Abstract: The embodiment of this disclosure may include a rule engine that adds a plurality of objects into a working memory, and processes the plurality of objects through a plurality of rules stored in a rule repository. Then, the rule engine may create a rule network comprising a root node and a child node based on the plurality of rules, and associate the root node with a predetermined list of object references. The rule engine may build a multi-object sub-token based on the plurality of objects that satisfy the predetermined list of object references. Then, the rule engine may pass the multi-object sub-token from the root node to the child node.

Abstract: In general, the techniques of this invention are directed to autonomic management of autonomic management systems. In particular, the embodiments of this invention use a measure, analyze, and respond model to autonomically manage one or more autonomic management systems. By understanding specific state information of these autonomic management systems, embodiments of the invention may achieve target performance for the autonomic management systems through operations monitoring, analyzing current system state against target state, and modifying the configurations or resources of the autonomic management systems.

Abstract: The embodiment of this disclosure may include a rule engine that adds a plurality of objects into a working memory, and processes the plurality of objects through a plurality of rules stored in a rule repository. Then, the rule engine may create a rule network comprising a root node and a child node based on the plurality of rules, and associate the root node with a predetermined list of object references. The rule engine may build a multi-object sub-token based on the plurality of objects that satisfy the predetermined list of object references. Then, the rule engine may pass the multi-object sub-token from the root node to the child node.

Abstract: In general, this disclosure describes techniques of managing resources in a service-oriented distributed computing system. As described in this disclosure, a control node automatically manages the system such that the system has sufficient capacity to satisfy an agreement to provide a given level of a service. In order to automatically manage the system, the control node evaluates the current capacity levels of resources in the system. The current capacity levels are indicative the capacity of resources to perform certain acts. The capacity of the resources to perform these acts may be indicative of whether the system is able to provide the given level of the service. Because resources may be deployed in chains, the capacities of resources to perform the certain acts may be defined to be dependent on the capacities of other resources to perform other acts.

Abstract: In general, this disclosure describes techniques of managing resources in a service-oriented distributed computing system. As described in this disclosure, a control node automatically manages the system such that the system has sufficient capacity to satisfy an agreement to provide a given level of a service. In order to automatically manage the system, the control node evaluates the current capacity levels of resources in the system. The current capacity levels are indicative the capacity of resources to perform certain acts. The capacity of the resources to perform these acts may be indicative of whether the system is able to provide the given level of the service. Because capacities provided by the resources change as the resources start, the control node uses a predicted pending capacity function to evaluate whether resources that are currently starting will be sufficient to satisfy the level of the service when completely started.

Abstract: In general, this disclosure describes techniques of managing resources in a service-oriented distributed computing system. As described in this disclosure, one or more control nodes provide for the efficient and automated allocation and management of resources within the distributed computing system. In order to provide automated allocation and management of computing functions and resources, a control node uses a set of governors. This set of governors includes a set of service governors to govern services used in the distributed computing system. The set of governors also includes a set of resource governors that govern individual resources of the services in the distributed computing system. The service governors and the resource governors may be implemented using finite state machines.

Abstract: In general, this disclosure describes techniques of managing resources in a service-oriented distributed computing system. As described in this disclosure, a control node automatically manages the system such that the system has sufficient capacity to satisfy an agreement to provide a given level of a service. In order to automatically manage the system, the control node evaluates the current capacity levels of resources in the system. The current capacity levels are indicative the capacity of resources to perform certain acts. The capacity of the resources to perform these acts may be indicative of whether the system is able to provide the given level of the service. Because capacities provided by the resources change as the resources start, the control node uses a predicted pending capacity function to evaluate whether resources that are currently starting will be sufficient to satisfy the level of the service when completely started.

Abstract: In general, this disclosure describes techniques of managing resources in a service-oriented distributed computing system. As described in this disclosure, one or more control nodes provide for the efficient and automated allocation and management of resources within the distributed computing system. In order to provide automated allocation and management of computing functions and resources, a control node uses a set of governors. This set of governors includes a set of service governors to govern services used in the distributed computing system. The set of governors also includes a set of resource governors that govern individual resources of the services in the distributed computing system. The service governors and the resource governors may be implemented using finite state machines.

Abstract: A distributed computing system conforms to a multi-level, hierarchical organizational model. One or more control nodes provide for the efficient and automated allocation and management of computing functions and resources within the distributed computing system in accordance with the organization model. The model includes four distinct levels: fabric, domains, tiers and nodes that provide for the logical abstraction and containment of the physical components as well as system and service application software of the enterprise. A user, such as a system administrator, interacts with the control nodes to logically define the hierarchical organization of distributed computing system. The control nodes are responsible for all levels of management in accordance with the model, including fabric management, domain creation, tier creation and node allocation and deployment.

Abstract: In general, this disclosure describes techniques of managing resources in a service-oriented distributed computing system. As described in this disclosure, a control node automatically manages the system such that the system has sufficient capacity to satisfy an agreement to provide a given level of a service. In order to automatically manage the system, the control node evaluates the current capacity levels of resources in the system. The current capacity levels are indicative the capacity of resources to perform certain acts. The capacity of the resources to perform these acts may be indicative of whether the system is able to provide the given level of the service. Because capacities provided by the resources change as the resources start, the control node uses a predicted pending capacity function to evaluate whether resources that are currently starting will be sufficient to satisfy the level of the service when completely started.

Abstract: In general, this disclosure describes techniques of managing resources in a service-oriented distributed computing system. As described in this disclosure, one or more control nodes provide for the efficient and automated allocation and management of resources within the distributed computing system. In order to provide automated allocation and management of computing functions and resources, a control node uses a set of governors. This set of governors includes a set of service governors to govern services used in the distributed computing system. The set of governors also includes a set of resource governors that govern individual resources of the services in the distributed computing system. The service governors and the resource governors may be implemented using finite state machines.

Abstract: In general, this disclosure describes techniques of managing resources in a service-oriented distributed computing system. As described in this disclosure, one or more control nodes provide for the efficient and automated allocation and management of resources within the distributed computing system. In order to provide automated allocation and management of computing functions and resources, a control node uses a set of governors. This set of governors includes a set of service governors to govern services used in the distributed computing system. The set of governors also includes a set of resource governors that govern individual resources of the services in the distributed computing system. The service governors and the resource governors may be implemented using finite state machines.

Abstract: In general, the techniques of this invention are directed to determining whether a component failure in a distributed computing system is genuine. In particular, embodiments of this invention analyze monitoring data from other application nodes in a distributed computing system to determine whether the component failure is genuine. If the component failure is not genuine, the embodiments may adjust a fault tolerance parameter that caused the component failure to be perceived.

Abstract: A distributed computing system conforms to a multi-level, hierarchical organizational model. One or more control nodes provide for the efficient and automated allocation and management of computing functions and resources within the distributed computing system in accordance with the organization model. The model includes four distinct levels: fabric, domains, tiers and nodes that provide for the logical abstraction and containment of the physical components as well as system and service application software of the enterprise. A user, such as a system administrator, interacts with the control nodes to logically define the hierarchical organization of distributed computing system. The control nodes are responsible for all levels of management in accordance with the model, including fabric management, domain creation, tier creation and node allocation and deployment.

Abstract: In general, the techniques of this invention are directed to determining whether a component failure in a distributed computing system is genuine. In particular, embodiments of this invention analyze monitoring data from other application nodes in a distributed computing system to determine whether the component failure is genuine. If the component failure is not genuine, the embodiments may adjust a fault tolerance parameter that caused the component failure to be perceived.

Abstract: A distributed computing system conforms to a multi-level, hierarchical organizational model. One or more control nodes provide for the efficient and automated allocation and management of computing functions and resources within the distributed computing system in accordance with the organization model. The model includes four distinct levels: fabric, domains, tiers and nodes that provide for the logical abstraction and containment of the physical components as well as system and service application software of the enterprise. A user, such as a system administrator, interacts with the control nodes to logically define the hierarchical organization of distributed computing system. The control nodes are responsible for all levels of management in accordance with the model, including fabric management, domain creation, tier creation and node allocation and deployment.

Abstract: A distributed computing system conforms to a multi-level, hierarchical organizational model. One or more control nodes provide for the efficient and automated allocation and management of computing functions and resources within the distributed computing system in accordance with the organization model. The model includes four distinct levels: fabric, domains, tiers and nodes that provide for the logical abstraction and containment of the physical components as well as system and service application software of the enterprise. A user, such as a system administrator, interacts with the control nodes to logically define the hierarchical organization of distributed computing system. The control node includes an automation subsystem having one or more rule engines that provide autonomic control of the application nodes in accordance with a set of one or more rules.

Abstract: A distributed computing system conforms to a multi-level, hierarchical organizational model. One or more control nodes provide for the efficient and automated allocation and management of computing functions and resources within the distributed computing system in accordance with the organization model. A user, such as a system administrator, interacts with the control nodes to logically define the hierarchical organization of distributed computing system. The control node includes an automation subsystem having one or more rule engines that provide autonomic control of the application nodes in accordance with a set of one or more rules. A pluggable, application-specific application matrix is selected and installed within the control node. The application matrix contains a logical definition of the applications, and parameters for controlling the deployment of the applications within the distributed computing system.

Abstract: In general, this disclosure describes techniques of managing resources in a service-oriented distributed computing system. As described in this disclosure, a control node automatically manages the system such that the system has sufficient capacity to satisfy an agreement to provide a given level of a service. In order to automatically manage the system, the control node evaluates the current capacity levels of resources in the system. The current capacity levels are indicative the capacity of resources to perform certain acts. The capacity of the resources to perform these acts may be indicative of whether the system is able to provide the given level of the service. Because capacities provided by the resources change as the resources start, the control node uses a predicted pending capacity function to evaluate whether resources that are currently starting will be sufficient to satisfy the level of the service when completely started.

Abstract: In general, this disclosure describes techniques of managing resources in a service-oriented distributed computing system. As described in this disclosure, a control node automatically manages the system such that the system has sufficient capacity to satisfy an agreement to provide a given level of a service. In order to automatically manage the system, the control node evaluates the current capacity levels of resources in the system. The current capacity levels are indicative the capacity of resources to perform certain acts. The capacity of the resources to perform these acts may be indicative of whether the system is able to provide the given level of the service. Because resources may be deployed in chains, the capacities of resources to perform the certain acts may be defined to be dependent on the capacities of other resources to perform other acts.