Abstract: A processing device receives a starting cluster layout for a first cluster, a target cluster layout for the first cluster, and a cluster management operation for creating or modifying the first cluster. The processing device determines a plurality of node level tasks to transition the first cluster from the starting cluster layout to the target cluster layout, determines dependencies between the plurality of node level tasks, and determines an order for the plurality of node level tasks based on the cluster management operation and the dependencies. The processing device then creates an execution plan that divides the cluster management operation into the plurality of node level tasks in the determined order.

Abstract: A scale-out method includes: upon detecting that a processing load of a first virtual machine among one or plural virtual machines exceeds a threshold, deploying a second virtual machine that is a new virtual machine; selecting a process that satisfies a predetermined condition based on processing loads of plural processes operating in the first virtual machine; first specifying first information for identifying first software related to selected process; and setting up the first software on the second virtual machine based on the first information.

Abstract: Techniques and mechanisms provide a flexible mapping for physical functions and virtual functions in an environment including virtual machines.

Abstract: An apparatus comprises at least one processing platform implemented using at least one processing device comprising a processor coupled to a memory. The processing platform comprises virtualization infrastructure, an assurance layer and an analytic layer. The assurance and analytic layers are configured to provide data collection and event management functionality to support automation relating to resources of the virtualization infrastructure and associated workloads. By way of example, the assurance and analytic layers illustratively comprise respective deterministic and indeterministic functional groupings of components. The functional groupings of components of the assurance and analytic layers are utilized to implement closed-loop remediation workflows and other types of automation relating to the virtualization infrastructure resources and their associated workloads.

Abstract: A specification of resource requirements is received. One or more resource configurations for a computing environment that satisfy the specification of resource requirements are generated utilizing a description of available resources in the computing environment. A model is utilized to estimate a level of service for each of the resource configurations, wherein the model predicts behavioral dependencies between attributes of the resources in the computing environment. A given one of the resource configurations is selected based at least in part on the estimated levels of service, and resources in the computing environment are assigned according to the selected configuration of resources.

Abstract: A method for scheduling tasks with deadline constraints, based on a model of independent periodic tasks and carried out in the user space by means of API POSIX is provided.

Abstract: Systems, apparatuses, and methods for classification based automated instance management are disclosed. Classification based automated instance management may include automatically commissioning an application instance based on a plurality of classification metrics, and automatically monitoring the application instance based on the plurality of classification metrics. Automatically monitoring the application instance may include identifying a plurality of instance monitoring policies associated with the application instance based on the plurality of classification metrics. Automatically monitoring the application instance may include automatically suspending the application instance plurality of instance monitoring policies and automatically decommissioning the application based on the plurality of instance monitoring policies.

Abstract: Plural virtual machines are executed by plural information processing devices coupled to each other via a network and connected to plural storage devices, where each information processing device executes one or more virtual machines by using a processor thereof. When first virtual machines used for distributed processing are created, a management device monitors a utilization ratio of the processor used for each of the first virtual machines, a first communication volume used for an access of each of the first virtual machines to one of the plural storage devices, and a second communication volume used for arithmetic processing of each of the first virtual machines performed on data stored in the plural storage devices. The management device controls a migration of each of the first virtual machines between the plural information processing devices, based on the utilization ratio of the processor, the first communication volume, and the second communication volume.

Abstract: A comprehensive approach to streaming backups for virtual machines (“VMs”) in a storage management system comprises improvements to the assignment of data agent proxies for VM secondary copy operations. New considerations in performing a VM streaming backup job include without limitation: determining and enforcing a system-wide per-proxy limit of concurrent data streams; generating an ordered priority list of the VMs to be backed up as a basis for choosing which proxies will back up the respective VM, though the illustrative system may not strictly adhere to the priority list based on further considerations; identifying a next available proxy based on data stream utilization at the proxy; and dynamically re-generating the priority list and re-evaluating considerations if some VMs become “stranded” due to a failure to be backed up. Secondary copy operations are distributed to proxies in ways that improve the chances of successfully completing VM streaming backups.

Abstract: Methods, computer program products, and systems are presented. The methods include, for instance: locating, by one or more processor, at least one virtual machine within a virtual network, wherein gratuitous address resolution functionality of the at least one virtual machine is inactive; and providing, by the one or more processor, location information of the at least one virtual machine. In one embodiment, the locating comprises: receiving an IP address of the at least one virtual machine; and selecting a virtual machine hosting network device from a computing network node table, where the computing network node table comprises at least one network connection record of the silent virtual machine network device hosting a silent virtual machine having a known MAC address and an unknown IP address; and querying the silent virtual machine network device for a MAC address corresponding to the IP address of the at least one virtual machine.

Abstract: A computer-implemented method includes identifying a primary computing platform, identifying one or more secondary computing platforms, and identifying a requesting virtual server. The requesting virtual server resides on the primary computing platform and is associated with one or more requesting clients. One or more donating virtual servers are identified. The donating virtual servers reside on the primary computing platform and are associated with one or more donating clients. One or more external virtual servers are identified. The external virtual servers reside on the secondary computing platforms. A resource donation scenario is determined. The resource donation scenario includes one or more resource exchanges between the requesting virtual server and the donating virtual servers. A resource adjustment scenario is determined. The resource adjustment scenario includes one or more resource exchanges between the external virtual servers.

Abstract: The method includes estimating an amount of unused memory in a memory allocation of one or more virtual machines based on a data associated with one or more applications previously dispatched to the one or more virtual machines. The method includes receiving a request for executing a new application. The method includes estimating an amount of memory utilized by one of the one or more virtual machines to execute the new application. The method includes dispatching the new application to one of the one or more virtual machine having an amount of unused memory exceeding the estimated amount of memory required to execute the new application. The method includes updating the data associated with the one or more applications previously dispatched to the one or more virtual machines by adding an identifier of the new application to the data.

Abstract: A system and method supports dynamic thread pool sizing suitable for use in multi-threaded processing environment such as a distributed data grid. Dynamic thread pool resizing utilizes measurements of thread pool throughput and worker thread utilization in combination with analysis of the efficacy of prior thread pool resizing actions to determine whether to add or remove worker threads from a thread pool in a current resizing action. Furthermore, the dynamic thread pool resizing system and method can accelerate or decelerate the iterative resizing analysis and the rate of worker thread addition and removal depending on the needs of the system. Optimizations are incorporated to prevent settling on a local maximum throughput. The dynamic thread pool sizing/resizing system and method thereby provides rapid and responsive adjustment of thread pool size in response to changes in work load and processor availability.

Abstract: Storing data that includes receiving an indication to perform an operation with respect to data associated with a virtual machine storage abstraction; and using a meta information identifying which data stored on a storage system is associated with the virtual machine storage abstraction to perform the requested operation.

Abstract: Systems and methods for dynamic granularity control of parallelized work in a heterogeneous multi-processor portable computing device (PCD) are provided. During operation a first parallelized portion of an application executing on the PCD is identified. The first parallelized portion comprising a plurality of threads for parallel execution on the PCD. Performance information is obtained about a plurality of processors of the PCD, each of the plurality of processors corresponding to one of the plurality of threads. A number M of workload partition granularities for the plurality of threads is determined, and a total execution cost for each of the M workload partition granularities is determined. An optimal granularity comprising a one of the M workload partition granularities with a lowest total execution cost is determined, and the first parallelized portion is partitioned into a plurality of workloads having the optimal granularity.

Abstract: Disclosed are apparatus and methods for managing thread resources. A computing device can generate threads for an executable application. The computing device can receive an allocation request to allocate thread-specific memory for an executable thread of the threads, where thread-specific memory includes a call stack for the executable thread. In response to the allocation request, the computing device can: allocate the thread-specific memory and indicate that the executable thread is ready for execution. The computing device can execute the executable thread. The computing device can receive a sleep request to suspend executable thread execution. In response to the sleep request, the computing device can determine whether the allocated thread-specific memory is to be deallocated. After determining that the allocated thread-specific memory is to be deallocated: the thread-specific memory can be deallocated and an indication that the executable thread execution is suspended can be provided.

Abstract: A load balancing system for performing stable processing and high reliability includes a management device which acquires time information indicating the time required in past processing on each of n processing devices, estimates a required time required for each processing devices to process processing target information based on the time information thereby obtaining an estimated time, and transmits estimated time information indicating a relationship between the estimated time and the processing device to a load balancing device. The load balancing device determines m (1<m<n) processing devices that process the processing target information based on the estimated time information and transmits the processing target information to the designated processing devices.

Abstract: Management is provided for threads of a database system that is subject to a plurality of disparate bottleneck conditions for resources. A monitor thread retrieves, from a first thread, first monitor data for first bottleneck condition of a first type. The monitor thread compares the first monitor data to a trigger level for the first bottleneck condition and then determines, in response to the comparison of the first monitor data to the trigger level, a potential source of the first bottleneck condition. A potential blocker thread is identified based upon the potential source of the first bottleneck condition. The monitor thread retrieves, from the potential blocker thread, second monitor data for a second type of bottleneck condition that is different from the first type of bottleneck condition. Based upon monitor data, a blocking thread is identified, and a particular blocking solution is applied to the blocking thread.

Abstract: Management is provided for threads of a database system that is subject to a plurality of disparate bottleneck conditions for resources. A monitor thread retrieves, from a first thread, first monitor data for first bottleneck condition of a first type. The monitor thread compares the first monitor data to a trigger level for the first bottleneck condition and then determines, in response to the comparison of the first monitor data to the trigger level, a potential source of the first bottleneck condition. A potential blocker thread is identified based upon the potential source of the first bottleneck condition. The monitor thread retrieves, from the potential blocker thread, second monitor data for a second type of bottleneck condition that is different from the first type of bottleneck condition. Based upon monitor data, a blocking thread is identified, and a particular blocking solution is applied to the blocking thread.

Abstract: A system, apparatus, and method for thread synchronization is provided. In one embodiment, a network system receives a signal from a first computing machine, and determines whether one or more processes are waiting for the signal. The network system also transmits the signal to one of the one or more processes on the first computing machine or a second computing machine to execute a thread of the process.