Abstract: In one or more embodiments, a software service allows software providers to implement machine learning (ML) features into products offered by the software providers. Each ML feature may be referred to as an encapsulated ML application, which may be defined and maintained in a central repository, while also being provisioned for each user of the software provider on an as-needed basis. Advantageously, embodiments allow for a central definition for an ML application that encapsulates data science and processing capabilities and routines of the software provider. This central ML application delivers a ML deployment pipeline template that may be replicated multiple times as separate, tailored runtime pipeline instances on a per-user basis. Each runtime pipeline instance accounts for differences in the specific data of each user, resulting in user-specific ML models and predictions based on the same central ML application.

Abstract: A provider network implements a proxy to control access to web-based resources of a provider network. The proxy receives requests to access web-based services. The proxy allows access to a web-based service only if user-configured access control rules are satisfied and credentials associated with the web-based service are authenticated. The proxy prevents access to a web-based service if user-configured access control rules are not satisfied or credentials associated with the web-based service are not authenticated. The provider network may also implement a proxy configuration service to set up and launch the proxy. The proxy configuration service receives from the client a specification of the access control rules, configures the proxy based on the access control rules, and launches the proxy.