The detection of idle virtual machines through usage pattern analysis is described. In one example, a computing device can collect utilization metrics from a virtual machine over time. The utilization metrics can be related to one or more processing usage, disk usage, network usage, and memory usage metrics, among others. The utilization metrics can be separated into a set of training metrics and a set of validation metrics, and a number of clusters can be determined based on the set of training metrics. The clusters can be used to organize the set of validation metrics into groups. Depending upon the number or overall percentage of the utilization metrics assigned to individual ones of the plurality of clusters, it is possible to determine whether or not the virtual machine is an idle virtual machine. Once identified, idle virtual machines can be shut down to conserve processing resources and costs.

A method and an apparatus for reducing an effect of local process variations of a digital circuit on a hardware performance monitor includes measuring a set of performance values (c.sub.1, c.sub.2 . . . c.sub.n) of the digital circuit by n identical hardware performance monitors, where n is a natural number greater than 1, determining an average value c.sub.mean of the measured performance values (c.sub.1, c.sub.2 . . . c.sub.n), as an approximation of an ideal performance value c.sub.0, selecting one performance value c.sub.j of the set of performance values (c.sub.1, c.sub.2 . . . c.sub.n) by a controller, comparing the performance value c.sub.j with a reference value c.sub.ref by a controller the controller, resulting in a deviation value Δc, and controlling an actuator by using the deviation Δc for regulating the local global process variations to the approximation c.sub.mean of the ideal performance value c.sub.0.

A method including receiving, from a user device, a user request to access data associated with a web page; generating, by a processor, a first transaction identification; collecting transaction information, the transaction information comprising server-side metrics; integrating, by the processor, the first transaction identification with the transaction information; transmitting, by the processor, the first transaction identification to the user device; receiving, from the user device, client-side data associated with a second transaction identification; integrating, by the processor, the server-side metrics and the client-side data; and analyzing, by the processor, the integrated server-side metrics and the client-side data.

Techniques for optimizing CPU usage in a host system based on VM guest OS power and performance management are provided. In one embodiment, a hypervisor of the host system can capture information from a VM guest OS that pertains to a target power or performance state set by the guest OS for a vCPU of the VM. The hypervisor can then perform, based on the captured information, one or more actions that align usage of host CPU resources by the vCPU with the target power or performance state.

A system and method to receive, from a database service executing on a cloud infrastructure, information indicating metrics regarding backups for the database service, the information including at least an indication of an age of a last complete backup for the database service, an indication of a size of changed data since the last complete backup, and an indication of a number of data units changed since the last complete backup; determine a type of backup strategy to instruct the database service to perform based on the received information, the type of backup strategy being one of a complete backup of the database service, a delta backup of the database service, and no backup of the database service; and issue, in response to the determination, an instruction to the database service to execute the determined type of backup.

In accordance with an embodiment, described herein are systems and methods for providing tiered data storage in cloud infrastructure environments. A data storage service (block store) is adapted to automatically adjust the manner by which the data for a data volume or block volume (data/block volume), associated with a cloud instance, can be stored to meet the requirements of a performance tier. For example, responsive to selection of a particular performance tier, the storage of the data/block volume can be allocated between a first type of data storage associated with a first performance characteristics; and a second type of data storage associated with a second performance characteristics. A graphical user interface enables configuring data/block volumes to use particular performance tiers, and/or to support automatic tuning.

A device receives a time-based restriction for usage by a first user with respect to an application, a website or a device-level function. The device receives encrypted data indicating a usage by the first user on a second device with respect to the application, website or device-level function. The device determines that at least one of the usage by the first user on the second device or a usage by the first user on the device with respect to the application, website or device-level function violates the time-based restriction. The device provides, in response to the determining, a notification that the time-based restriction has been violated by the first user.

Techniques and systems for detecting leakage of computing resources in cloud computing architectures are described. In some implementations, first data may be obtained that indicates usage of a computing resource, such as non-volatile memory, volatile memory, processor cycles, or network resources, by a group of computing devices included in a cloud computing architecture. The first data may be used to determine reference data that may include a distribution of values of usage of the computing resource by the group of computing devices. Second data may also be collected that indicates usage of the computing resource by the group of computing devices during a subsequent time frame. The second data may be evaluated against the reference data to determine whether one or more conditions indicating a leak of the computing resource are satisfied.

Systems, methods, and storage media are provided that are useful in a computing environment for 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.

Method and apparatus for enhancing performance of a storage device, such as a solid-state drive (SSD). In some embodiments, the storage device monitors a rate at which client I/O access commands are received from a client to transfer data with a non-volatile memory (NVM) of the storage device. A ratio of background access commands to the client I/O access commands is adjusted to maintain completion rates of the client I/O access commands at a predetermined level. The background access commands transfer data internally with the NVM to prepare the storage device to service the client I/O access commands, and can include internal reads and writes to carry out garbage collection and metadata map updates. The ratio may be adjusted by identifying a workload type subjected to the storage device by the client.