Systems and methods facilitating selection of computer system deployments to mock for testing are described herein. A method as described herein can include filtering, by a first system operatively coupled to a processor, data relating to deployments of respective second systems as collected from the respective second systems, wherein the filtering is based on relevancy of the deployments to a testing criterion and results in a filtered group of deployments; grouping, by the first system, respective ones of the filtered group of deployments into respective clusters according to a difference function, the difference function being defined according to respective properties of the respective ones of the filtered group of deployments; and designating, by the first system, selected ones of the filtered group of deployments from respective ones of the clusters for testing according to a selection criterion.

Various examples are provided related to cache miss classification. In one example, a method for classification of cache misses includes detecting a susceptible instruction of a program with frequent cache misses based upon performance monitoring units (PMU) based course grain sampling; collecting a memory access pattern of the susceptible instruction using breakpoint-based fine-grain sampling; and classifying a type of cache miss associated with the susceptible instruction. The type of cache miss can be classified as a capacity miss, a conflict miss, or a coherence miss using the memory access pattern of the susceptible instruction.

An information processing apparatus includes a processor configured to: acquire signature information indicating whether an application program installed on the information processing apparatus is signed or not; and with the signature information indicating that the application program is not signed, transmit log information indicating an operation log of the application program to an external apparatus.

A method, an electronic device, and a program product for determining a score of a log file are provided. The method includes acquiring a log file related to a monitored system and source code corresponding to the log file. The method may further include determining a first score of the log file based on a first log rule subset in a log rule set, the log rule set being used to evaluate at least one of analyzability of the log file and supportability of the monitored system. The method may further include determining a second score of the source code based on a second log rule subset in the log rule set and determining a third score of the log file at least based on the first score and the second score.

Methods and systems for managing deployments are disclosed. A deployment may include one or more devices. The devices may include hardware and/or software components. The operation of the deployment may depend on the operation of these devices and components. To manage the operation of the deployment, a system may include a deployment manager. The deployment manager may obtain logs for components of the deployment reflecting the historical operation of these components and use the log to predict the future operation of the deployment. Based on the predictions, the deployment manager may take proactive action to reduce the likelihood of the deployment becoming impaired.

An apparatus includes operational circuitry and Hardware Diagnostics Circuitry (HDC). The HDC is configured to receive a definition of multiple trigger rules, each trigger rule specifying a respective trigger event as a function of trigger data sources in the operational circuitry, to receive a definition of (i) a pre-trigger logging set selected from among a plurality of diagnostics data sources in the operational circuitry, and (ii) for each trigger rule, a respective post-trigger logging set including a set of one or more of the diagnostics data sources, and, during operation of the operational circuitry, to log the diagnostics data sources in the pre-trigger logging set, to log the trigger data sources and to repeatedly evaluate the trigger rules, and, in response to triggering of a given trigger event by a given trigger rule, to start logging the diagnostics data sources in the post-trigger logging set of the given trigger rule.

A method for handling an anomaly of data, in particular in a motor vehicle. At least one sensor obtains data for the anomaly detection. The sensor examines the obtained data for anomalies, and generates an event as a function of the associated data when an anomaly is detected. It is decided whether the event is further processed, in particular stored and/or further communicated, at least in part.

The computerized method is shown and includes obtaining input at a local electronic device, generating a first result by processing the input according to a first rule set, wherein the first result provides a current status or a predicted status of the electronic device and transmitting the first result or indicia thereof to a remote server computer system. The computerized method additionally includes receiving a communication from the remote server computer system, wherein the communication includes an instruction to enable a second rule set, responsive to receiving the communication, enabling the second rule set, obtaining subsequent input at the local electronic device, and processing the subsequent input according to the second rule set. The computerized method may further include performing a statistical analysis on the input, and generating a predicated status of the electronic device based on an extrapolation process using a result of the statistical analysis.

An aspect of the present disclosure provides a relevance ranking system for events identified by performance management systems. In one embodiment, a system receives, from one or more performance management systems, events associated with performance metrics and determines, based on the received events, a corresponding relevance score for each performance metric. The system generates a ranking list of the received events based on the corresponding relevance scores (determined for the performance metrics). The system then provides the ranking list of events to a user (such as an administrator). According to another aspect, the system (noted above) performs the steps of receiving, determining, and generating for each time interval of a set of time intervals.

System and computer-implemented method for managing multi-availability zone (AZ) clusters of host computers in a cloud computing environment automatically detects a degraded state of a first AZ in the cloud computing environment based on host failure events for host computers in a first cluster section of a multi-AZ cluster of host computers located in the first AZ and a recovered state of the first AZ based a successful scale-in operation of another multi-AZ cluster located partially in the first AZ. In response to the detection of the degraded state of the first AZ, a second cluster section of the multi-AZ cluster of host computers located in a second AZ is scaled out. In response to the detection of the recovered state of the first AZ, the second cluster section of the multi-AZ cluster of host computers located in the second AZ is scaled in.