An estimation model utilizes simulations of an autonomous vehicle and objects detected near the automated vehicle to develop estimates of tolerable frame processing latency to develop real world frame processing latency estimates for similar driving conditions. An estimation model can a minimum tolerable latency for processing the frames of image data of an object detection camera on an autonomous vehicle using the object state data of the objects detected near the autonomous vehicle. An autonomous vehicle system process can determine if the processing latency of a sensor is greater than the modeled tolerable latency for that sensor, then a safety check is failed and an alert is sent. An autonomous vehicle system process can determine if the processing latency of a sensor is greater than the modeled tolerable latency for that sensor, then the hardware resources are prioritized to the processing for that sensor. An autonomous vehicle system process can determine if the processing latency of a sensor is greater than the modeled tolerable latency for that sensor, hardware performance may be increased.

A testing and verification system for an equivalent physical configuration of an in-flight entertainment and communications system with one or more hardware components includes a virtual machine manager. One or more virtual machines each including a hardware abstraction layer is instantiated by the virtual machine manager according to simulated hardware component definitions corresponding to the equivalent physical configuration of the hardware components. The virtual machines are in communication with each other over virtual network connections. A test interface to the one or more virtual machines generate test inputs to target software applications installed on the virtual machines. A display interface is connected to the virtual machines, with results from the execution of the target software applications responsive to the test inputs are output thereto.

Techniques for performing cache operations are provided. The techniques include tracking performance events for a plurality of test sets of a cache, detecting a replacement policy change trigger event associated with a test set of the plurality of test sets, and in response to the replacement policy change trigger event, operating non-test sets of the cache according to a replacement policy associated with the test set.

A method for providing end-to-end monitoring of an application is disclosed. The method includes receiving, via a graphical user interface, a request to monitor the application, the request including information relating to the application; generating a service call based on the request, the service call relating to a synthetic transaction in a master configuration; scheduling the service call in the master configuration; generating a synthetic workflow based on the service call; executing the synthetic workflow based on a result of the scheduling; and capturing a metric from the executed synthetic workflow.

Methods, systems and computer program products are described herein that enable executing simulation scenarios against a computing system simulation model to determine one or more appropriate modifications to a physical, operating computing system. The simulation model includes virtual components corresponding to a plurality of computing system components of the computing system. The virtual components of the simulation model are included in a graph database, and the virtual components correspond to one or more nodes and edges stored as a graph in the graph database. Execution of the simulation scenario produces a simulation result that is analyzed to determine at least one modification of the computing system, and where thereafter, the computing system is modified at least according to the determined modification. Embodiments also enable testing a physical computing system to determine whether the simulation model of the computing system is accurate, and/or to determine one or more computing system modifications.

A non-transitory computer-readable medium includes instructions that, when executed, cause one or more processors to perform operations. The operations include receiving a first request to access a digital representation that is assigned to an asset of an industrial automation system and includes code specific to operating, maintaining, or diagnosing the asset. The operations also include verifying a security access for the first request, providing the computing device access to the digital representation, receiving an input to modify the code from the computing device and, performing one or more simulations based on the modified code by utilizing the digital representation. Additionally, the operations include sending one or more simulation results to the computing device, receiving, from the computing device, a second request for pushing the modified code to the asset, and in response to receiving the second request, causing the modified code to be sent to the asset.

A method may be performed by a network server and includes: applying historical raw user data as an input to a first application running in a simulation environment; receiving activity log entries from the first application in the simulation environment; identifying a first group of the activity log entries corresponding to an error of the first application; saving an error entry in non-volatile storage media in response to identifying the first group of the activity log entries, the error entry including the first group of the activity log entries and an identification of action to be taken in response to the error of the first application; and causing a monitoring system to generate a first alert corresponding to the error entry.

A testing platform for an auto-decision engine is disclosed. An auto-test database for a decision engine may be accessed and modified by, for example, executing an application programming interface protocol of a third-party computing system. The decision engine may be bypassed, and a simulated auto-decision may be requested based on a unique key corresponding to a scenario in the auto-test database. A graphical user interface displays information regarding the auto-test database on a user computing device, and one or more output data fields in the auto-test database may be modified.

A distributed network system and method includes a processing unit configured to manage safety data for a plurality of medical devices, a database software component in communication with the processing unit, and a monitoring software component in communication with the processing unit. The monitoring software component is configured to monitor a number of messages between a number of medical devices and the processing unit, to process performance parameters to generate an overall performance index, and to generate an output that is viewable by a user. The output includes relative contributions of each of the performance parameters to the overall performance index, where the overall performance index is generated using a weighting factor associated with each of the performance parameters. The performance parameters include the number of messages waiting to be processed, which has the largest weighting factor, and a disk queue length, which has the smallest weighting factor.

Embodiments monitor for faults in a cloud based network for a plurality of features comprising an application and dependent features. Embodiments generate a graphical representation of the plurality of features comprising a plurality of nodes and corresponding relationships between the nodes, each node corresponding to one of the plurality of features. Embodiments monitor for events for the plurality of features, the events corresponding to one or more of the nodes, to generate monitored events. Embodiments populate a graph database with the monitored events and classify each of the nodes with a trained graph neural network (“GNN”), the classification comprising a prediction of a failure of at least one node. Based on the classifying, for a failure node corresponding to the prediction, embodiments generate a new alert for the failure node or revise a threshold for an existing alert for the failure node.