Abstract: Various embodiments manage deployable computing environments. In one embodiment, a system model of a computing environment that includes a set of computing resources is analyzed. The system model at least describes properties of each of the set of computing nodes and identifies a plurality of configuration operations to be executed by each of the set of computing nodes during deployment. A set of dependency information is generated for each of the set of computing nodes based on analyzing the system model. The set of dependency information identifies at least one dependency between two or more of the plurality of configuration operations. An executable coordination operation is added to each of the plurality of configuration operations. The executable coordination operation automatically coordinates execution of the plurality of configuration operations on the computing node.

Abstract: Various embodiments manage deployable computing environments. In one embodiment, a system model of a computing environment that includes a set of computing resources is analyzed. The system model at least describes properties of each of the set of computing nodes and identifies a plurality of configuration operations to be executed by each of the set of computing nodes during deployment. A set of dependency information is generated for each of the set of computing nodes based on analyzing the system model. The set of dependency information identifies at least one dependency between two or more of the plurality of configuration operations. An executable coordination operation is added to each of the plurality of configuration operations. The executable coordination operation automatically coordinates execution of the plurality of configuration operations on the computing node.

Abstract: Various embodiments manage deployable computing environments. In one embodiment, a system model of a computing environment that includes a set of computing resources is analyzed. The system model at least describes properties of each of the set of computing nodes and identifies a plurality of configuration operations to be executed by each of the set of computing nodes during deployment. A set of dependency information is generated for each of the set of computing nodes based on analyzing the system model. The set of dependency information identifies at least one dependency between two or more of the plurality of configuration operations. An executable coordination operation is added to each of the plurality of configuration operations. The executable coordination operation automatically coordinates execution of the plurality of configuration operations on the computing node.

Abstract: Various embodiments manage deployable computing environments. In one embodiment, a system model of a computing environment that includes a set of computing resources is analyzed. The system model at least describes properties of each of the set of computing nodes and identifies a plurality of configuration operations to be executed by each of the set of computing nodes during deployment. A set of dependency information is generated for each of the set of computing nodes based on analyzing the system model. The set of dependency information identifies at least one dependency between two or more of the plurality of configuration operations. An executable coordination operation is added to each of the plurality of configuration operations. The executable coordination operation automatically coordinates execution of the plurality of configuration operations on the computing node.

Abstract: Various embodiments manage deployable computing environments. In one embodiment, a system model of a computing environment that includes a set of computing resources is analyzed. The system model at least describes properties of each of the set of computing nodes and identifies a plurality of configuration operations to be executed by each of the set of computing nodes during deployment. A set of dependency information is generated for each of the set of computing nodes based on analyzing the system model. The set of dependency information identifies at least one dependency between two or more of the plurality of configuration operations. An executable coordination operation is added to each of the plurality of configuration operations. The executable coordination operation automatically coordinates execution of the plurality of configuration operations on the computing node.

Abstract: Various embodiments manage deployable computing environments. In one embodiment, a system model of a computing environment that includes a set of computing resources is analyzed. The system model at least describes properties of each of the set of computing nodes and identifies a plurality of configuration operations to be executed by each of the set of computing nodes during deployment. A set of dependency information is generated for each of the set of computing nodes based on analyzing the system model. The set of dependency information identifies at least one dependency between two or more of the plurality of configuration operations. An executable coordination operation is added to each of the plurality of configuration operations. The executable coordination operation automatically coordinates execution of the plurality of configuration operations on the computing node.

Abstract: A high availability system in a cloud computing environment includes a snapshot manager disposed in a mirror environment having at least one computer server and a plurality of virtual machines disposed in a production environment. Each of the plurality of virtual machines includes a snapshot agent configured to perform a method. The method includes periodically taking snapshots of the virtual machine associated with the snapshot agent, determining a delta image based on a change between a current snapshot and a previous snapshot, removing previous snapshots in the virtual machine and transmitting the delta image to the snapshot manager. The snapshot manager is configured to store a recovery image for each of the plurality of virtual machines and to merge the received delta image with the recovery image to update the recovery image.

Abstract: A high availability system in a cloud computing environment includes a snapshot manager disposed in a mirror environment having at least one computer server and a plurality of virtual machines disposed in a production environment. Each of the plurality of virtual machines includes a snapshot agent configured to perform a method. The method includes periodically taking snapshots of the virtual machine associated with the snapshot agent, determining a delta image based on a change between a current snapshot and a previous snapshot, removing previous snapshots in the virtual machine and transmitting the delta image to the snapshot manager. The snapshot manager is configured to store a recovery image for each of the plurality of virtual machines and to merge the received delta image with the recovery image to update the recovery image.

Abstract: A system method and computer program product for managing readiness states of a plurality of computing devices. In response to a request, a computer system operates to either: provide one or more computing devices from an inactive pool to an active pool, or accept one or more active computing devices into the inactive pool. An Inactive Pool Manager proactively manages the inactive states of each computing device by: determining the desired number (and identities) of computing devices to be placed in each inactive state of readiness by solving a constraint optimization problem that describes a user-specified trade-off between expected readiness (estimated time to be able to activate computing devices when they are needed next) and conserving energy; generating a plan for changing the current set of inactive states to the desired set; and, executing the plan. Multiple alternative ways of quantifying the desired responsiveness to surges in demand are provided.

Abstract: A high availability system in a cloud computing environment includes a snapshot manager disposed in a mirror environment having at least one computer server and a plurality of virtual machines disposed in a production environment. Each of the plurality of virtual machines includes a snapshot agent configured to perform a method. The method includes periodically taking snapshots of the virtual machine associated with the snapshot agent, determining a delta image based on a change between a current snapshot and a previous snapshot, removing previous snapshots in the virtual machine and transmitting the delta image to the snapshot manager. The snapshot manager is configured to store a recovery image for each of the plurality of virtual machines and to merge the received delta image with the recovery image to update the recovery image.

Abstract: A high availability system in a cloud computing environment includes a snapshot manager disposed in a mirror environment having at least one computer server and a plurality of virtual machines disposed in a production environment. Each of the plurality of virtual machines includes a snapshot agent configured to perform a method. The method includes periodically taking snapshots of the virtual machine associated with the snapshot agent, determining a delta image based on a change between a current snapshot and a previous snapshot, removing previous snapshots in the virtual machine and transmitting the delta image to the snapshot manager. The snapshot manager is configured to store a recovery image for each of the plurality of virtual machines and to merge the received delta image with the recovery image to update the recovery image.

Abstract: A system method and computer program product for managing readiness states of a plurality of computing devices. In response to a request, a computer system operates to either: provide one or more computing devices from an inactive pool to an active pool, or accept one or more active computing devices into the inactive pool. An Inactive Pool Manager proactively manages the inactive states of each computing device by: determining the desired number (and identities) of computing devices to be placed in each inactive state of readiness by solving a constraint optimization problem that describes a user-specified trade-off between expected readiness (estimated time to be able to activate computing devices when they are needed next) and conserving energy; generating a plan for changing the current set of inactive states to the desired set; and, executing the plan. Multiple alternative ways of quantifying the desired responsiveness to surges in demand are provided.

Abstract: Managing readiness states of a plurality of computing devices. A programmed processor unit operates, upon receipt of a request, to: provide one or more computing devices from an inactive pool to an active pool, or accept one or more active computing devices into the inactive pool. The system proactively manages the inactive states of each computing device by: determining the desired number (and identities) of computing devices to be placed in each inactive state of readiness by solving a constraint optimization problem that describes a user-specified trade-off between expected readiness (estimated time to be able to activate computing devices when they are needed next) and conserving energy; generating a plan for changing the current set of inactive states to the desired set; and, executing the plan. Multiple alternative ways of quantifying the desired responsiveness to surges in demand are provided.

Abstract: A system method and computer program product for managing readiness states of a plurality of computing devices. A programmed processor unit operates, upon receipt of a request, to either: provide one or more computing devices from an inactive pool to an active pool, or accept one or more active computing devices into the inactive pool. An Inactive Pool Manager proactively manages the inactive states of each computing device by: determining the desired number (and identities) of computing devices to be placed in each inactive state of readiness by solving a constraint optimization problem that describes a user-specified trade-off between expected readiness (estimated time to be able to activate computing devices when they are needed next) and conserving energy; generating a plan for changing the current set of inactive states to the desired set; and, executing the plan.

Abstract: Managing readiness states of a plurality of computing devices. A programmed processor unit operates, upon receipt of a request, to: provide one or more computing devices from an inactive pool to an active pool, or accept one or more active computing devices into the inactive pool. The system proactively manages the inactive states of each computing device by: determining the desired number (and identities) of computing devices to be placed in each inactive state of readiness by solving a constraint optimization problem that describes a user-specified trade-off between expected readiness (estimated time to be able to activate computing devices when they are needed next) and conserving energy; generating a plan for changing the current set of inactive states to the desired set; and, executing the plan. Multiple alternative ways of quantifying the desired responsiveness to surges in demand are provided.

Abstract: A system and method for testing a self configuring computer which includes a computer system. Sensors electrically communicating with respective electrical connectors in the computer system. The sensors detecting when the electrical connector has a change of status from a previous start up. The sensor indicating a state change when the connector has a change of status. The computer system electrically communicating with the sensor for detecting the sensor state. The computer system initiating a power up and a self test of the connector and a new device connected to the connector using the program upon start up of the computer system when a change in the state of the sensor indicates a change in the status of the connector. The computer system by-passing a power up and self test of the connector when there is no change in the state of the sensor.

Abstract: A system method and computer program product for managing readiness states of a plurality of computing devices. A programmed processor unit operates, upon receipt of a request, to either: provide one or more computing devices from an inactive pool to an active pool, or accept one or more active computing devices into the inactive pool. An Inactive Pool Manager proactively manages the inactive states of each computing device by: determining the desired number (and identities) of computing devices to be placed in each inactive state of readiness by solving a constraint optimization problem that describes a user-specified trade-off between expected readiness (estimated time to be able to activate computing devices when they are needed next) and conserving energy; generating a plan for changing the current set of inactive states to the desired set; and, executing the plan.

Abstract: A system and method for autonomic problem determination. Events and problems associated with the events are received from a computing resource and are expressed as entries in an event-problem matrix. Expert knowledge is expressed as entries in one or more multi-level structure dictionaries. The system and method enables dynamic interaction between the events in the matrix and the current dictionaries with its entries being updated continuously to maximize correlation among the events and problems. The index of each term in the dictionary is used to calculate the weight of each event in the matrix wherein events having frequent association with a specific problem will be given a higher weight in the matrix. Using singular value decomposition (SVD), the weighted events enable an accelerated and accurate convergence to a set of specific associated problems.

Abstract: A statistical approach implementing Singular Value Decomposition (SVD) to a policy-based management system for autonomic and on-demand computing applications. The statistical approach empowers a class of applications that require policies to handle ambiguous conditions and allow the system to “evolve” in response to changing operation and environment conditions. In the system and method providing the statistical approach, observed event-policy associated data, which is represented by an event-policy matrix, is treated as a statistical problem with the assumption that there are some underlying or implicit higher order correlations among events and policies. The SVD approach enables such correlations to be modeled, extracted and modified. From these correlations, recommended policies can be selected or created without exact match of policy conditions.

Abstract: A system and method for testing a self configuring computer which includes a computer system. Sensors electrically communicating with respective electrical connectors in the computer system. The sensors detecting when the electrical connector has a change of status from a previous start up. The sensor indicating a state change when the connector has a change of status. The computer system electrically communicating with the sensor for detecting the sensor state. The computer system initiating a power up and a self test of the connector and a new device connected to the connector using the program upon start up of the computer system when a change in the state of the sensor indicates a change in the status of the connector. The computer system by-passing a power up and self test of the connector when there is no change in the state of the sensor.