Cloud computing is a service-oriented approach to distributed computing that provides users with resources at varying levels of abstraction. Cloud infrastructures provide users with access to self-service virtual machines that they can customize for their applications. Alternatively, cloud platforms offer users a fully managed programming stack that users can deploy their applications to and scales without user intervention. Yet challenges remain to using cloud computing systems effectively. Cloud services are offered at varying levels of abstraction, meter based on vendor-specific pricing models, and expose access to their services via proprietary APIs. This raises the barrier-to-entry for each cloud service, and encourages vendor lock-in.

The focus of our research is to design and implement research tools to mitigate the effects of these barriers-to-entry. We design and implement tools that service users in the web services domain, high performance computing domain, and general-purpose application domain. These tools operate on a wide variety of cloud services, and automatically execute applications provided by users, so that the user does not need to be conscientious of how each service operates and meters. Furthermore, these tools leverage programming language support to facilitate more expressive workflows for evolving use cases.

Our empirical results indicate that our contributions are able to effectively execute user-provided applications across cloud compute services from multiple, competing vendors. We demonstrate how we are able to provide users with tools that can be used to benchmark cloud compute, storage, and queue services, without needing to first learn the particulars of each cloud service. Additionally, we are able to optimize the execution of user-provided applications based on cost, performance, or via user-defined metrics.