An example system and method facilitates operation of a networked software application that communicates with a network resource during periods of intermittent network connectivity and includes determining when a networked software application is offline and when it is online; selectively intercepting one or more request messages from the networked software application addressed to a network resource when the software application is offline, resulting in a store of intercepted request messages; detecting when the networked software application transitions from being offline to being online; and selectively issuing the one or more request messages to the network resource in a sequence in which the one or more request messages were stored in the store of intercepted request messages. In a more specific embodiment, the system is implemented via an offline toolkit for capturing REpresentational State Transfer (REST) calls when the networked software application (client) is offline; then selectively replaying the calls when the client reconnects, i.e., goes online.

Provided are a method and apparatus for transferring an edge computing application. The method includes: receiving, by a first edge computing application of a first edge computing host, a first message sent by an edge computing platform of the first edge computing host, where the first message includes edge computing application information of a second edge computing host; and sending, by the first edge computing application, a second message to a second edge computing application of the second edge computing host according to the edge computing application information of the second edge computing host, where the second message carries user context information.

A partitioned virtual space supports logical networking of IoT devices. Agents of the devices are assigned to interest-based cells in a virtual space, and can travel among the cells. Within the cells, pairs of devices are tested for similarity, based on device profiles, and for detected affinity. Agents of devices having affinity are connected in a logical network. Some attributes can be based on a personality model and can reflect the personality of a user or other principal associated with a device. Such attributes can influence requests for affinity testing, calculation of similarity, and further behavioral effects incorporated in affinity determination. Evaluation of recommendations can lead to updating of similarity scores or changes in affinity determination. Disclosed embodiments provide scalable, distributed, autonomous, and unsupervised device-to-device connectivity, free of prior constraints. Embodiments can be implemented in the cloud, with privacy protection.

An example of an apparatus including a memory storage unit to store telemetry data collected from a plurality of sources, wherein each source of the plurality of sources maintains confidentiality. The apparatus further includes an anonymizing engine to remove identifying information from the telemetry data to generate anonymized data. The apparatus also includes a communication interface to receive request from a client device for an upgrade. The request includes a requesting device configuration of the client device. The apparatus also includes a selection engine to select a subset of the anonymized data based on the requesting device configuration. Furthermore, the apparatus includes a comparison engine to analyze the subset of the anonymized data to determine a probability of an upgrade failure at the client device. Additionally, the apparatus includes an upgrade engine to implement the upgrade on the client device based on the probability.

A method, system and computer-readable storage medium for performing a cognitive information processing operation. The cognitive information processing operation includes: receiving data from a plurality of data sources; processing the data from the plurality of data sources to provide cognitively processed insights via an augmented intelligence system, the augmented intelligence system executing on a hardware processor of an information processing system, the augmented intelligence system and the information processing system providing a cognitive computing function; performing a robustness assessment operation, the robustness assessment operation assessing robustness of the cognitive computing function, the robustness assessment operation generating a robustness score representing robustness of the cognitive computing function; and, providing the cognitively processed insights to a destination, the destination comprising a cognitive application, the cognitive application enabling a user to interact with the cognitive insights.

A computer system for verifying vehicle software configuration may be provided. The computer system may include a processor and a non-transitory, tangible, computer-readable storage medium having instructions stored thereon that, in response to execution by the processor, cause the processor to: (1) transmit, to a vehicle computing system, an authentication request including a hash algorithm specification; (2) receive, from the vehicle computing system, a current configuration hash value and a vehicle identifier; (3) retrieve a trusted data block from a memory based upon the vehicle identifier, the trusted data block including a stored configuration hash value and a smart contract code segment; (4) execute the smart contract code segment, the smart contract code segment including a failsafe code segment; and/or (5) transmit the authentication response to the vehicle computing system, and cause the vehicle computing system to execute the failsafe code segment.

A system includes a plurality of containers and a plurality of controllers. Each of the controllers are associated with a respective one of the plurality of containers. An unmanned aerial vehicle is configured for wireless communication with the plurality of controllers.

A multi-cloud service mesh orchestration platform can receive a request to deploy an application as a service mesh application. The platform can tag the application with governance information (e.g., TCO, SLA, provisioning, deployment, and operational criteria). The platform can partition the application into its constituent components, and tag each component with individual governance information. For first time steps, the platform can select and perform a first set of actions for deploying each component to obtain individual rewards, state transitions, and expected returns. The platform can determine a reinforcement learning policy for each component that maximizes a total reward for the application based on the individual rewards, state transitions, and expected returns of each first set of actions selected and performed for each component. For second time steps, the platform can select and perform a second set of actions for each component based on the reinforcement learning policy for the component.

A method for configuring multiple electronic devices in a batch, is described. The method can include initializing, by a first computing device a communication network based on a pre-defined configuration parameter. The pre-defined configuration parameter is associated with a first instance of an application on the first computing device. Further, the method includes identifying, by the first computing device, an initialization of a second instance of an application at a second computing device. In response to identifying the initialization of the second instance of the application at the second computing device, the method includes, sending, by the first computing device configuration settings for the second computing device over a secured communication network. In this regard, the configuration settings can comprise at least the pre-defined configuration parameter for configuring the second computing device.

Embodiments of the present disclosure relate to systems, methods, and user interfaces that automate the workflow testing process. Users can configure, automate and execute repeating workflow tests associated with software updates or upgrades. In doing so, issues with the updates or upgrades are proactively prevented. To do so, a selection of one or more business processes is initially received. The one or more business processes are combined into a client workflow. Test data and assertion types are received for each business process of the one or more business processes. A script and metadata containing the client workflow name and the one or more business process names utilized to create the client workflow is stored and the client workflow can be executed in a target environment. Any errors in the client workflow are detected and a notification is provided to a user for follow-up and resolution.