Many organizations migrate on-premise software applications to the cloud. However, current coarse-grained
cloud migration solutions have made such migrations a non transparent task, an endeavor based on trial-anderror.
This paper presents Variability-based, Pattern-driven Architecture Migration .V-PAM), a migration
method based on (i) a catalogue of fine-grained service-based cloud architecture migration patterns that
target multi-cloud, (ii) a situational migration process framework to guide pattern selection and composition,
and (iii) a variability model to structure system migration into a coherent framework. The proposed
migration patterns are based on empirical evidence from several migration projects, best practice for cloud
architectures and a systematic literature review of existing research. Variability-based, Pattern-driven Architecture
Migration allows an organization to (i) select appropriate migration patterns, (ii) compose them to
define a migration plan, and (iii) extend them based on the identification of new patterns in new contexts.
The patterns are at the core of our solution, embedded into a process model, with their selection governed
by a variability model.