Online experimentation is an agile software development practice that plays an essential role in enabling rapid innovation. Existing solutions for online experimentation in Web and mobile applications are unsuitable for cloud applications. There is a need for rethinking online experimentation in the cloud to advance the state-of-the-art by considering the unique challenges posed by cloud environments. In this paper, we introduce Iter8, an open-source system that enables practitioners to deliver code changes to cloud applications in an agile manner while minimizing risk. Iter8 embodies our novel mathematical formulation built on online Bayesian learning and multi-armed bandit algorithms to enable online experimentation tailored for the cloud, considering both SLOs and business concerns, unlike existing solutions. Using Iter8, practitioners can safely and rapidly orchestrate various types of online experiments, gain key insights into the behavior of cloud applications, and roll out the optimal versions in an automated and statistically rigorous manner.