simulations by selecting components or sections of the digital twin model to selectively bypass during the simulation or provide overriding values for non-simulated portions of the digital twin which can be used as entry criteria inputted into the next simulated section or component of the digital twin, to complete the simulation.

A system for monitoring a computing platform configured to receive a particular metric from metrics associated with the computing platform. A plurality of layers of the computing platform are monitored. Monitoring parameters of the plurality of layers of the plurality of layers are determined. Heuristics of each monitoring parameter are determined over a time period. Monitoring packages are created from the monitoring parameters based on correlations between groups of monitoring parameters, the plurality of layers, and the metrics. Based on the particular metric, a string of monitoring packages is dynamically created from the monitoring packages. A behavior of the particular metric is determined in a configurable time duration in the future using the dynamically created string of monitoring packages. Possible failures of the computing platform related to the particular metric are predicted in an environment of the computing platform based on the determined behavior of the particular metric.

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 method for installing and using hardware specific plugins to a monitoring application includes installing, by use of a processor, a hardware specific plugin to a monitoring application that monitors health of a monitored computing system. The plugin corresponds to a hardware device of the monitored computing system monitored by the monitoring application. The plugin includes analytics rules corresponding to hardware parameters monitored within the hardware device and received by a server comprising the processor and running the monitoring application. The method includes receiving, by use of a processor, data corresponding to the hardware parameters of the hardware device, applying, by use of a processor, the analytics rules of the plugin to the received data of the monitored hardware parameters of the hardware device, and sending, by use of a processor, an alert in response to determining that the received data violates an analytics rule of the plugin.