Provided is a non-transitory computer-readable recording medium storing an aggregation program causing a computer to execute a process, the process including determining, plural times within a first period of time, whether a first function, which puts a processor into a sleep state, is being executed among functions written in a program being executed by the processor, identifying a second function that is performing either input or output processing among the functions when it is determined that the first function is being executed, and aggregating a number of times that the second function is identified within the first period of time.

Provided is a management system for managing a relation between a database and a volume without installing an agent. A management system manages a relation between a data catalog and a volume of a storage system storing data to be used by the data catalog. A processor of the management system accesses data that is included in the data catalog and that includes authentication information of the volume; detects the number of accesses to the volume in a time range including a timing of the access to the data; and manages the relation between the data catalog and the volume on the basis of the number of accesses.

The present disclosure relates to implementing, updating, and managing operation of a client agent on a client device (e.g., computing device, virtual device) in a way that enables isolation of features and functionality while also allowing the client agent to self-heal and intelligently update discrete features thereon. The client agent includes a collection of plugins that are isolated and run in accordance with respective plugin policies. The client agent makes use of device-level, agent-level, and plugin-level health monitors that collectively monitor a health status of discrete components of the client agent in a way that enables the client agent to selectively discontinue scheduling certain plugins without interrupting functionality of other plugins or of the client agent as a whole. Indeed, features described herein enable the client agent to intelligently update and self-heal with respect to individual plugins based on information obtained by the respective health monitors.

Methods, systems, and devices for persistent health monitoring for volatile memory devices are described. A memory device may determine that an operating condition associated with an array of memory cells on the device, such as a temperature, current, voltage, or other metric of health status is outside of a range associated with a risk of device degradation. The memory device may monitor a duration over which the operating condition is outside of the range, and may determine whether the duration satisfies a threshold. In some cases, the memory device may store an indication of when (e.g., each time) the duration satisfied the threshold. The memory device may store the one or more indications in one or more non-volatile storage elements, such as fuses, which may enable the memory device to maintain a persistent indication of a cumulative duration over which the memory device is operated with operating conditions outside of the range.

A system is described herein for mitigating slow process instances in a streaming application. The system includes a slow process instance candidate identifier configured to identify, based on a relative watermark latency, a set of slow process instance candidates from among a plurality of process instances that comprise the streaming application. The system further includes a set of filters configured to remove false positives from the set of slow process instance candidates. The filters account for window operations performed by the process instances as well as stabilization time needed for downstream process instances to stabilize after a slow upstream process instance is mitigated by a mitigation implementer, which may also be included in the system.

System and method for merging and aggregation of workflow processes by recording a series of screen captures in real-time that can assist in capturing the steps for completing the business workflow process across one or more business applications in a workflow data file. The workflow data file includes a graphical representation of the steps in a sequential order for performing the business workflow process. The workflow data file is compatible with a workflow application.

Systems, devices, media, and methods are presented for releasing an application feature in incremental stages while monitoring the application for anomalies. The feature includes a package of code and an action setting. The methods in some implementations include identifying active devices on which the application has been installed, monitoring the application according to a set of metrics, activating the feature by changing its action setting for a first segment of the active devices, pausing the feature if an anomaly is detected among the set of metrics, and generating a repair ticket. As long as no anomaly is detected, the activating step proceeds for subsequent segments of the active devices, iteratively, until the release is completed. A feature rank may be used to process and release a plurality of features in order of priority.

Systems, methods, and storage media provided are useful in a computing environment receiving, modifying, and transforming service level information from database servers and entities in a hosted database environment. Multiple application programming interface (API) calls are made by a database observation system to request information for multiple service level indicators from database servers belonging to multiple different entities. Database observation system receives and aggregates the information for multiple service level indicators from each of the database servers belonging to multiple different entities. The database observation system provides, within a dashboard interface, the aggregated information for each of the multiple service level indicators, individual service level indicator scores, and aggregated service level indicator scores for each of the database servers for each of the multiple entities.

Examples of electronic devices are described herein. In some examples, an electronic device may include a communication interface to receive information from a peripheral device. In some examples, the electronic device may include logic circuitry to determine a target latency tolerance reporting (LTR) value based on the information via a machine learning model.

A system is described herein for mitigating slow process instances in a streaming application. The system includes a slow process instance candidate identifier configured to identify, based on a relative watermark latency, a set of slow process instance candidates from among a plurality of process instances that comprise the streaming application. The system further includes a set of filters configured to remove false positives from the set of slow process instance candidates. The filters account for window operations performed by the process instances as well as stabilization time needed for downstream process instances to stabilize after a slow upstream process instance is mitigated by a mitigation implementer, which may also be included in the system.