This document discusses lessons learned from deploying Hadoop in a private cloud. Some key lessons include: choosing the right hardware with sufficient CPU, RAM, and bandwidth; understanding that configuration is critical for Hadoop, HBase, and Solr; expecting failures and bugs to occur; and realizing that big data projects take a long time to complete. Public clouds are expensive for long-term big data storage needs, so a private cloud may be more cost effective despite requiring infrastructure management. Open source tools like Hadoop have advanced to enable organizations to tackle "big data" challenges.