Abstract: Techniques provide include analyzing a first node, associated with a first version of an service, to extract first configuration metadata; analyzing the first node, associated with a second version, subsequent to the first version, of the aservice, to extract second configuration metadata; determining, based upon a comparison of the first configuration metadata and the second configuration metadata, that the first node has not been modified between the first version and the second version; generating a first image of the node for distribution in conjunction with the service in response to the determining that the particular node has not been modified; and caching the first image for use in conjunction with the service.

Abstract: Techniques provide include analyzing a first node, associated with a first version of an service, to extract first configuration metadata; analyzing the first node, associated with a second version, subsequent to the first version, of the aservice, to extract second configuration metadata; determining, based upon a comparison of the first configuration metadata and the second configuration metadata, that the first node has not been modified between the first version and the second version; generating a first image of the node for distribution in conjunction with the service in response to the determining that the particular node has not been modified; and caching the first image for use in conjunction with the service.

Abstract: Techniques provide include analyzing a first node, associated with a first version of an service, to extract first configuration metadata; analyzing the first node, associated with a second version, subsequent to the first version, of the service, to extract second configuration metadata; determining, based upon a comparison of the first configuration metadata and the second configuration metadata, that the first node has not been modified between the first version and the second version; generating a first image of the node for distribution in conjunction with the service in response to the determining that the particular node has not been modified; and caching the first image for use in conjunction with the service.

Abstract: Techniques provide include analyzing a first node, associated with a first version of an service, to extract first configuration metadata; analyzing the first node, associated with a second version, subsequent to the first version, of the service, to extract second configuration metadata; determining, based upon a comparison of the first configuration metadata and the second configuration metadata, that the first node has not been modified between the first version and the second version; generating a first image of the node for distribution in conjunction with the service in response to the determining that the particular node has not been modified; and caching the first image for use in conjunction with the service.

Abstract: Techniques provide include analyzing a first node, associated with a first version of an service, to extract first configuration metadata; analyzing the first node, associated with a second version, subsequent to the first version, of the a service, to extract second configuration metadata; determining, based upon a comparison of the first configuration metadata and the second configuration metadata, that the first node has not been modified between the first version and the second version; generating a first image of the node for distribution in conjunction with the service in response to the determining that the particular node has not been modified; and caching the first image for use in conjunction with the service.

Abstract: Techniques provide include analyzing a first node, associated with a first version of an service, to extract first configuration metadata; analyzing the first node, associated with a second version, subsequent to the first version, of the aservice, to extract second configuration metadata; determining, based upon a comparison of the first configuration metadata and the second configuration metadata, that the first node has not been modified between the first version and the second version; generating a first image of the node for distribution in conjunction with the service in response to the determining that the particular node has not been modified; and caching the first image for use in conjunction with the service.

Abstract: Techniques provide include analyzing a first node, associated with a first version of an service, to extract first configuration metadata; analyzing the first node, associated with a second version, subsequent to the first version, of the aservice, to extract second configuration metadata; determining, based upon a comparison of the first configuration metadata and the second configuration metadata, that the first node has not been modified between the first version and the second version; generating a first image of the node for distribution in conjunction with the service in response to the determining that the particular node has not been modified; and caching the first image for use in conjunction with the service.

Abstract: Techniques provide include analyzing a first node, associated with a first version of an service, to extract first configuration metadata; analyzing the first node, associated with a second version, subsequent to the first version, of the aservice, to extract second configuration metadata; determining, based upon a comparison of the first configuration metadata and the second configuration metadata, that the first node has not been modified between the first version and the second version; generating a first image of the node for distribution in conjunction with the service in response to the determining that the particular node has not been modified; and caching the first image for use in conjunction with the service.

Abstract: A method, apparatus, and computer instructions are provided for a common cluster model for configuring, managing, and operating different clustering technologies in a data center. The common cluster model supports peer cluster domains and management server cluster domains. Each cluster domain may have one or more cluster nodes. For each cluster domains, one or more cluster resources may be defined. These resources may depend on one another and may be grouped into a resource group. A set of cluster domain and cluster resources logical device operations are provided to configure, manage, and operate cluster domains and its associated resources.

Abstract: A deployment modeling platform enables a user to model application characteristics of target software and to associate application modeling parameters to the modeled application characteristics. A user may also model environment characteristics of a target deployment environment and to associate environment modeling parameters to the modeled deployment environment characteristics. Still further, a user may create a deployment model that associates and maps selected parameters of the modeled application characteristics of the target software to associated parameters of the modeled environment characteristics of the deployment environment, and to verify that each parameter that relates to a requirement is mapped to and is fulfilled by an associated parameter that relates to a corresponding capability to determine whether validation problems exist in order to deploy the target software in the associated deployment environment.

Abstract: Extending a plurality of manageability capabilities of manageable information technology (IT) resources utilize an “aspect of” association for describing a relationship between a first object representing a manageable resource playing a role of a subject and one or more additional objects each playing a role of an aspect. The “aspect of” association establishes an overall manageability function for the first object representing a manageable resource and the one or more additional objects as a logical composition of a plurality of manageability capabilities. The manageability capabilities are provided using distinct implementation classes for supporting a specific role, and for supporting management-discipline related aspects and behaviors needed by each of a plurality of resource management applications for managing the manageable resource. The one or more additional objects have an aspect life cycle that is bounded maximally by a subject lifecycle of the first manageable resource.

Abstract: A workflow request having a set of device specific operations and credentials is obtained. The workflow request is parsed to locate at least one of the set of device specific operations and credentials. The located device specific operations and credentials are replaced with at least one logical device operation and logical credentials to create a generalized credential and protocol workflow.

Abstract: A deployment modeling platform enables a user to model application characteristics of target software and to associate application modeling parameters to the modeled application characteristics. A user may also model environment characteristics of a target deployment environment and to associate environment modeling parameters to the modeled deployment environment characteristics. Still further, a user may create a deployment model that associates and maps selected parameters of the modeled application characteristics of the target software to associated parameters of the modeled environment characteristics of the deployment environment, and to verify that each parameter that relates to a requirement is mapped to and is fulfilled by an associated parameter that relates to a corresponding capability to determine whether validation problems exist in order to deploy the target software in the associated deployment environment.

Abstract: A workflow request having a set of device specific operations and credentials is obtained. The workflow request is parsed to locate at least one of the set of device specific operations and credentials. The located device specific operations and credentials are replaced with at least one logical device operation and logical credentials to create a generalized credential and protocol workflow.

Abstract: A deployment modeling platform enables a user to model application characteristics of target software and to associate application modeling parameters to the modeled application characteristics. A user may also model environment characteristics of a target deployment environment and to associate environment modeling parameters to the modeled deployment environment characteristics. Still further, a user may create a deployment model that associates and maps selected parameters of the modeled application characteristics of the target software to associated parameters of the modeled environment characteristics of the deployment environment, and to verify that each parameter that relates to a requirement is mapped to and is fulfilled by an associated parameter that relates to a corresponding capability to determine whether validation problems exist in order to deploy the target software in the associated deployment environment.

Abstract: To provide a more cost effective way to manage the infrastructure while addressing the security needs of a computerized data center, a technique for credential and protocol independent management of infrastructure in a computerized data processing system is provided. More cost effective and secure management is obtained through modified workflows used in the operational management of the computer data processing system. A workflow is first parsed to locate device specific operation requests. Such specifications are then replaced with logical equivalents. The resulting workflow is neutral with respect to both credentials and protocol. Prior to execution, the modified workflow is combined with information retrieved from a resource or by an administrator that further resolves the workflow to a specific target object or plurality of target objects. Security is enhanced through granular administration of user ID and password combinations which may be maintained separate from the workflows in which they are used.

Abstract: A method and system for monitoring computational resources within a data processing system is presented. A monitoring service receives a non-application-specific request to perform a monitoring operation in order to gather information about the usage of a computational resource within a data processing system. The monitoring service automatically selects a monitoring application from a set of monitoring applications in which the selected monitoring application is able to perform the monitoring operation on the computational resource. The monitoring service then sends to the selected monitoring application an application-specific request that identifies the computational resource and indicates the monitoring operation to be performed on the computational resource.

Abstract: A method, apparatus, and computer instructions are provided for expressing high availability (H/A) cluster demand based on probability of breach. When a failover occurs in the H/A cluster, event messages are sent to a provisioning manager server. The mechanism of embodiments of the present invention filters the event messages and translates the events into probability of breach data. The mechanism then updates the data model of the provision manager server and makes a recommendation to the provisioning manager server as to whether reprovisioning of new node should be performed. The provisioning manager server makes the decision and either reprovisions new nodes to the H/A cluster or notifies the administrator of detected poisoning problem.

Abstract: A deployment modeling platform enables a user to model application characteristics of target software and to associate application modeling parameters to the modeled application characteristics. A user may also model environment characteristics of a target deployment environment and to associate environment modeling parameters to the modeled deployment environment characteristics. Still further, a user may create a deployment model that associates and maps selected parameters of the modeled application characteristics of the target software to associated parameters of the modeled environment characteristics of the deployment environment, and to verify that each parameter that relates to a requirement is mapped to and is fulfilled by an associated parameter that relates to a corresponding capability to determine whether validation problems exist in order to deploy the target software in the associated deployment environment.

Abstract: Extending a plurality of manageability capabilities of manageable information technology (IT) resources utilize an “aspect of” association for describing a relationship between a first object representing a manageable resource playing a role of a subject and one or more additional objects each playing a role of an aspect. The “aspect of” association establishes an overall manageability function for the first object representing a manageable resource and the one or more additional objects as a logical composition of a plurality of manageability capabilities. The manageability capabilities are provided using distinct implementation classes for supporting a specific role, and for supporting management-discipline related aspects and behaviors needed by each of a plurality of resource management applications for managing the manageable resource. The one or more additional objects have an aspect life cycle that is bounded maximally by a subject lifecycle of the first manageable resource.