  Deploying, configuring, and managing large clusters is very a demanding and
cumbersome task due to the complexity of such systems and the variety of skills
needed. One needs to perform low-level configuration of the cluster nodes to
ensure their interoperability and connectivity, as well as install, configure
and provision the needed services.
  In this paper we address this problem and demonstrate how to build a Big Data
analytic platform on Amazon EC2 in a matter of minutes. Moreover, to use our
tool, embedded into a public Amazon Machine Image, the user does not need to be
an expert in system administration or Big Data service configuration. Our tool
dramatically reduces the time needed to provision clusters, as well as the cost
of the infrastructure. Researchers enjoy an additional benefit of having a
simple way to specify the experimental environments they use, so that their
experiments can be easily reproduced by anyone using our tool.
