IBM Watson is a reasoning system with a question and answer front end that processes natural language coming from both structured and unstructured data. Watson additionally incorporates analytics from which the system learns to derive answer confidence and scoring. We will discuss the Watson System and some of its key foundations that came from the Open Source Apache Software Foundation. We will share the lessons learned of using Open source technologies including UIMA, Derby, Hadoop and Tomcat in Watson. We will explain how the primary (shallow) search was built with Apache Lucene and how the team followed Agile best practices for its Software development efforts.