It is clear that public clouds such as Amazon Web Services (AWS) and Microsoft’s Azure provide excellent capabilities for scalable Web applications and Hadoop-based processing. Recent additions to public clouds to support connected devices and IoT have the potential to similarly disrupt emerging homegrown and/or proprietary approaches. While early public cloud IoT success stories have focused on smaller-scale scenarios such as connected houses, it is unclear to what extent these new public cloud mechanisms and abstractions are suitable and effective for larger-scale and/or scientific scenarios, which often have a different set of constraints or requirements. This paper addresses the challenge of implementing a scalable IoT infrastructure testbed in the public cloud for scientific experimentation. There are two main contributions of this paper. First, the design and implementation of a representative cloud-based IoT infrastructure in a specific public cloud – AWS – is presented. The system created is for dynamic vehicle traffic control based on vehicle volumes/patterns and weather conditions. Second, an evaluation of AWS IoT and lessons learned are provided. We find that while AWS IoT performance and performance scalability are likely to meet the requirements of many next-generation scientific IoT use-cases, manageability/modifications of a scientific IoT scenario can be challenging for moderate- to large-scale deployments.