1 research outputs found
Reusing empirical knowledge during cloud computing adoption
Moving legacy software systems to cloud platforms is an ever popular option.
But, such an endeavour may not be hazard-free and demands a proper
understanding of requirements and risks involved prior to taking any actions.
The time is indeed ripe to undertake a realistic view of what migrating systems
to the cloud may offer, an understanding of exceptional situations causing
system quality goal failure, and insights on countermeasures. The cloud
migration body of knowledge, although is useful, is dispersed over the current
literature. It is hard for busy practitioners to digest, synthesize, and
harness this body of knowledge into practice in a scenario of integrating
legacy systems with cloud services. We address this issue by creating an
innovative synergy between the approaches evidence-based software engineering
and goal-oriented modelling. We develop an evidential repository of commonly
occurred obstacles and platform agnostic resolution tactics related to making
systems cloud-enabled. The repository is further utilized during the systematic
goal-obstacle elaboration of given cloud migration scenarios. The applicability
of the proposed framework is also demonstrated