Abstract: Examples provide catchment modeling for identifying destination locations eligible for last mile delivery from source locations, such as a store or fulfillment center. The catchment modeling system divides a catchment area associated with the source location into a plurality of geohash blocks within a polygon fence. The size of the geohash blocks varies relative to proximity of each geohash block to a fence point within a polygon fence. The plurality of blocks includes a set of inclusion blocks within the predetermined distance from the source location and/or a set of exclusion blocks exceeding the predetermined distance from the source location. Data compression via polygon merging is performed. The compressed data is cached for utilization during catchment delivery eligibility determinations. If a destination address is within the set of inclusion address or absent from the set of exclusion addresses, the destination is eligible for delivery from the source to the destination.

Abstract: An example apparatus includes means for setting a scaling status of a first virtual machine included in an application deployed in a computing environment, the first virtual machine to execute a first component of the application, means for identifying an information dependency of a second virtual machine on information from the first virtual machine, the second virtual machine to execute a second component of the application, and means for updating the information dependency based on the scaling status of the first virtual machine, the information dependency in the configuration information to include a reference to the first virtual machine.

Abstract: An example apparatus includes a deployment monitor to initiate a modification of a number of virtual machines deployed in the computing environment. The virtual machines including a first virtual machine to execute a first component of an application deployed in the computing environment. A dependents identifier is to identify an information dependency of a second virtual machine on information from the first virtual machine. The second virtual machine is to execute a second component of the application. An updater is to update the information dependency based on a scaling status of the first virtual machine. The information dependency in the configuration information including a reference to the first virtual machine.

Abstract: Described in detail herein are simulation systems for a production environment and related methods of use. In one exemplary system a routing application receives a request associated with one or more physical objects. Based on the request, the routing application retrieves one or more simulation profiles from a database and forwards the request and the simulation profiles to a first computing system. The first computing system hosts a simulation environment and simultaneously executes a simulation of the request for each simulation profile in the simulation environment. The first computing system generates resultant data in response to executing each simulation that may be used to alter a production application for a production environment.

Abstract: The current document is directed to an integrated cloud-management facility, or subsystem, that incorporates an automated-application-deployment-facility integrator that incorporates one or more automated-application-deployment facilities into the cloud-management facility. The automated-application-deployment-facility integrator allows users of the cloud-management facility to access one or more automated-application-deployment facilities within the context of the cloud-management facility. The automated-application-deployment-facility integrator provides to system managers and administrators, through the cloud-management facility, a wider range of functionalities and capabilities than is provided by a cloud-management facility that includes only a single automated-application-deployment facility, or subsystem.

Abstract: An example apparatus includes a deployment monitor to initiate a modification of a number of virtual machines deployed in the computing environment. The virtual machines including a first virtual machine to execute a first component of an application deployed in the computing environment. A dependents identifier is to identify an information dependency of a second virtual machine on information from the first virtual machine. The second virtual machine is to execute a second component of the application. An updater is to update the information dependency based on a scaling status of the first virtual machine. The information dependency in the configuration information including a reference to the first virtual machine.

Abstract: An example apparatus includes a deployment monitor to initiate a modification of a number of virtual machines deployed in the computing environment. The virtual machines including a first virtual machine to execute a first component of an application deployed in the computing environment. A dependents identifier is to identify an information dependency of a second virtual machine on information from the first virtual machine. The second virtual machine is to execute a second component of the application. An updater is to update the information dependency based on a scaling status of the first virtual machine. The information dependency in the configuration information including a reference to the first virtual machine.

Abstract: A method including generating a first list of fulfillment nodes of fulfillment nodes that are enabled to deliver within a first shipping time period. The method also can include sending each fulfillment node to a separate instance of a multi-threaded worker system. The method additionally can include generating a list of zip codes that the input fulfillment node can deliver to via ground shipping within the first shipping time period. The method additionally can include transforming the lists of zip codes to generate a mapping from each zip code in the lists of zip codes to a list of fulfillment nodes of the fulfillment nodes that can deliver via ground shipping to the each zip code within the first shipping speed. The method additionally can include receiving a request including an input zip code and an input shipping time period.

Abstract: Described in detail herein are simulation systems for a production environment and related methods of use. In one exemplary system a routing application receives a request associated with one or more physical objects. Based on the request, the routing application retrieves one or more simulation profiles from a database and forwards the request and the simulation profiles to a first computing system. The first computing system hosts a simulation environment and simultaneously executes a simulation of the request for each simulation profile in the simulation environment. The first computing system generates resultant data in response to executing each simulation that may be used to alter a production application for a production environment.

Abstract: An example apparatus includes a deployment monitor to initiate a modification of a number of virtual machines deployed in the computing environment. The virtual machines including a first virtual machine to execute a first component of an application deployed in the computing environment. A dependents identifier is to identify an information dependency of a second virtual machine on information from the first virtual machine. The second virtual machine is to execute a second component of the application. An updater is to update the information dependency based on a scaling status of the first virtual machine. The information dependency in the configuration information including a reference to the first virtual machine.

Abstract: The current document is directed to automated application-release-management facilities that, in a described implementation, coordinate continuous development and release of cloud-computing applications. The application-release-management process is specified, in the described implementation, by application-release-management pipelines, each pipeline comprising one or more stages, with each stage comprising one or more tasks.

Abstract: Methods, apparatus, systems and articles of manufacture are disclosed to scale application deployments in cloud computing environments. An example method disclosed herein includes marking a scaling status of a virtual machine included in a first node deployed in the computing environment, the first node executing a first component of the application, the scaling status of the virtual machine indicating a change in a number of virtual machines included in the first node. The example method also includes identifying a second node including a dependency with the virtual machine, the second node deployed in the computing environment. The example method also includes updating configuration information associated with the second node based on the scaling status of the virtual machine, the configuration information including a reference to the virtual machine.

Abstract: The current document is directed to automated-application-release-management facilities that support aspect-oriented-programming-like insertion of plug-in-implemented advice into release pipelines. In a described implementation, advice is represented by entries in an advice set or aggregation. These entries encode rules, advice types, and references to advice-implementing plug-ins. During release-pipeline execution, calls to the advice-implementing plug-ins are inserted prior to and after tasks in workflows corresponding to the tasks that are then executed by a workflow-execution engine. Rules may include release-pipeline parameters and advice definitions may use wildcard characters and other elements of regular expression in pipeline, stage, and task names.

Abstract: The current document is directed to automated application-release-management facilities that, in a described implementation, coordinate continuous development and release of cloud-computing applications. The application-release-management process is specified, in the described implementation, by application-release-management pipelines, each pipeline comprising one or more stages, with each stage comprising one or more tasks. Current application-release-management pipelines are linear, with the stages sequentially ordered within the pipeline. The current document is directed to an automated application-release-management facility that supports branch points within application-release-management pipelines where, as a result of inter-application dependencies, a task within a stage of the first pipeline associated with a first application launches a second pipeline associated with a second application.

Abstract: The current document is directed to an automated-application-release-management controller within an automated-application-release-management subsystem of a workflow-based cloud-management system that provides mechanisms for parameter-value exchanges between tasks of an application-release-management pipeline. Pipeline parameters and task-output parameters are stored in the execution context of the automated-application-release-management controller. During configuration of an automated-application-release-management pipeline, inputs to tasks may be specified as outputs from other tasks. When tasks finish executing, the output values are stored in the execution context of the management controller so that, when execution of subsequent tasks is launched, the stored output values from previously executed tasks can be furnished as input values to the subsequently executed tasks.

Abstract: The current document is directed to an integrated cloud-management facility, or subsystem, that incorporates an automated-application-deployment-facility integrator that incorporates one or more automated-application-deployment facilities into the cloud-management facility. The automated-application-deployment-facility integrator allows users of the cloud-management facility to access one or more automated-application-deployment facilities within the context of the cloud-management facility. The automated-application-deployment-facility integrator provides to system managers and administrators, through the cloud-management facility, a wider range of functionalities and capabilities than is provided by a cloud-management facility that includes only a single automated-application-deployment facility, or subsystem.

Abstract: The current document is directed to an automated-application-release-management subsystem, or facility, that organizes and manages the application-development and application-release processes to allow for continuous application development and release. The current document is particularly directed to implementations in which the automated application-release-management subsystem is highly modularized to provide plug-in compatibility with a large variety of external, third-party subsystems, libraries, and functionalities. This highly plug-in-compatible architecture provides for decreasing dependencies on various subsystems and components of a workflow-based cloud-management system in which the plug-compatible automated application-release-management subsystem is incorporated.

Abstract: The current document is directed to automated application-release-management facilities that, in a described implementation, coordinate continuous development and release of cloud-computing applications. The application-release-management process is specified, in the described implementation, by application-release-management pipelines, each pipeline comprising one or more stages, with each stage comprising one or more tasks.

Abstract: Methods, apparatus, systems and articles of manufacture are disclosed to scale application deployments in cloud computing environments. An example method disclosed herein includes marking a scaling status of a virtual machine included in a first node deployed in the computing environment, the first node executing a first component of the application, the scaling status of the virtual machine indicating a change in a number of virtual machines included in the first node. The example method also includes identifying a second node including a dependency with the virtual machine, the second node deployed in the computing environment. The example method also includes updating configuration information associated with the second node based on the scaling status of the virtual machine, the configuration information including a reference to the virtual machine.