An information processing apparatus includes one or more managers that manage one or more virtual environments, and a management controller that controls the one or more managers. When the execution of the software is detected in any of the one or more virtual environments, the management controller instructs the manager that manages the detected virtual environment to determine whether to execute the software in the detected virtual environment. The manager reads a file stored in the detected virtual environment, and determines whether to execute the software in the detected virtual environment based on information indicated in the file.

In accordance with an embodiment, described herein is a system and method for use in a distributed computing environment, for automatically scaling a cluster based on metrics being monitored. A cluster that comprises a plurality of nodes or brokers and supports one or more colocated partitions across the nodes, can be associated with an exporter process and alert manager that monitors metrics associated with the cluster. Various metrics can be associated with user-configured alerts that trigger or otherwise indicate the cluster should be scaled. When a particular alert is raised, a callback handler associated with the cluster, for example an operator, can automatically bring up one or more new nodes, that are added to the cluster, and then reassign a selection of existing colocated partitions to the new nodes/brokers, such that computational load can be distributed within the newly-scaled cluster environment.

A system includes a processor in communication with a memory, a virtual machine running on the processor, and an application executing within the virtual machine. The virtual machine is associated with at least one testing tool configured to transform a plurality of application classes of the application, such that each respective class of the plurality of application classes is configured to track its respective usage. The testing tool is further configured to test the application with a plurality of tests, and while testing the application, map which respective classes of the plurality of application classes are used by respective tests. Additionally, the testing tool is configured to determine which class(es) is used by which tests (e.g., a subset of tests). Responsive to a first class being modified, the testing tool is configured to retest the application with the subset of tests.

Virtual servers are monitored in real-time. A group of virtual servers from virtual server events occurring within a time window is identified by a computer system in real-time. A metric is determined for the group of virtual servers by the computer system in real-time using the virtual server events occurring within the time window for the group of virtual servers. A set of actions is performed by the computer system using the metric.

Embodiments herein provide an analytics-based solution for recommending for the initial placement of one or more virtual desktop (VD) users in a multi-cloud environment and/or for the subsequent migration of one or more users in a multi-cloud environment. In one or more embodiments, a placement (initial or migratory) recommendation may be based one or more metrics related to the cloud deployment and user conditions/requirements. In one or more embodiments, a placement recommendation is based on assessing functionality requirements of a user or users and a correlation analysis with other functionality or functionalities as it relates to functionality that is available at specific cloud deployments. In one or more embodiments, the recommendation may alternatively or additionally be based upon latency analytics, in which end-to-end latency from the user to an application or applications may be considered as metric(s) in the recommendation determination.

A virtualized system is provided. The virtualized system includes: a memory device; a processor configured to provide a virtualization environment; a direct memory access device configured to perform a function of direct memory access to the memory device; and a memory management circuit configured to manage a core access of the processor to the memory device and a direct access of the direct memory access device to the memory device. The processor is further configured to provide: a plurality of guest operating systems that run independently from each other on a plurality of virtual machines of the virtualization environment; and a hypervisor configured to control the plurality of virtual machines in the virtualization environment and control the memory management circuit to block the direct access when a target guest operating system controlling the direct memory access device, among the plurality of guest operating systems is rebooted.

A method, system, and computer program product for implementing container runtime optimization and execution is provided. The method includes enabling a container management instance and a container runtime comprising specified operational attributes associated with a container. Supervisor tree code is embedded within the container runtime and definition software is executed. The definition software describes specified digital endpoints of an associated application process being executed by the container. The container is enabled for operational functionality and an external interface is enabled for communications with the supervisor tree code. The container management instance is executed in response to a command received via the external interface.

Systems, methods, and machine-storage medium for classifying snapshot image processing are described. The system receives read requests to read snapshot information. Each read request includes an offset identifying a storage location and a length. The snapshot information includes snapshots including a full snapshot and at least one incremental snapshot. The read requests include a first read request to read data from the snapshot information. The system generates a first plurality of read events including a second plurality of read events that are generated by processing the first read request. The second plurality of read events includes first and a second read events. The system identifies whether utilizing a cache optimizes the job based on the first plurality of read events.

Methods, apparatus, systems and articles of manufacture are disclosed to detect drift in a hybrid cloud environment. An example apparatus to detect drift in a hybrid cloud environment includes a configuration model determiner to, after deployment of a blueprint in the hybrid cloud environment, generate a first model including first relationships of a first plurality of resources corresponding to the blueprint, the blueprint including a plurality of properties in which at least one of the plurality of properties is agnostic of type of cloud, an inventor model determiner to generate a second model including second relationships of a second plurality of resources as deployed in the hybrid cloud environment based on the blueprint, and a drift determiner to determine a drift value based on the first relationships and the second relationships, the drift value representative of a difference between the first relationships and the second relationships.

A charge calculation method executed by a processor included in a computer to execute a process, the process includes determining a degree of possibility that a virtual machine having redundant configuration exists in a plurality of virtual machines that provide a service, calculating a difference of charges for using the service before and after a first virtual machine among the plurality of virtual machines is migrated to an another location different from a location where the first virtual machine is located, and displaying the degree of possibility and the difference with respect to the service.