Local SOA-based IT landscapes have been a research focus for many years. However, current research does not adequately address the needs of global SOA-based IT landscapes. This presentation focuses on global SOA and on the complexity of global SOA-based IT landscapes.
To analyze global SOA-based IT landscapes, we use the concept of solution space, which represents all possible design solutions under given design rules. To measure the complexity of global SOA-based IT landscapes, we propose a new metric: maximum system variety. Maximum system variety shows the maximum cumulative component dependency that a system can achieve under given design rules.
Based on an example, we show how this metric can be used for selecting design rules for reducing system complexity. Identifying and combining such design rules are required for finding a viable setup for a global SOA-based IT landscape. We propose to combine these design rules in a decision tree.
This presentation was given at SATURN 2011 in Burlingame, CA.