No Downtime for Data Conversions: Rethinking Hot Upgrades (CMU-PDL-09-106)

Unavailability in enterprise systems is usually the result of planned events, such as upgrades, rather than failures. Major system upgrades entail complex data conversions that are difficult to perform on the fly, in the face of live workloads. Minimizing the downtime imposed by such conversions is a time-intensive and error-prone manual process. We present Imago, a system that aims to simplify the upgrade process, and we show that it can eliminate all the causes of planned downtime recorded during the upgrade history of one of the ten most popular websites. Building on the lessons learned from past research on live upgrades in middleware systems, Imago trades off a need for additional storage resources for the ability to perform end-to-end, enterprise upgrades online, with minimal application-specific knowledge. Acknowledgements: We would like to thank Alan Downing, Jim Stamos and Byron Wang of Oracle for their feedback during the early stage of this research project.