Configuration management databases have gained popularity in enterprises due to their role in providing efficient IT Resource and Service Management. Enterprises are becoming more competitive through increasing of resource utilization to support their business services. Existing configuration management database implantations are known to have serious problems, introducing security and maintenance issues. They use a centralized approach implemented via a complex logical database model. This complexity reduces the possibility for enterprises to achieve competitive advantage. Apart from this, implementing such a complex model requires time.

There is room for a new logical database model. Cfengine’s approach to logical database is not as a traditional inventory, but rather as a knowledge-base semantic web of information that connects various aspects of configuration management. The thesis considers designing of a logical database model, and its topic map model for Cfengine 3, which is a machine-learning approach. The developed model is characterized of being easily manageable, easy to implement, extensible, and optimized for updating process.