Abstract: A system and method for automated application programming interface (API) importation that includes receiving a selection of at least one API provider service of a set of API provider services with API integration support for a platform, retrieving a listing of APIs provided by the selected at least one API provider service, receiving a selection of at least one API from the listing of APIs, and enabling the selected at least one API for a user of the platform, in response to the selection of the at least one API.

Abstract: Techniques and architectures for data ingestion in an environment having a distributed data storage system. A request to import data into the environment. The data to be imported from an external source through an application programming interface (API). The request is analyzed to determine if the request corresponds to a request to import a large data load. The data is staged if the request is for the large data load. Data management jobs are created to cause the data to be stored in one or more nodes of the distributed data storage system. The data management jobs are transmitted to corresponding nodes in the distributed data storage system. The jobs are executed asynchronously to cause the data to be stored in the nodes.

Abstract: A system and method for automated application programming interface (API) importation that includes receiving a selection of at least one API provider service of a set of API provider services with API integration support for a platform, retrieving a listing of APIs provided by the selected at least one API provider service, receiving a selection of at least one API from the listing of APIs, and enabling the selected at least one API for a user of the platform, in response to the selection of the at least one API.

Abstract: Techniques and architectures for data ingestion in an environment having a distributed data storage system. A request to import data into the environment. The data to be imported from an external source through an application programming interface (API). The request is analyzed to determine if the request corresponds to a request to import a large data load. The data is staged if the request is for the large data load. Data management jobs are created to cause the data to be stored in one or more nodes of the distributed data storage system. The data management jobs are transmitted to corresponding nodes in the distributed data storage system. The jobs are executed asynchronously to cause the data to be stored in the nodes.

Abstract: Techniques and architectures for data ingestion in an environment having a distributed data storage system. A request to import data into the environment. The data to be imported from an external source through an application programming interface (API). The request is analyzed to determine if the request corresponds to a request to import a large data load. The data is staged if the request is for the large data load. Data management jobs are created to cause the data to be stored in one or more nodes of the distributed data storage system. The data management jobs are transmitted to corresponding nodes in the distributed data storage system. The jobs are executed asynchronously to cause the data to be stored in the nodes.

Abstract: Optimization preferences are defined for optimizing execution of a distributed application. Candidate sets of application parameter values may be tested in test execution environments. Measures of performance for metrics of interest are determined based upon the execution of the distributed application using the candidate sets of application parameter values. Utility curves may be utilized to compute measures of effectiveness for metrics of interest. A multi-attribute rollup operation may utilize the computed measures of effectiveness and weights to compute a grand measure of merit (MOM) for the candidate sets of application parameter values. An optimized set of application parameter values may then be selected based upon the computed grand MOMs. The optimized set of application parameter values may be deployed to a production execution environment executing the distributed application.

Abstract: Described is a dynamic web platform configured to provide content rendered with one or more rendering systems. The rendering systems and the modules making up the rendering modules may interact with one another by way of declarative data. Administrators may configure the platform using the declarative data. The declarative data may express operational parameters, business rules, and so forth and may be modified while the platform is operating. The modules in the rendering system may be loosely bound, allowing for concurrent operations, dynamic changes to what content is to be rendered, and so forth.

Abstract: Techniques and architectures for data ingestion in an environment having a distributed data storage system. A request to import data into the environment. The data to be imported from an external source through an application programming interface (API). The request is analyzed to determine if the request corresponds to a request to import a large data load. The data is staged if the request is for the large data load. Data management jobs are created to cause the data to be stored in one or more nodes of the distributed data storage system. The data management jobs are transmitted to corresponding nodes in the distributed data storage system. The jobs are executed asynchronously to cause the data to be stored in the nodes.

Abstract: Optimization preferences are defined for optimizing execution of a distributed application. Candidate sets of application parameter values may be tested in test execution environments. Measures of performance for metrics of interest are determined based upon the execution of the distributed application using the candidate sets of application parameter values. Utility curves may be utilized to compute measures of effectiveness for metrics of interest. A multi-attribute rollup operation may utilize the computed measures of effectiveness and weights to compute a grand measure of merit (MOM) for the candidate sets of application parameter values. An optimized set of application parameter values may then be selected based upon the computed grand MOMs. The optimized set of application parameter values may be deployed to a production execution environment executing the distributed application.

Abstract: Described is a dynamic web platform configured to provide content rendered with one or more rendering systems. The rendering systems and the modules making up the rendering modules may interact with one another by way of declarative data. Administrators may configure the platform using the declarative data. The declarative data may express operational parameters, business rules, and so forth and may be modified while the platform is operating. The modules in the rendering system may be loosely bound, allowing for concurrent operations, dynamic changes to what content is to be rendered, and so forth.