Requests for computing resources and other resources can be predicted and managed. For example, a system can determine a baseline prediction indicating a number of requests for an object over a future time-period. The system can then execute a first model to generate a first set of values based on seasonality in the baseline prediction, a second model to generate a second set of values based on short-term trends in the baseline prediction, and a third model to generate a third set of values based on the baseline prediction. The system can select a most accurate model from among the three models and generate an output prediction by applying the set of values output by the most accurate model to the baseline prediction. Based on the output prediction, the system can cause an adjustment to be made to a provisioning process for the object.

The disclosure provides an approach for measuring performance between a virtualized desktop infrastructure (VDI) client running on a client device and a remote computing device. Embodiments include generating, by a performance client on the client device, an event and storing a time associated with generating the event. Embodiments include transmitting, by the VDI client to the remote computing device, a message based on the OS event. Embodiments include determining, by a performance agent on the remote computing device, a time associated with receiving the message at the remote computing device and causing an indication of the time to be displayed in a virtual desktop screen. Embodiments include extracting, by the performance client, from the virtual desktop screen, the time, and determining a performance metric based on the extracted time and the time associated with receiving the message at the remote computing device.

In an approach for generating differentiated workload telemetry data, a processor corresponds one or more services with a workload related telemetry generating an event emitter. A processor performs a correlation analysis of corresponding relationship and connection among connected resources and current traffic into and out of the one or more services. A processor labels domain context for each telemetry event. A processor communicates each telemetry event to a global event handler. A processor performs a cross-correlation in real-time of telemetry data with the global event handler. A processor updates a real-time differentiated workload report.

An interface receives reported information from a system on chip (SOC), where the reported information includes: (1) hardware-reported information that is reported by a hardware functional module included in the SOC and (2) firmware-reported information that is reported by a firmware functional module included in the SOC. A processor receives one or more display settings and generates visual information based at least in part on: (1) the one or more display settings, (2) the hardware-reported information, and (3) the firmware-reported information. The visual information is displayed via a display.

Techniques for determining insight are described. An exemplary method includes receiving a request to provide insight into potential abnormal behavior; receiving one or more of anomaly information and event information associated with the potential abnormal behavior; evaluating the received one or more of the anomaly information and event information associated with the abnormal behavior to determine there is insight as to what is causing the potential abnormal behavior and to add to an insight at least two of an indication of a metric involved in the abnormal behavior, a severity for the insight indication, an indication of a relevant event involved in the abnormal behavior, and a recommendation on how to cure the potential abnormal behavior; and providing an insight indication for the generated insight.

An illustrative method includes detecting, by a cloud based storage system services provider based on a problem signature, that a storage system has experienced a problem that is associated with the problem signature; and deploying, without user intervention, one or more corrective measures that modify the storage system to resolve the problem.

Embodiments disclosed herein provide for monitoring performance of a processing device to manage non-precise events. A processing device includes a performance counter to track a non-precise event and to increment upon occurrence of the non-precise event, wherein the non-precise event comprises a first type of performance event that is not linked to an instruction in an instruction trace. The processing device also includes a first handler circuit to generate and store a first record, the first record comprising architectural metadata defining a state of the processing device at a time of generation of the first record, wherein the first handler circuit to generate records corresponding to precise events. The processing device further includes a second handler circuit communicably coupled to the first handler circuit, the second handler circuit to cause the first handler circuit to generate a second record for the non-precise event upon overflow of the performance counter.

In accordance with embodiments disclosed herein, there is provided systems and methods for monitoring performance of a processor to manage events. A processor includes a first performance counter to increment upon occurrence of a first type of event in the processor and a second performance counter to increment upon occurrence of a second type of event in the processor. The processor is to reset the second performance counter in response to the first performance counter reaching a first limit.

An instrumentation analysis system processes data streams by executing instructions specified using a data stream language program. The data stream language allows users to specify a search condition using a find block for identifying the set of data streams processed by the data stream language program. The set of identified data streams may change dynamically. The data stream language allows users to group data streams into sets of data streams based on distinct values of one or more metadata attributes associated with the input data streams. The data stream language allows users to specify a threshold block for determining whether data values of input data streams are outside boundaries specified using low/high thresholds. The elements of the set of data streams input to the threshold block can dynamically change. The low/high threshold values can be specified as data streams and can dynamically change.

An aspect of behavior of an embedded system may be determined by (a) determining a baseline behavior of the embedded system from a sequence of patterns in real-time digital measurements extracted from the embedded system; (b) extracting, while the embedded system is operating, real-time digital measurements from the embedded system; (c) extracting features from the real-time digital measurements extracted from the embedded system while the embedded system was operating; and (d) determining the aspect of the behavior of the embedded system by analyzing the extracted features with respect to features of the baseline behavior determined.