Abstract: Online retailers may operate a network of computing systems in order to provide an electronic marketplace to customers. The network of computing systems may be responsible for maintaining and providing different data to the customers of the online retailer. When a customer transmits a request to the online retailer the request may be divided into a set of tasks that may be executed in parallel by the computing systems. The data generated by executing the various tasks may be cached for various periods of time. Furthermore, log information may be generated based at least in part on execution of the various tasks. The logs may record data on initial access along with an identifier associated with the cached data. For subsequent tasks requiring cached data the log may include only the identifier associated with the cached data.

Abstract: A network-based scalable production load test service may be implemented on a provider network including a plurality of computing devices in order to provide load testing for network-based production systems. In some embodiments, the plurality of computing devices is configured to receive a request to capture to a load test data repository items of transaction data for a network-based production service. In some embodiments, the plurality of computing devices is configured to capture to the load test data repository the items of transaction data. The transaction data include input to the network-based production service over a network. In some embodiments, in response to a load test specification received by the scalable production load test service, the plurality of computing devices is configured to dynamically allocate one or more resources to perform a load test of the network-based production service according to the load test specification.

Abstract: Computer applications may generate event data based on a large volume of different types of record data. Described herein are systems, methods and devices for providing website recommendations using the event data. In one example, using the event data, a computing node generates the website recommendations within a designated amount of time after the generation of the record data.

Abstract: A machine generated service cache that utilizes one or more machine learning classifiers is trained using service requests directed to a human-generated service and service responses generated by the human-generated service in response to the service requests. Once the machine generated service cache has been trained to a predetermined level of performance, the machine generated service cache can be utilized to process actual service requests directed to the human-generated service. The machine generated service cache might be utilized to process service requests for which it is not essential that the returned service response be identical to a response that would be generated by the human-generated service.

Abstract: Computer applications may generate a large volume of different types of record data. In one example, the large volume of record data may represent millions of different processes occurring every second. Described herein are systems, methods and devices for generating parsed data based on the large volume of record data. The parsed data may be consumed by computing nodes within a designated amount of time from the generation of the record data.

Abstract: A page rendering feedback technology is described. A page component and a script are sent to a rendering device as elements of a page. Feedback is received from the script regarding positional rendering information for the page component within the page. The component position may also be compared with a model component layout position to determine whether the component position was correctly rendered.

Abstract: Computer applications may generate event data based on a large volume of different types of record data. Described herein are systems, methods, and devices for enabling a computing node to implement new functions for dynamically consuming the event data. In one example, the computing node may implement a new function using an expression language, without modifying predefined hard coded functions.