Abstract: The invention discloses a method for identifying the bacterial species and key functional genes thereof involved in antimony reduction in the soil. After consuming the original substrate by starvation culture, the sole metabolic substrate is added and the sole electron acceptor Sb(V) is provided, so that there is only one dominant electron exchange process in the system. The microorganisms metabolize and oxidize the organic substrate while coupling with the reduction of antimony, so that Sb(V) gets electrons and is reduced to Sb(III). The present invention observes the Sb(V) reduction in an anaerobic culture system of paddy soil under Sb(V) stress, and uses DNA-SIP technology to identify the phylogenic information of microorganisms that can drive the Sb(V) reduction in the culture system.

Abstract: A port listening request dynamically generated by an application process hosted in a container can be identified. Whether the application process hosted in the container is trusted can be determined. Responsive to determining that the application process hosted in the container is trusted, a first port to be used as an external port for the application process can be dynamically selected, and a port assignment can be communicated to a container engine, the port assignment indicating the first port is assigned to the application process. The first port can be mapped to a second port assigned as an internal port for the application process. The first port can be opened for the application process.

Abstract: A port listening request dynamically generated by an application process hosted in a container can be identified. Whether the application process hosted in the container is trusted can be determined. Responsive to determining that the application process hosted in the container is trusted, a first port to be used as an external port for the application process can be dynamically selected, and a port assignment can be communicated to a container engine, the port assignment indicating the first port is assigned to the application process. The first port can be mapped to a second port assigned as an internal port for the application process. The first port can be opened for the application process.

Abstract: A port listening request dynamically generated by an application process hosted in a container can be identified. Whether the application process hosted in the container is trusted can be determined. Responsive to determining that the application process hosted in the container is trusted, a first port to be used as an external port for the application process can be dynamically selected, and a port assignment can be communicated to a container engine, the port assignment indicating the first port is assigned to the application process. The first port can be mapped to a second port assigned as an internal port for the application process. The first port can be opened for the application process.

Abstract: A port listening request dynamically generated by an application process hosted in a container can be identified. Whether the application process hosted in the container is trusted can be determined. Responsive to determining that the application process hosted in the container is trusted, a first port to be used as an external port for the application process can be dynamically selected, and a port assignment can be communicated to a container engine, the port assignment indicating the first port is assigned to the application process. The first port can be mapped to a second port assigned as an internal port for the application process. The first port can be opened for the application process.

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, 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: 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, 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: Embodiments of the present invention provide methods and systems for simulating variable changes during runtime of a process. The method includes recording variable changes and process context, and filtering sensitive content from the variable changes and process context. The recorded variable changes are recorded into a timeline containing the change in values to the variable changes, which is executed in a simulation environment, in order to debug the process.

Abstract: Embodiments of the present invention provide methods and systems for simulating variable changes during runtime of a process. The method includes recording variable changes and process context, and filtering sensitive content from the variable changes and process context. The recorded variable changes are recorded into a timeline containing the change in values to the variable changes, which is executed in a simulation environment, in order to debug the process.

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: 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, 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: 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: 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 a non-intrusive method and apparatus for automatically dispatching security rules in a cloud environment. The method comprises: forming a composition application model of an application in the cloud environment, said composition application model including at least types of various servers for deploying said application; generating a topology model of said various servers in the cloud environment; automatically generating security rules to be adopted by the server-side firewalls of respective servers based on the application context of said application, said composition application model and said topology model; and dispatching said security rules to each server-side firewall based on said composition application model and topology model.

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.