A data health monitoring system and method are provided which may be configured to monitor different indicators or parameters of a computing device which may affect the health of the computing device, such as which may be used in looking for early warning signs that could indicate future data loss or corruption. The system may periodically query certain data health indicators, such as S.M.A.R.T. status, disk temperature, read and write errors, etc. The system may also monitor data as it is being accessed keeping track of other indicators such as: files that are modified, when the last backed up was, protection status of the file, type of changes made to the file, which application is making changes, etc. Preferably, the combined status of each data health indicator may be rolled up into a simple message and shown to the user via notifications, reports, logs or a user interface.

A system and method for automated firmware testing. The system includes test stations for testing firmware products. The stations split into pools, with each pool including multiple test stations. The system also includes multiple execution instances, each execution instance for executing tests corresponding to the associated pool. Each of competing test stations delivers a test start event to a corresponding execution instance. The corresponding execution instance receives test start events from the competing test stations, and executes a run test command on a select test station among the competing test stations such that the select test station performs test execution based on a test sequence.

Techniques are described providing improved ways to benchmark and validate virtual desktop deployments where targeted workloads are delivered to virtual desktops based on parameters such as the desktop type and origin, and where workload operations can be triggered from the client device. Client instructions for performing workload operations can be encoded into a digital image such as a Quick Response (QR) code on the virtual desktop and inserted into the virtual desktop graphical user interface (GUI). The client decodes the digital image in the received GUI to obtain the instructions and actuate the operations. Completion of operations can be tracked to benchmark desktop performance.

A method for generating an output for performance impact assessment of a change includes determining changes associated with a first managed computer system where corresponding change records includes a respective change time-stamp, determining performance values for a performance metric for predetermined times and associating respective performance time-stamps, selecting one of the changes wherein the selected change has a change time-stamp, identifying first performance values with performance time-stamps that are prior in time to change time-stamp and associating them with a before-change category, identifying second performance values with performance time-stamps that are later in time relative to the change time-stamp and associating them with an after-change category, and generating an output with the first and second performance values (in a tabular or common timeline format) with the first performance values being distinguishable from the second performance values to thereby allow the user to determine before/after performance impact of the selected change.

Systems and methods for enhancing the representation of outliers in a distribution of telemetry data of a monitored system are provided. According to one embodiment, telemetry data of the monitored system may be continuously collected. Frequency values representing a frequency of occurrence of corresponding telemetry data of the collected telemetry data may be generated by aggregating the collected telemetry data. As the vast majority of telemetry data is expected to represent a normal operating state of the system and relatively few, if any, of the telemetry data (e.g., outliers) will be indicative of one or more events of significance, the resulting distribution of the frequency values is highly skewed. In order to facilitate visualization of the distribution that accentuates the outliers, display characteristics may be calculated for the frequency values by applying a visualization model based on a weighted combination of multiple data transformations to each of the frequency values.

A test environment availability system is disclosed that comprises test servers that include JAVA virtual machines (JVMs), applications executing on the JVMs, and monitoring tools. The system comprises a server including an application that receives a mapping of each function to applications executing on one or more of the test servers that enable an end-to-end journey of the function, obtains operational statuses of the JVMs and the applications on the test servers from the monitoring tools, coalesces each of the operational statuses with a corresponding function based on the mapping to create a coalesced operational statuses mapping, applies a rules set to the coalesced operational statuses mapping, determines whether each function is operational based on the application of the rules set, and creates and provides a dashboard based on the determination that illustrates each function and each function's operational status to an electronic device for display on the electronic device.

Notifications can be managed across ecosystems. A centralized hub can implement a learning engine that uses an algorithm to evaluate incoming notifications that are intended for a user that uses multiple computing devices having different ecosystems. The algorithm can be configured to determine on which of the user's computing devices the notifications should be presented given a particular context. Agents executing on the user's computing devices can monitor how the user interacts with the notifications and provide indications of such interactions to the learning engine. The learning engine can then update its algorithm based on the user's interactions to cause future notifications to be delivered to the user via the ecosystem that is most appropriate for a given context in which each notification is received.

Example implementations include a method of receiving a host command identifier associated with a host command, determining a device command associated with the host command and a memory controller device, receiving a device command timestamp corresponding to a time of the determining the device command, and determining a debug record contemporaneously with the determining the device command, the debug record including the host command identifier, a device command identifier associated with the device command, and the device command timestamp. Example implementations also include a device operably coupled to a memory array, and with a memory controller device configured to receive a host command identifier associated with a host command, and configured to determine a device command associated with the host command and a memory controller device, and a debug record generator device operatively coupled to the memory controller device and configured to receive a device command timestamp corresponding to a time of the determined device command, and configured to determine a debug record contemporaneously with the determining the device command, the debug record including the host command identifier, a device command identifier associated with the device command, and the device command timestamp.

Example bulk device processing systems and methods are described. In one implementation, techniques receive a plurality of application programming interface (API) requests, where each of the plurality of API requests is associated with a particular device. The techniques further sort the plurality of API requests based on an associated carrier. The techniques also create a first batch of API calls associated with devices using a first carrier and create a second batch of API calls associated with devices using a second carrier. The techniques then create multiple threads for parallel execution of the first batch of API calls and the second batch of API calls, and automatically execute the API calls associated with the plurality of threads.

A method of monitoring an operating state of a computing device includes running a system agent on the computing device. An introduced process is executed on the computing device, and a captured parameter relating to at least one of the system agent and the introduced process is captured. The captured parameter is compared to at least one pre-determined parameter. Where the captured parameter differs from the pre-determined parameter by more than a pre-determined threshold, a signal indicative of a change in operating state of the computing device is output.