Abstract:
Techniques are described for facilitating use of software components by software applications in a configurable manner. In some situations, the software components are fee-based components that are made available by providers of the components for use by others in exchange for fees defined by the components providers, and in at least some situations, the software components may have various associated restrictions or other non-price conditions related to their use. The described techniques facilitate use of such software components by software applications in a configured manner. Furthermore, in at least some situation, the execution of such software applications is managed by an application deployment system that controls and tracks the execution of the software application on one or more computing nodes, including to manage the execution of any software components that are part of the software application.
Abstract:
The deployment of content and computing resources for implementing a distributed software application can be optimized based upon customer location. The volume and geographic origin of incoming requests for a distributed software application are determined. Based upon the volume and geographic origin of the incoming requests, content and/or one or more instances of the distributed software application may be deployed to a geographic region generating a significant volume of requests for the distributed software application. Content and/or instances of a distributed software application might also be speculatively deployed to a geographic region in an attempt to optimize the performance, cost, or other attribute of a distributed software application.
Abstract:
Update preferences might be utilized to specify that an update to an application should not be applied until the demand for the application falls below a certain threshold. Demand for the application is monitored. The update to the application is applied when the actual demand for the application falls below the specified threshold. The threshold might be set such that updates are deployed during the off-peak periods of demand encountered during a regular demand cycle, such as a diurnal, monthly, or yearly cycle.
Abstract:
Update preferences might be utilized to specify that an update to an application should not be applied until the demand for the application falls below a certain threshold. Demand for the application is monitored. The update to the application is applied when the actual demand for the application falls below the specified threshold. The threshold might be set such that updates are deployed during the off-peak periods of demand encountered during a regular demand cycle, such as a diurnal, monthly, or yearly cycle.
Abstract:
Techniques are described for facilitating use of software components by software applications in a configurable manner. In some situations, the software components are fee-based components that are made available by providers of the components for use by others in exchange for fees defined by the components providers, and in at least some situations, the software components may have various associated restrictions or other non-price conditions related to their use. The described techniques facilitate use of such software components by software applications in a configured manner. Furthermore, in at least some situation, the execution of such software applications is managed by an application deployment system that controls and tracks the execution of the software application on one or more computing nodes, including to manage the execution of any software components that are part of the software application.
Abstract:
The deployment of content and computing resources for implementing a distributed software application can be optimized based upon customer location. The volume and geographic origin of incoming requests for a distributed software application are determined. Based upon the volume and geographic origin of the incoming requests, content and/or one or more instances of the distributed software application may be deployed to a geographic region generating a significant volume of requests for the distributed software application. Content and/or instances of a distributed software application might also be speculatively deployed to a geographic region in an attempt to optimize the performance, cost, or other attribute of a distributed software application.
Abstract:
The deployment of content and computing resources for implementing a distributed software application can be optimized based upon customer location. The volume and geographic origin of incoming requests for a distributed software application are determined. Based upon the volume and geographic origin of the incoming requests, content and/or one or more instances of the distributed software application may be deployed to a geographic region generating a significant volume of requests for the distributed software application. Content and/or instances of a distributed software application might also be speculatively deployed to a geographic region in an attempt to optimize the performance, cost, or other attribute of a distributed software application.
Abstract:
Update preferences might be utilized to specify that an update to an application should not be applied until the demand for the application falls below a certain threshold. Demand for the application is monitored. The update to the application is applied when the actual demand for the application falls below the specified threshold. The threshold might be set such that updates are deployed during the off-peak periods of demand encountered during a regular demand cycle, such as a diurnal, monthly, or yearly cycle.
Abstract:
Update preferences might be utilized to specify that an update to an application should not be applied until the demand for the application falls below a certain threshold. Demand for the application is monitored. The update to the application is applied when the actual demand for the application falls below the specified threshold. The threshold might be set such that updates are deployed during the off-peak periods of demand encountered during a regular demand cycle, such as a diurnal, monthly, or yearly cycle.