Abstract: A network system to use machine learning systems to create chaos testing scenarios on cloud-based applications. The system uses inputs from applications that are implemented on user computing devices to allow users to interface with a network or other system. The system creates a model of the application based on input data received from a network of applications, the model representing a structure, method, and dependencies of the application. The system identifies points of failure of the application and generates one or more chaos testing simulation scenarios that target the identified points of failure. The system performs the chaos testing based on the received simulation scenarios and logs the results of the testing. The system generates recommendations to revise code of the application based on the outcome of the chaos testing. A large language model may be used to provide documentation and analysis of the chaos testing.

Abstract: A network system to use machine learning systems to create chaos testing scenarios on cloud-based applications. The system uses inputs from applications that are implemented on user computing devices to allow users to interface with a network or other system. The system creates a model of the application based on input data received from a network of applications, the model representing a structure, method, and dependencies of the application. The system identifies points of failure of the application and generates one or more chaos testing simulation scenarios that target the identified points of failure. The system performs the chaos testing based on the received simulation scenarios and logs the results of the testing. The system generates recommendations to revise code of the application based on the outcome of the chaos testing. A large language model may be used to provide documentation and analysis of the chaos testing.

Abstract: A network system to provide testing, resiliency, chaos and performance testing in a single tool that operates on cloud-based applications in real time. When applications are deployed on a cloud environment, the applications must be validated based on functional aspects, performance aspects, resiliency aspects, and test-code coverage ratio aspects. The system combines all these validations in a single package. The system provides a rich set of modules for functional validations, which can be combined as nodes to allow applications to be quickly validated for functionality. The extensible model of the same functional modules may also be used for performance testing. The system also provides resiliency and chaos testing mechanisms that push the applications into a constant state of perturbation. The system does so by detecting the application code and modifying the code at runtime to inject perturbation. The system monitors the recovery of the system from the testing.

Abstract: A platform for customer and prospective customer messaging is provided. The platform generally coordinates message audience selection, message timing, and message content for delivery on any of a variety of communication channels (e.g., email, text message, push notification) for messages from marketing tenants and operational tenants to ensure a coordinated customer experience.

Abstract: A datagrid loading system contains a device including a processor and a memory with a management application installed thereon. The instructions of the management application when executed by the processor cause the processor to accumulate data from a first database, the data configured to be and include an identifier that is particular to the first database, and distribute the data into buckets by an integrated heuristic of the management application, the integrated heuristic and the buckets configured according to database characteristics particular to a second database that is different from the first database, the integrated heuristic further configured to distribute the data based on the identifier.