33134results about "Resource allocation" patented technology

A management capability is provided for a virtual computing platform. In one example, this platform allows interconnected physical resources such as processors, memory, network interfaces and storage interfaces to be abstracted and mapped to virtual resources (e.g., virtual mainframes, virtual partitions). Virtual resources contained in a virtual partition can be assembled into virtual servers that execute a guest operating system (e.g., Linux). In one example, the abstraction is unique in that any resource is available to any virtual server regardless of the physical boundaries that separate the resources. For example, any number of physical processors or any amount of physical memory can be used by a virtual server even if these resources span different nodes. A virtual computing platform is provided that allows for the creation, deletion, modification, control (e.g., start, stop, suspend, resume) and status (i.e., events) of the virtual servers which execute on the virtual computing platform and the management capability provides controls for these functions. In a particular example, such a platform allows the number and type of virtual resources consumed by a virtual server to be scaled up or down when the virtual server is running. For instance, an administrator may scale a virtual server manually or may define one or more policies that automatically scale a virtual server. Further, using the management API, a virtual server can monitor itself and can scale itself up or down depending on its need for processing, memory and I / O resources. For example, a virtual server may monitor its CPU utilization and invoke controls through the management API to allocate a new processor for itself when its utilization exceeds a specific threshold. Conversely, a virtual server may scale down its processor count when its utilization falls. Policies can be used to execute one or more management controls. More specifically, a management capability is provided that allows policies to be defined using management object's properties, events and / or method results. A management policy may also incorporate external data (e.g., an external event) in its definition. A policy may be triggered, causing the management server or other computing entity to execute an action. An action may utilize one or more management controls. In addition, an action may access external capabilities such as sending notification e-mail or sending a text message to a telephone paging system. Further, management capability controls may be executed using a discrete transaction referred to as a “job.” A series of management controls may be assembled into a job using one or management interfaces. Errors that occur when a job is executed may cause the job to be rolled back, allowing affected virtual servers to return to their original state.

An apparatus, system, and method are disclosed for autonomic management of data operations and performance resources on a grid computing system. An autonomic management apparatus includes a monitor module, a policy module, and a regulation module. The monitor module is configured to monitor the grid computing system for a trigger event. The policy module is configured to access one of a plurality of system policies. Each of the plurality of system policies corresponds to an operational control parameter of a system resource of the grid computing system. The regulation module is configured to autonomically regulate the system resource in response to a recognized trigger event according to one of the plurality of system policies. The trigger event may be a prediction trigger event, an initiation trigger event, a regulation trigger event, or a termination trigger event.

A level of abstraction is created between a set of physical processors and a set of virtual multiprocessors to form a virtualized data center. This virtualized data center comprises a set of virtual, isolated systems separated by a boundary referred as a partition. Each of these systems appears as a unique, independent virtual multiprocessor computer capable of running a traditional operating system and its applications. In one embodiment, the system implements this multi-layered abstraction via a group of microkernels, each of which communicates with one or more peer microkernel over a high-speed, low-latency interconnect and forms a distributed virtual machine monitor. Functionally, a virtual data center is provided, including the ability to take a collection of servers and execute a collection of business applications over a compute fabric comprising commodity processors coupled by an interconnect. Processor, memory and I / O are virtualized across this fabric, providing a single system, scalability and manageability. According to one embodiment, this virtualization is transparent to the application, and therefore, applications may be scaled to increasing resource demands without modifying the application.

Intelligent monitoring systems and methods for virtual environments are disclosed that understand various components of a virtual infrastructure and how the components interact to provide improved performance analysis to users. In certain examples, a monitoring system assesses the performance of virtual machine(s) in the context of the overall performance of the physical server(s) and the environment in which the virtual machine(s) are running. For instance, the monitoring system can track performance metrics over a determined period of time to view changes to the allocation of resources to virtual machines and their location(s) on physical platforms. Moreover, monitoring systems can utilize past performance information from separate virtual environments to project a performance impact resulting from the migration of a virtual machine from one physical platform to another.

A system has a virtual overlay infrastructure mapped onto physical resources for processing, storage and network communications, the virtual infrastructure having virtual entities for processing, storage and network communications. The system has a mapping manager to dynamically alter the mapping for balancing, performance, and redundancy. There can be more independence from the underlying physical configuration, compared to known methods of virtualizing only some of the entities. The mapping manager can be distributed across a number of entities on different physical servers arranged to cooperate with each other.

A system and method may include identifying a virtual machine setting associated with a virtual machine, obtaining system specification information associated with a computer, and generating validation information based on the system specification information and the virtual machine setting. The system and method may further include determining whether to deploy the virtual machine to the computer based on the validation information.

A system and method for automatic workload characterization are provided. Transactions performed in a computer system may be logged. The log of transactions comprises a timestamp for each transaction. Resource usage in the computer system may be logged. The log of resource usage comprises one or more periods of time during which each of a plurality of resources is used, and the log of resource usage comprises a plurality of system performance metrics which reflect resource consumption by one or more processes that performed the transactions. The timestamps in the log of transactions may be compared to the periods of time in the log of resource usage. It may be determined which transactions used which resources as a result of the comparing the timestamps in the log of transactions to the periods of time in the log of resource usage. One or more workloads may be determined using the determining which transactions used which resources. Heuristics may be used to group processes into workloads.

A plurality of content providers provide multiple resources to multiple clients. At least some of said resources are to be served to clients from a shared content delivery network (CDN) formed by a plurality of repeater servers. Each content provider provides at least some resources via one or more content sources associated with that content provider. Amounts of data transmitted by the CDN on behalf of each of the plurality of content providers are monitored. Based at least in part on said monitoring, requests for resources are selectively delivered at a lower transmission rate. The lower transmission rate is achieved by generating pauses or delays in the transmission.

The present invention relates to a method and apparatus for managing and balancing the load of each of the servers in the network. In one aspect, the invention relates to an apparatus for managing server load in a networked system of servers. The apparatus includes a dynamic store storing run-time information associated with a plurality of servers in a server farm. The apparatus also includes an event bus. The apparatus also includes a load management subsystem in communication with the dynamic store via the event bus. The load management subsystem receives a request from the event bus to identify a server and transmits a message to the event bus that includes an address of an identified server based on information from the dynamic store.

A method and system for leasing storage locations in a distributed processing system is provided. Consistent with this method and system, a client requests access to storage locations for a period of time (lease period) from a server, such as the file system manager. Responsive to this request, the server invokes a lease period algorithm, which considers various factors to determine a lease period during which time the client may access the storage locations. After a lease is granted, the server sends an object to the client that advises the client of the lease period and that provides the client with behavior to modify the lease, like canceling the lease or renewing the lease. The server supports concurrent leases, exact leases, and leases for various types of access. After all leases to a storage location expire, the server reclaims the storage location.

An apparatus and method are disclosed for providing one or more computer services to a plurality of customers (A,B,C). At least one virtual machine (VS) is set up on a real computer (30) for each of the customers (A,B,C) at the request of each of the customers (A,B,C). The or each virtual machine (VS) for each of the customers (A,B,C) has a specification specified by the respective customer (A,B,C).

A virtualized logical server cloud that enables logical servers to exist independent of physical servers that instantiate the logical servers. Servers are treated as logical resources in order to create a logical server cloud. The logical attributes of a logical server are non-deterministically allocated to physical resources creating a cloud of logical servers over the physical servers. Logical separation is facilitated by the addition of a server cloud manager, which is an automated multi-server management layer. Each logical server has persistent attributes that establish its identity. Each physical server includes or is coupled to physical resources including a network resource, a data storage resource and a processor resource. At least one physical server executes virtualization software that virtualizes physical resources for logical servers. The server cloud manager maintains status and instance information for the logical servers including persistent and non-persistent attributes that link each logical server with a physical server.

Resource requests made by clients of origin servers in a network are intercepted by reflector mechanisms and selectively reflected to other servers called repeaters. The reflectors select a best repeater from a set of possible repeaters and redirect the client to the selected best repeater. The client then makes the request of the selected best repeater. The resource is possibly rewritten to replace at least some of the resource identifiers contained therein with modified resource identifiers designating the repeater instead of the origin server.

A monitoring system for a distributed environment including a plurality of hosts capable of executing multiple copies of a scalable application includes a first device for generating first data corresponding to performance of all copies of the scalable application; a second device for generating second data corresponding to performance of all host in the distributed environment; and a third device for generating performance metrics based on the first and second data.