Ferry lets you define, run, and deploy big data stacks on your local machine using Docker.

Ferry currently supports Hadoop/Yarn, GlusterFS/OpenMPI, and Cassandra (with more in the future). By using Ferry developers can get started creating their big data applications right away without the pain of installing and configuring all the complex backend software.

Big data technologies are designed to operate and scale over many machines and usually consist of multiple functional parts. Developers interested in creating a Hadoop application, for example, must first download the appropriate packages, configure these systems to operate in a single-machine environment (or multiple machines for operational environments), and configure other required services (e.g., PostGresql).

Fortunately for us, Ferry and Docker vastly simplifies the entire process by capturing the entire process in a set of lightweight Linux containers. This enables developers to quickly stand up a big data stack and attach connectors/clients with zero manual configuration. Because Docker is so lightweight, you can even test multiple big data stacks with minimal overhead.

Ferry is a Python application and runs on your local machine. All you have to do to get started is have docker installed and type the following pip install -U ferry. Afterwards you can start creating your big data application. Here's an example stack:

{
  "backend":[
   {
    "storage":
        {
  	   "personality":"gluster",
  	   "instances":2
	},
    "compute":[
	{
	  "personality":"mpi",
	  "instances":2
	}]
   }],
  "connectors":[
	{"personality":"mpi-client"}
  ]
}

This stack consists of two GlusterFS data nodes, and two OpenMPI compute nodes. There's also a Linux client that automatically connect to those backend components. To create this stack, just type ferry start openmpi. Once you create the stack, you can log in by typing ferry ssh sa-0.

More detailed installation instructions and examples can be found here.

Ferry leverages some awesome open source projects:

• Docker simplifies the management of Linux containers
• Python programming language
• Hadoop is a general-purpose big data storage and processing framework
• GlusterFS is a parallel filesystem actively developed by Redhat
• OpenMPI is a scalable MPI implementation focused on modeling & simulation
• Cassandra is a highly scalable column store
• PostGresql is a popular relational database