Abstract: A method (and system) for managing memory among virtual machines in a system having a plurality of virtual machines, includes providing at least one memory optimization mechanism which can reduce memory usage of a virtual machine at a cost of increasing CPU usage. Information on memory usage and CPU usage of each virtual machine is periodically collected. In response to detecting that a first virtual machine exhibits a high level of memory use, at least one second virtual machine with extra CPU capacity is identified. The at least one memory optimization mechanism is applied to the at least one second virtual machine, to reduce memory used by the at least one second virtual machine, thereby providing a portion of freed memory. The portion of freed memory is then allocated to the first virtual machine.

Abstract: An apparatus includes at least one processor executing a method for managing memory among a plurality of concurrently-running virtual machines, and a non-transitory memory device that stores a set of computer readable instructions for implementing and executing said memory management method. A memory optimization mechanism can reduce a memory usage of a virtual machine at a cost of increasing a central processing unit (CPU) usage. Information on a memory usage and a CPU usage of each virtual machine is periodically collected. When a first virtual machine exhibits high memory use, at least one second virtual machine with an extra CPU capacity is identified. A memory optimization mechanism is applied to the second virtual machine to reduce memory used by the second virtual machine, thereby providing a portion of freed memory that is then allocated to the first virtual machine.

Abstract: A method (and system) for managing memory among virtual machines in a system having a plurality of virtual machines, includes providing at least one memory optimization mechanism which can reduce memory usage of a virtual machine at a cost of increasing CPU usage. Information on memory usage and CPU usage of each virtual machine is periodically collected. In response to detecting that a first virtual machine exhibits a high level of memory use, at least one second virtual machine with extra CPU capacity is identified. The at least one memory optimization mechanism is applied to the at least one second virtual machine, to reduce memory used by the at least one second virtual machine, thereby providing a portion of freed memory. The portion of freed memory is then allocated to the first virtual machine.

Abstract: Methods and apparatus are provided for evaluating potential resource capacity in a system where there is elasticity and competition between a plurality of containers. A dynamic potential capacity is determined for at least one container in a plurality of containers competing for a total capacity of a larger container. A current utilization by each of the plurality of competing containers is obtained, and an equilibrium capacity is determined for each of the competing containers. The equilibrium capacity indicates a capacity that the corresponding container is entitled to. The dynamic potential capacity is determined based on the total capacity, a comparison of one or more of the current utilizations to one or more of the corresponding equilibrium capacities and a relative resource weight of each of the plurality of competing containers. The dynamic potential capacity is optionally recalculated when the set of plurality of containers is changed or after the assignment of each work element.

Abstract: A method and structure for dynamic memory re-allocation for an application runtime environment (ARE) includes receiving, through an interface of an application runtime environment (ARE), a first set of internal operational metrics of the ARE executing at a current setting S1 on a processor of a computer. A first performance P1 of the ARE is determined at the current setting S1 using the received first set of internal operation metrics. The current setting S1 of the ARE is varied to a new setting S2. A second set of internal operational metrics of the ARE executing at the new setting S2 is received through the interface of the ARE. A second performance P2 of the ARE is determined at the new setting S2, using the received second set of internal operation metrics. A memory allocation for the ARE is re-allocated, based on the determined performances P1 and P2.

Abstract: Methods and apparatus are provided for scheduling parallel jobs in a system of virtual containers. At least one parallel job is assigned to a plurality of containers competing for a total capacity of a larger container, wherein the at least one parallel job comprises a plurality of tasks. The assignment method comprises determining a current utilization and a potential free capacity for each of the plurality of competing containers; and assigning the tasks to one of the plurality of containers based on the potential free capacities and at least one predefined scheduling policy. The predefined scheduling policy may comprise, for example, one or more of load balancing, server consolidation, maximizing the current utilizations, minimizing a response time of the parallel job and satisfying quality of service requirements. The load balancing can be achieved, for example, by assigning a task to a container having a highest potential free capacity.

Abstract: Methods and apparatus are provided for scheduling parallel jobs in a system of virtual containers. At least one parallel job is assigned to a plurality of containers competing for a total capacity of a larger container, wherein the at least one parallel job comprises a plurality of tasks. The assignment method comprises determining a current utilization and a potential free capacity for each of the plurality of competing containers; and assigning the tasks to one of the plurality of containers based on the potential free capacities and at least one predefined scheduling policy. The predefined scheduling policy may comprise, for example, one or more of load balancing, server consolidation, maximizing the current utilizations, minimizing a response time of the parallel job and satisfying quality of service requirements. The load balancing can be achieved, for example, by assigning a task to a container having a highest potential free capacity.

Abstract: A method (and system) for managing memory among virtual machines in a system having a plurality of virtual machines, includes providing at least one memory optimization mechanism which can reduce memory usage of a virtual machine at a cost of increasing CPU usage. Information on memory usage and CPU usage of each virtual machine is periodically collected. In response to detecting that a first virtual machine exhibits a high level of memory use, at least one second virtual machine with extra CPU capacity is identified. The at least one memory optimization mechanism is applied to the at least one second virtual machine, to reduce memory used by the at least one second virtual machine, thereby providing a portion of freed memory. The portion of freed memory is then allocated to the first virtual machine.

Abstract: A method (and system) for managing memory among virtual machines in a system having a plurality of virtual machines, includes providing at least one memory optimization mechanism which can reduce memory usage of a virtual machine at a cost of increasing CPU usage. Information on memory usage and CPU usage of each virtual machine is periodically collected. In response to detecting that a first virtual machine exhibits a high level of memory use, at least one second virtual machine with extra CPU capacity is identified. The at least one memory optimization mechanism is applied to the at least one second virtual machine, to reduce memory used by the at least one second virtual machine, thereby providing a portion of freed memory. The portion of freed memory is then allocated to the first virtual machine.

Abstract: Methods and apparatus are provided for scheduling parallel jobs in a system of virtual containers. At least one parallel job is assigned to a plurality of containers competing for a total capacity of a larger container, wherein the at least one parallel job comprises a plurality of tasks. The assignment method comprises determining a current utilization and a potential free capacity for each of the plurality of competing containers; and assigning the tasks to one of the plurality of containers based on the potential free capacities and at least one predefined scheduling policy. The predefined scheduling policy may comprise, for example, one or more of load balancing, server consolidation, maximizing the current utilizations, minimizing a response time of the parallel job and satisfying quality of service requirements. The load balancing can be achieved, for example, by assigning a task to a container having a highest potential free capacity.

Abstract: Methods and apparatus are provided for scheduling parallel jobs in a system of virtual containers. At least one parallel job is assigned to a plurality of containers competing for a total capacity of a larger container, wherein the at least one parallel job comprises a plurality of tasks. The assignment method comprises determining a current utilization and a potential free capacity for each of the plurality of competing containers; and assigning the tasks to one of the plurality of containers based on the potential free capacities and at least one predefined scheduling policy. The predefined scheduling policy may comprise, for example, one or more of load balancing, server consolidation, maximizing the current utilizations, minimizing a response time of the parallel job and satisfying quality of service requirements. The load balancing can be achieved, for example, by assigning a task to a container having a highest potential free capacity.

Abstract: A method for hosting versioned web services includes steps of: receiving a request from a service requestor, the request comprising version metadata; parsing the request; extracting the version metadata from the parsing step; and locating a target implementation version using the version metadata. If the target implementation version is located, the method proceeds by dynamically routing the versioned request to the target implementation version.

Abstract: Methods and apparatus are provided for evaluating potential resource capacity in a system where there is elasticity and competition between a plurality of containers. A dynamic potential capacity is determined for at least one container in a plurality of containers competing for a total capacity of a larger container. A current utilization by each of the plurality of competing containers is obtained, and an equilibrium capacity is determined for each of the competing containers. The equilibrium capacity indicates a capacity that the corresponding container is entitled to. The dynamic potential capacity is determined based on the total capacity, a comparison of one or more of the current utilizations to one or more of the corresponding equilibrium capacities and a relative resource weight of each of the plurality of competing containers. The dynamic potential capacity is optionally recalculated when the set of plurality of containers is changed or after the assignment of each work element.

Abstract: A generic mechanism and model are provided to capture and store configuration profiles for resource monitors such that monitors can be flexibly deployed, configured, modified, and removed using appropriate sets of parameters and values. As an integral part of resource provisioning, this generic mechanism will require only a generic set of workflows and a generic data model to provision monitors. The provisioning system of the present invention captures and stores response parameters and values from monitors created during initial deployment such that these parameters can be used for later modification and removal of these monitors.

Abstract: A method for managing a web service client update without recompiling or redeploying of the client code includes the following steps or acts of: receiving a request for the web service from a subscribed client; transmitting the request to the web service; receiving notification of the web service update from a service provider or registry or some other means; parsing the notification and retrieving parameters describing the web service update; marshalling the parameters; determining whether the new web service update is compatible with the current web service invoked by the client application; updating the local service proxy instance with the marshaled parameters if the new web service update is compatible with the current web service invoked by the client application; and transmitting a notification if the web service update is not compatible with the current web service invoked by the client application.

Abstract: A method for hosting versioned web services includes steps of: receiving a request from a service requestor, the request comprising version metadata; parsing the request; extracting the version metadata from the parsing step; and locating a target implementation version using the version metadata. If the target implementation version is located, the method proceeds by dynamically routing the versioned request to the target implementation version.

Abstract: A method for hosting versioned web services includes steps of: receiving a request from a service requester, the request comprising version metadata; parsing the request; extracting the version metadata from the parsing step; and locating a target implementation version using the version metadata. If the target implementation version is located, the method proceeds by dynamically routing the versioned request to the target implementation version.

Abstract: A method, system, and computer program product are described for managing the provisioning of resources in a data processing system. There are different types of resources. Each resource is one of these types. Multiple provisioning states are defined for each type of resource. Relationships are defined among the provisioning states. The relationships describe valid transitions from one state to another. Workflows of one or more tasks are defined, varying to the resource implementation specifications, that are associated with each one of the valid transitions between states. When a resource is to transition from a current state, the relationships among states are used to determine a valid next state. The workflow specific to the resource specification and associated with this transition from the current state to the determined next state is then executed in order to transition to the next state.

Abstract: A generic method and model for capturing and storing configuration profiles for each resource in a provisioning system. As a resource is utilized in a specific environment, the configuration values can be changed as needed to reflect different stages in the life cycle of the resource, such as configuration, and modification.

Abstract: A method, system, and computer program product are disclosed for logically provisioning resources in a data processing system. A request for one or more resources to be provisioned in a provisioning environment is received. The requested resources may be of multiple different available types of resources. Particular instances of the requested types of resources are selected from a group of different types of unassigned available resources. The selected resources are indicated as being reserved, and thus no longer unassigned or available, to fulfill this request. The selected resources are then logically provisioned by establishing logical relationships between the selected resource instances in the provisioning environment.