A system and method may analyze computer actions on a computer desktop system. Using a data gathering process, a low-level user action information item, describing input by a user (e.g. to the computer desktop system), may be received or gathered. The low-level user action information item may include an input type description and screen window information. Based on a series of low-level user action information items, a process a computer is engaging in with the user may be estimated or determined. The best or most appropriate next low-level user action may be displayed or suggested to the user, e.g. on a computer desktop system to a user.

Various embodiments include a method for determining a collection frequency of data. The data are collected from a device for an application program to monitor the device. The method may include: determining a collection frequency requirement of the application program regarding the data of the device; determining state information of the device; and determining, based on the determined collection frequency requirement of the application program regarding the data of the device and the determined state information of the device, a collection frequency of data according to a preset rule.

Embodiments relate to a computer platform to support processing of informational logs and corresponding performance data to detect and mitigate occurrence of anomalous behavior. Metrics are extracted from the informational logs and correlated with performance data, and in an exemplary embodiment golden signal metrics. A window or block of the logs is classified as potential candidates or indicators of anomalous behavior, which in an embodiment is indicative of potential failure or service outage. A control signal is dynamically issued to an operatively coupled device associated with the window or block of logs. The control signal is configured to selectively control a state of a physical device or process controlled by software, with the control directed at mitigating or eliminating the effect(s) of the anomalous behavior.

Systems, devices or methods provide for control of sensitive data in a computer system that includes at least one central server communicatively-coupled to a plurality of client computers. A particular method relates to the execution of software code on the at least one central server to monitor data communications of the plurality of client computers for sensitive data. A subset of the data communications is restricted when sensitive data is detected. Configuration data is provided to each of the plurality of client computers. Software code is executed on each of the plurality of client computers to detect accesses to sensitive data by one or more applications running on a client computer. Actions of the one or more applications running on a client computer are monitored to determine whether or not a trigger event has occurred. In response to determining that the trigger event has occurred, a notification is sent.

Various embodiments relate generally to data science and data analysis, computer software and systems, and control systems to provide a platform to facilitate implementation of an interface, and, more specifically, to a computing and data storage platform that implements specialized logic to optimize effectiveness of content in electronic messages as a function, for example, modifiable portions of the content. In some examples, a method may include publishing a first electronic message including data representing a subset of components of electronic message, identifying a performance criterion against which a performance metric may be monitored, monitoring a value of the performance metric, determining a match, and publishing a second electronic message.

The disclosed embodiments disclose techniques for journaling data received in a cloud-based distributed computing environment (CBDCE). Multiple services simultaneously execute on the CBDCE compute nodes, with each service comprising multiple service instances that simultaneously execute on multiple, distinct compute nodes of the CBDCE. The CBDCE includes a distributed database that enables coordination between the service instances of services that execute in the CBDCE; this distributed database also includes multiple distributed database instances that simultaneously executing on multiple different CBDCE compute nodes. During operation, a service instance executing on one of these compute nodes receives a client request. The service instance submits this client request to a distributed database instance and, in parallel, also submits the client request and its associated user data to a distributed journaling service.

An embodiment of an electronic apparatus may include one or more substrates, and logic coupled to the one or more substrates, the logic to determine a set of requirements for a persistent storage media based on input from an agent, dedicate one or more banks of the persistent storage media to the agent based on the set of requirements, and configure at least one of the dedicated one or more banks of the persistent storage media at a program mode width which is narrower than a native maximum program mode width for the persistent storage media. Other embodiments are disclosed and claimed.

The technology described herein is directed towards determining a datacenter's power consumption of its devices at the workload level, from which an objective carbon footprint impact score can be determined. Devices can include servers, network devices such as switches, and storage devices. For a group of workloads at a location, workload power consumption values can be determined based on collected power-related workload metrics data. The power consumption values are used in determining per-workload carbon footprint values for the workloads based on the location. One or more actions can be taken to modify the respective carbon footprint values, e.g., moving a workload to a different location, changing device hardware, and so on.

Disclosed herein are system, apparatus, article of manufacture, method, and/or computer program product embodiments for monitoring long-standing computing resources. An apparatus may operate by receiving a cloud monitoring notification, where the cloud monitoring notification may indicate an occurrence of a monitored condition. The apparatus may then operate by scanning a cluster computing system for resource having a client assigned resource identifier and a computing resource attribute based on a resource identifier scan parameter and a resource attribute scan parameter. The apparatus may further operate by generating a resource notification request based on the scanning of the cluster computing system and transmitting the resource notification request to a communications system to notify a user that the resource has a computing resource attribute that match the resource attribute scan parameter.

Replicated instances in a database environment provide for automatic failover and recovery. A monitoring component can periodically communicate with a primary and a secondary replica for an instance, with each capable of residing in a separate data zone or geographic location to provide a level of reliability and availability. A database running on the primary instance can have information synchronously replicated to the secondary replica at a block level, such that the primary and secondary replicas are in sync. In the event that the monitoring component is not able to communicate with one of the replicas, the monitoring component can attempt to determine whether those replicas can communicate with each other, as well as whether the replicas have the same data generation version. Depending on the state information, the monitoring component can automatically perform a recovery operation, such as to failover to the secondary replica or perform secondary replica recovery.