In recent years Statistical Machine Translation (SMT) has established a dominant position among the variety of machine translation paradigms. Industrial Machine Translation computer systems, such as KantanMT, deliver fast and of high performance SMT solutions to the end user. KantanMT is a cloud-based platform that allows its users to build custom SMT engines and use them for translation via a batch or an online mode. In order to employ the full potential of the cloud we have developed an efficient method for asynchronous online translation. This method implements a producer-consumer technique that uses multiple queues as intermediate data storage units. Furthermore, each queue is associated with a priority that defines how quickly the queue can be consumed. That gives our users the control on the flow of translation requests, especially when it comes to large amounts of data. In this paper we describe the design and the implementation of the new method and compare it to others. We then assess the improvement in the quality of service of our platform by empirical evaluation.