This chapter proposes to use data mining methods implemented via R in order to analyze the Domain Name System (DNS) traffic and to develop innovative techniques for balancing the DNS traffic according to Fully Qualified Domain Names (FQDN) rather than according to the Internet Protocol (IP) addresses. With DNS traffic doubling every year and the deployment of its secure extension DNSSEC, DNS resolving platforms require more and more CPU and memory resources. After characterizing the DNS(SEC) traffic thanks to reduction in dimension and clustering methods implemented with R functions and packages, we propose techniques to balance the DNS traffic among the DNS platform servers based on the FQDN. Several methods are considered to build the FQDN-based routing table: K-means clustering algorithm, mixed integer linear programming, and a heuristic scheme. These load balancing approaches are run, and evaluated with R on real DNS traffic data extracted from an operational network of an Internet Service Provider. They result in reducing the platform CPU resources by 30% with a difference of less than 2% CPU between the servers of a platform