Methods, apparatus, systems, and articles of manufacture are disclosed that analyze performance of manufacturer independent devices. An example apparatus includes a software development kit (SDK) deployment engine to deploy an SDK to a manufacturer of a device, the SDK to define heartbeat data to be collected from the device and interfacing techniques to transmit the heartbeat data to a measurement entity. In some examples, the apparatus includes a machine learning engine to predict whether the device is associated with one or more failure modes. The example apparatus also includes an alert generator to generate an alert based on a prediction, the alert to indicate at least one of a type of a first one of the failure modes or at least one component of the device to be remedied according to the first one of the one or more failure modes, and transmit the alert to a management agent.

A method is provided for providing mobile device support services. The method may include monitoring a mobile device status. The method may additionally include performing device diagnostics based at least in part on captured device status data to identify potential faults that may affect mobile device functionality. A corresponding system, apparatus, and computer program product are also provided.

Systems, methods, and computer readable storage mediums for performing remote replication including receiving, by a target storage system, an indication that a dataset stored on a source storage system will be replicated to the target storage system; identifying, by the target storage system, portions of the dataset that are not already stored on the target storage system; and initiating, by the target storage system, replication of one or more of the portions of the dataset that are not already stored on the target storage system from a source other than the source storage system.

Embodiments of the present disclosure provide methods and apparatuses for processing at least one activity regarding a physical entity. A method performed by a server includes receiving monitoring data regarding at least one first physical entity from a communication device. The method further includes creating a reference model based on the monitoring data. The method further includes processing at least one activity regarding at least one second physical entity based on the reference model.

Apparatus, device, methods and system relating to a vehicular telemetry environment for identifying in real time unpredictable network communication faults in network zones based upon pre-processed raw telematics big data logs that may include GPS data and an indication of vehicle status data, and supplemental data that may further include location data and network data.

In examples, an electronic device comprises a component, communication port, and a controller coupled to the component and the communication port. The controller is to store operational data of the component during operation of the electronic device. The controller is to provide the operational data to a peripheral device coupled to the electronic device in response to the electronic device establishing a wired connection to the peripheral device via the communication port, the operational data secured by a security credential of the controller. The controller is to receive a repair command from the peripheral device based on the operational data. The controller is to correct a malfunction of the component based on the repair command.

Embodiments of the present disclosure relate to detecting and mitigating errors associated with software pull requests such as software deployment packages. The embodiments include identifying a failure of a pull request, identifying a system error associated with the failure, determining a failure mitigation process based on the failure and the system error, and executing the failure mitigation process to resolve the failure. The errors can be classified as system errors, user errors or planned downtime. The failure mitigation process can include generating an alert associated with the identified system error, updating a status of the pull request, re-evaluating the failure after a predetermined period of time, and retrying deployment of the pull request using an exponential retry process.

A process for analyzing an incident includes setting up an alert for a high error rate on a particular endpoint. Once the alert is triggered, a set of traces for transactions exhibiting errors on the offending endpoint is queried. All traces for other services/operations that include errors on the offending endpoint are also enumerated. A set of baseline transactions that involve the offending endpoint, but do not result in error may be utilized to determine whether the errors are always present, or are distinctive for certain offending transactions. All traces are ranked based on a statistic. Once the traces have been ranked, they may be traced down to a deepest/most terminal error. A set of transactions that correlate to the terminal error may also be analyzed to determine infrastructure causes.

A computing device including: more than two Universal Serial Bus (USB) ports configured to be connected respectively to more than two mobile devices simultaneously; at least one processor coupled to the USB ports; and a memory storing instructions configured to instruct the at least one processor to reprogram, through the more than two USB ports, the more than two mobile devices simultaneously.

Intelligent collection and analysis of in-app failure data is disclosed herein. Upon an application failure in a client device, the client device may collect failure information uniquely identifying a specific failure and provide the failure information to an analysis system. The analysis system may identify a specific failure that identifies the application and a specific portion of the code in the application, based on the failure information and match an action correlated to the specific failure where the action is uniquely designed to resolve the specific failure in the application. The action may include instructions for the client device used to intelligently lead to a resolution of the specific failure. The analysis system may transmit the action to the client device to perform the action and provide any follow up information to the analysis server. The analysis server may use the information to further analyze the specific failure.