Systems and methods are provided for assigning and associating resources in a cloud computing environment. Virtual machines in the cloud computing environment can be assigned or associated with pools corresponding to users as dedicated, standby, or preemptible machines. The various states provide users with the ability to reserve a desired level of resources while also allowing the operator of the cloud computing environment to increase resource utilization.

Assignment of resources in virtual machine pools

Systems and methods are presented for providing resources by way of a platform as a service in a distributed computing environment to perform a job. A user may submit a work item to the system that results in a job being processed on a pool of virtual machines. The pool may be automatically established by the system in response to the work item and other information associated with the work item, the user, and/or the account. Further, it is contemplated that resources associated with the pool, such as virtual machines, may be automatically allocated based, at least in part, on information associated with the work item, the user, the account, the pool, and/or the system.

Platform as a service job scheduling

A service manages a plurality of virtual machine instances for low latency execution of user codes. The plurality of virtual machine instances can be configured based on a predetermined set of configurations. One or more containers may be created within the virtual machine instances. In response to a request to execute user code, the service identifies a pre-configured virtual machine instance suitable for executing the user code. The service can allocate the identified virtual machine instance to the user, create a new container within an instance already allocated to the user, or re-use a container already created for execution of the user code. When the user code has not been activated for a time-out period, the service can invalidate allocation of the virtual machine instance destroy the container. The time from receiving the request to beginning code execution is less than a predetermined duration, for example, 100 ms.

Threading as a service

A system for providing low-latency compute capacity is provided. The system may be configured to route incoming code execution requests based on user indications to use specific containers running on a plurality of virtual machine instances. The system may be configured to process a code execution request, identify, based on the user indication that a specific container previously used to handle a request of similar type is to be used for handling the code execution request, and cause the code execution request to be handled using the specific container.

Code execution request routing

A method identifies an initial configuration of graphical representations (e.g. application icons or widgets) displayed in a user interface presented by a computing device, each of the graphical representations being associated with a respective computer-executable application. Two or more usage signals (e.g. frequency of use, interaction time/frequency, navigation rate and/or order of use) corresponding to each of the graphical representations are determined. The usage signals reflecting user interaction with the respective associated computer-executable application. A priority score is determined based on the usage signals and a priority order of the graphical representation is determined. The priority order is modified based on a second usage signal and a modified configuration of the graphical representation is generated, wherein the modified configuration reduce a navigation rate of the user with respect to the former configuration. At least a portion of the modified configuration of graphical representations is presented to a user.

Organizing graphical representations on computing devices

An example system identifies a set of tasks as being designated for execution, and the set of tasks includes a first task and a second task. The example system accesses task dependency data that corresponds to the second task and indicates that the first task is to be executed prior to the second task. The example system, based on the task dependency data, generates a task dependency model of the set of tasks. The dependency model indicates that the first task is to be executed prior to the second task. The example system schedules an execution of the first task, which is scheduled to use a particular data processing resource. The scheduling is based on the dependency model.

Perv Rastogi

Papers

Task scheduling based on dependencies and resources