Abstract:
Systems and methods are described for managing cross-account access to tasks on an on-demand code execution environment or other distributed code execution environment. Such environments utilize pre-initialized virtual machine instances to enable execution of user-specified code in a rapid manner, without delays typically caused by initialization of the virtual machine instances. However, to ensure security, the code of different users is generally maintained separately, and executed on separate virtual machines. Embodiments described herein enable users of a first account to execute code of a second account, without gaining access to the code itself and while maintaining the privacy and security of each account. Specifically, aliases for a task of a first account can be created on a task of a second account, and used to invoke that task on behalf of the first account. Aliases may also allow users to customize how the task is executed.
Abstract:
Systems and methods are described for utilizing cross-account access to tasks on an on-demand code execution environment or other distributed code execution environment to implement an application programming interface (API) on a network-accessible service. An on-demand code execution environment can utilize pre-initialized virtual machine instances to enable execution of user-specified code in a rapid manner, without delays typically caused by initialization of the virtual machine instances. While users may generally execute their own code, the present application enables code of a first user to be executed by a second user, while maintaining the privacy and security of the code and associated accounts. Further, the present application enables a set of tasks to be grouped together as an API, enabling any user to create an API for a service, while the on-demand code execution environment manages execution of the tasks and allocation of underlying computing resources.
Abstract:
Systems and methods are described for determining a location in an on-demand code execution environment to execute user-specified code. Virtual machines can be utilized to isolate different executions of code from one another. However, virtual machines require additional computing resources to implement, and may slow code executions. This disclosure enables multiple items of code, potentially associated with different users, to be executed on a single virtual machine instance or other device. Specifically, the present disclosure enables the generation of a risk profile for an item of code, which can be used to determine the security or privacy risk that would occur by executing the code on a device. By comparing the risk profiles of a given item of code to other items of code executing on a device, the on-demand code execution environment can selectively group code executions, thus increasing the efficiency of the system while maintaining security and privacy.
Abstract:
Systems and methods are described for predictively managing calls to tasks on an on-demand code execution environment. Specifically, a task profile can be utilized to predict that a call to a task will be followed by transmission of information to an auxiliary service. Thereafter, the on-demand code execution environment can select a virtual machine to execute the task based, for example, on the speed or reliability of a communication channel between the selected virtual machine and the auxiliary service. If execution of the task does cause transmission of information to the auxiliary service, the information can be transmitted via the communication channel, thereby increasing the speed or reliability of the transmission.
Abstract:
Systems and methods are described for transforming a data set within a data source into a series of task calls to an on-demand code execution environment or other distributed code execution environment. Such environments utilize pre-initialized virtual machine instances to enable execution of user-specified code in a rapid manner, without delays typically caused by initialization of the virtual machine instances, and are often used to process data in near-real time, as it is created. However, limitations in computing resources may inhibit a user from utilizing an on-demand code execution environment to simultaneously process a large, existing data set. The present application provides a task generation system that can iteratively retrieve data items from an existing data set and generate corresponding task calls to the on-demand computing environment, while ensuring that at least one task call for each data item within the existing data set is made.
Abstract:
A system for providing a stateful virtual compute system is provided. The system may be configured to maintain a plurality of virtual machine instances. The system may be further configured to receive a request to execute a program code and select a virtual machine instance to execute the program code on the selected virtual machine instance. The system may further associate the selected virtual machine instance with shared resources and allow program codes executed in the selected virtual machine instance to access the shared resources.
Abstract:
A service manages a plurality of virtual machine instances for low latency execution of user codes. The service can provide the capability to execute user code in response to events triggered on various event sources and initiate execution of other control functions to improve the code execution environment in response to detecting errors or unexpected execution results. The service may maintain or communicate with a separate storage area for storing code execution requests that were not successfully processed by the service. Requests stored in such a storage area may subsequently be re-processed by the service.
Abstract:
A system for providing automatic resource resizing is provided. The system may be configured to maintain a plurality of virtual machine instances. The system may be further configured to receive a request to execute a program code and allocate computing resources for executing the program code on one of the virtual machine instances. The amount of resources allocated for executing the program code may be specified by the request and adjusted as needed.
Abstract:
A service manages a plurality of virtual machine instances for low latency execution of user codes. The service can provide the capability to execute user code in response to events triggered on an auxiliary service to provide implicit and automatic rate matching and scaling between events being triggered on the auxiliary service and the corresponding execution of user code on various virtual machine instances. An auxiliary service may be configured as an event triggering service to detect events and generate event messages for execution of the user codes. The service can request, receive, or poll for event messages directly from the auxiliary service or via an intermediary message service. Event messages can be rapidly converted to requests to execute user code on the service. The time from processing the event message to initiating a request to begin code execution is less than a predetermined duration, for example, 100 ms.
Abstract:
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.