To simplify and accelerate the process, the team decided to leverage the potential of graph technology. First, they synchronized their Content Management System, which stored the data about their IT infrastructure, with a graph database. The design of a graph data model, compiling together applications, servers, domain components and their respective dependencies, was simple as the underlying infrastructure was inherently a graph.
“In the context of an IS counting more than 200 applications and 150 servers, linked in a complex and constantly changing way, it was essential to work with a graph tool” said Lionel Grosjean, project leader.
They loaded the data into a Neo4j graph database and it was instantly available in Linkurious Enterprise. From here, the team was able to understand in a glimpse the complex interactions between IT assets, which is essential in infrastructure change projects.
With the dynamic graph visualization interface, Lionel and his team could easily navigate through their IT infrastructure, expending neighboring components. This helped to answer questions on macro and micro levels such as “how are my servers connected? what are the single points of failures in my infrastructure? What impact will the replacement of this component have on my system?