Abstract: In one embodiment, a method includes a processor deploying one or more scripts in a first deployment instance, where the first deployment instance is deployed from a first shared computing environment. The processor determines a difference between the first deployment instance at deployment and the first deployment instance at runtime and based on this determination, selects a first script from the one or more scripts. The processor captures a representation of the first deployment instance and selects a second script, where second script sets up relationships between resources of the first deployment instance in a subsequently deployed deployment instance. The processor utilizes the representation, the first script, and the second script to deploy a second deployment instance from a second shared computing environment.

Abstract: A computer-implemented method includes monitoring a template registry for changes in the template registry. In response to detecting a new template in the template registry, the method includes analyzing the new template to identify explicit and implicit metadata corresponding to the new template. The method further includes determining one or more possible link dependencies between a container based on the new template and one or more other containers, respectively, based on the identified explicit and implicit metadata. In addition, the method includes providing container setting recommendations to a user based on the one or more possible link dependencies and the identified explicit and implicit metadata.

Abstract: Embodiments of the present disclosure dynamically generate solution stacks. In one embodiment, a request to deploy a service in a cloud computing environment is received. A service repository is queried for data that describes one or more requirements of the service. One or more prerequisite services are identified based, at least in part, on the requirements of the service. A solution stack model is dynamically generated from (i) a stack service model of the service and (ii) the one or more prerequisite services, wherein the solution stack model is based, at least in part, on the requirements of the service.

Abstract: Embodiments of the present disclosure dynamically generate solution stacks. In one embodiment, a request to deploy a service in a cloud computing environment is received. A service repository is queried for data that describes one or more requirements of the service. One or more prerequisite services are identified based, at least in part, on the requirements of the service. A solution stack model is dynamically generated from (i) a stack service model of the service and (ii) the one or more prerequisite services, wherein the solution stack model is based, at least in part, on the requirements of the service.

Abstract: A method, apparatus, and/or computer program product analyzes data processing. Dependency metadata, which is used for representing dependency on data among at least two components of an application, is acquired. Error information, which is used for describing errors that occurred while running the application, and data output, which includes data output by components used to run the application, are acquired. Based on the error information, dependency metadata and data output relevant to the error information are analyzed to provide an analysis result. The analysis result includes at least one of: a prompt for an error correction method, a relevant dependency metadata leading to an occurrence of an error, and relevant data output leading to an occurrence of an error.

Abstract: One or more processors acquire dependency metadata, where the dependency metadata is used for representing dependency on data among at least two components of an application. The processor(s) acquire error information and data output, where the error information is used for describing errors that occur while running the application, and where the data output includes data output by the at least two components while running the application. The processor(s) analyze, based on the error information, dependency metadata and data output relevant to the error information, where the analyzing includes determining, based on a null pointer exception in the error information and data output of a component corresponding to the null pointer exception, that there is an error in dependency metadata corresponding to the null pointer exception. The processor(s) then provide an analysis result to improve the operation of a computer that is running the application.

Abstract: One or more processors acquire dependency metadata, where the dependency metadata is used for representing dependency on data among at least two components of an application. The processor(s) acquire error information and data output, where the error information is used for describing errors that occur while running the application, and where the data output includes data output by the at least two components while running the application. The processor(s) analyze, based on the error information, dependency metadata and data output relevant to the error information, where the analyzing includes determining, based on a null pointer exception in the error information and dependency metadata corresponding to the null pointer exception, that corresponding data has not been output by a component corresponding to the null pointer exception. The processor(s) then use an analysis result to improve the operation of a computer that is running the application.

Abstract: One or more processors acquire dependency metadata, where the dependency metadata is used for representing dependency on data among at least two components of an application. The processor(s) acquire error information and data output, where the error information is used for describing errors that occur while running the application, and where the data output includes data output by the at least two components while running the application. The processor(s) analyze, based on the error information, dependency metadata and data output relevant to the error information, where the analyzing includes determining, based on a null pointer exception in the error information and data output of a component corresponding to the null pointer exception, correct dependency metadata corresponding to the null pointer exception. The processor(s) then provide an analysis result to improve the operation of a computer that is running the application.

Abstract: The present invention relates to mechanisms for managing VM instances. More specifically, the mechanisms provide at least one VM instance in a resource pool. A configuration requirement is provided with respect to a virtual machine, the configuration requirement describing a first amount of application resources to be installed on the virtual machine. Based on the configuration requirement, a resource tree is built describing a dependency relation between the first amount of application resources. At least one VM instance corresponding to a sub-path of the resource tree is provided in the resource pool, where on each VM instance in the at least one VM instance there are installed application resources included in the sub-path.

Abstract: A method, apparatus, and/or computer program product analyzes data processing. Dependency metadata, which is used for representing dependency on data among at least two components of an application, is acquired. Error information, which is used for describing errors that occurred while running the application, and data output, which includes data output by components used to run the application, are acquired. Based on the error information, dependency metadata and data output relevant to the error information are analyzed to provide an analysis result. The analysis result includes at least one of: a reason why an error occurs, a prompt for an error correction method, a relevant dependency metadata leading to an occurrence of an error, and relevant data output leading to an occurrence of an error.

Abstract: The present invention relates to mechanisms for managing VM instances. More specifically, the mechanisms provide at least one VM instance in a resource pool. A configuration requirement is provided with respect to a virtual machine, the configuration requirement describing a first amount of application resources to be installed on the virtual machine. Based on the configuration requirement, a resource tree is built describing a dependency relation between the first amount of application resources. At least one VM instance corresponding to a sub-path of the resource tree is provided in the resource pool, where on each VM instance in the at least one VM instance there are installed application resources included in the sub-path.

Abstract: Embodiments of the invention relate to deploying a program module. The deploying includes obtaining a data dependency relationship between the program module and multiple to-be-deployed program modules, and a specific start order. In response to a request to install and configure the program module, data on which the program module depends are identified according to the data dependency relationship. In addition, the program module is installed and configured responsive to the identified data. The program module is started in response to completion of a startup of program modules required to be started before the program module as specified by the specific start order.

Abstract: A method, apparatus, and/or computer program product analyzes data processing. Dependency metadata, which is used for representing dependency on data among at least two components of an application, is acquired. Error information, which is used for describing errors that occurred while running the application, and data output, which includes data output by components used to run the application, are acquired. Based on the error information, dependency metadata and data output relevant to the error information are analyzed to provide an analysis result. The analysis result includes at least one of: a reason why an error occurs, a prompt for an error correction method, a relevant dependency metadata leading to an occurrence of an error, and relevant data output leading to an occurrence of an error.