Noisy-neighbor detection and remediation is provided by performing real-time monitoring of workload processing and associated resource consumption of application components that use shared resource(s) of a computing environment, determining workload and shared resource consumption patterns for each of the application components, for each application, of a plurality of applications, that includes at least one application component of the application components, correlating the determined workload and shared resource consumption patterns of each of those application component(s) and determining a correlated shared resource usage pattern for that application, performing impact analysis to determine impact of the applications on each other, and identifying noisy-neighbor(s) that use the one or more shared resources and automatically raising an alert indicating those noisy-neighbor(s).

A self-managing database system includes a metrics collector to collect metrics data from one or more databases of a computing system and an anomaly detector to analyze the metrics data and detect one or more anomalies. The system includes a causal inference engine to mark one or more nodes in a knowledge representation corresponding to the metrics data for the one or more anomalies and to determine a root cause with a highest probability of causing the one or more anomalies using the knowledge representation. The system includes a self-healing engine, to take at least one remedial action for the one or more databases in response to determination of the root cause.

A method may include receiving, via a first computing node, a first pod from a second computing node. The method may also include retrieving a first image file that may include a first set of containers from a registry based on the first pod. The first set of containers may cause a control system to halt operations. The method may then involve generating a first package based on the first set of containers and storing the first package in a filesystem, receiving a second pod from the second computing node, and retrieving a second image file having a second set of containers from the registry. The second pod may include the second set of containers may cause the control system to update software components. The method may also involve generating a second package based on the second set of containers and storing the second package in the filesystem.

Example aspects include techniques for accurate and expeditious cloud service health communication to customers. These techniques may include determining that a service health incident has customer impact, the service health incident corresponding to an outage of one or more services of a cloud computing platform, identifying a plurality of customers impacted by the service health incident, and predicting, based on the service health incident and one or more other service health incidents, aggregated incident information identifying a plurality of service health incidents associated with the outage of the one or more services. In addition, the techniques may include identifying the one or more services associated with the service health incident, and transmitting, based at least in part on the aggregated incident information and the one or more services, a health notification to the plurality of customers.

Configurations for data center component monitoring are disclosed. In at least one embodiment, movement of a server component is determined based on sensor data and the movement is used to diagnose a root cause for a server component failure.

Aspects of the disclosure relate to automated error processing. A computing platform may receive historical error/solution information. The computing platform may train, using the historical error/solution information, an artificial intelligence engine to automatically identify solutions for current errors for a plurality of users. The computing platform may identify current errors for a user of the plurality of users. The computing platform may notify the user of the current errors. The computing platform may receive a request to correct an error of the one or more current errors. The computing platform may identify, using the artificial intelligence engine, a solution to the error. The computing platform may automatically perform actions to achieve the solution. The computing platform may send, after performing the actions, commands directing an event processing system to process an event with which the error was associated, which may cause the event processing system to process the event.

A system and method for allowing an assignee to rapidly collect data about a bug/error that is associated with the execution of a software application on a computing device. The method includes including receiving, from a client device, a request to resolve an error associated with an execution of an application on a remote server. The request includes configuration information for connecting to the remote server and an identifier to a component of the application. The method includes determining one or more files associated with the component of the application. The method includes establishing a connection to the remote server using the configuration information. The method includes retrieving the one or more files from the remote server via the connection. The method includes granting, to an assignee device, access to the one or more files that were retrieved from the remote server.

An analytics server receives from client computing devices end-user events. Each client computing device is operated by an end-user to access an application at a web server based on the end-user events resulting in calls being passed through a proxy to the web server. The analytics server receives from the proxy the calls being made to the web server, and receives return responses from the web server being passed through the proxy. The return responses correspond to activities being performed within the application. The end-user events are correlated with the corresponding calls and return responses from the proxy. Respective correlated end-user events, calls and return responses are translated into respective event vectors. The respective event vectors are processed to determine similarities among the client computing devices. The similar activities are associated with a quality indicator to identify anomalies within the application for corrective action to be taken.

Provided is an anomaly pattern detection system including an anomaly detection device connected to one or more servers. The anomaly detection device may include an anomaly detector configured to model input data by considering all of the input data as normal patterns, and detect an anomaly pattern from the input data based on the modeling result.

Embodiments of the disclosed technology concern transforming a high-level quantum-computer program to one or more symbolic expressions. Because the transformations lead to symbolic expressions in the compiled code, one can extract these to arrive at symbolic resource estimates for the quantum program. In cases where these transformations do not yield closed-form solutions, they can still be evaluated many orders of magnitude faster than it was possible using other resource estimation tools. Having access to such symbolic or near-symbolic expressions not only greatly improves the performance of accuracy management and resource estimation, but also better informs quantum software developers of the bottlenecks that may be present in the quantum program. In turn, the underlying quantum-computer program can be improved as appropriate.