A functional programming discipline, combined with abstractions like Concurrent ML (CML)’s first-class synchronous events, offers an attractive programming model for concurrency. In high-latency distributed environments, like the cloud, however, the high communication latencies incurred by synchronous communication can compromise performance. While switching to an explicitly asynchronous communication model may reclaim some of these costs, program structure and understanding also becomes more complex. To ease the challenge of migrating concurrent applications to distributed cloud environments, we have built an extension of the MultiMLton compiler and runtime that implements CML communication asynchronously, but guarantees that the resulting execution is faithful to the synchronous semantics of CML. We formalize the conditions under which this equivalence holds, and present an implementation that builds a decentralized dependence graph whose structure can be used to check the integrity of an execution with respect to this equivalence. We integrate a notion of speculation to allow ill-formed executions to be rolled-back and re-executed, replacing offending asynchronous actions with safe synchronous ones. Several realistic case studies deployed on the Amazon EC2 cloud infrastructure demonstrate the utility of our approach.