Continuuity open sources Loom for devops on big data clusters

Big data application-platform Continuuity has open sourced Loom, a system for easily deploying and managing big data systems. For developers, that means a simple interface and API to launch Hadoop or other scale-out clusters.¬†Continuuity cofounder and CEO Jonathan Gray (pictured above) announced Loom at Gigaom’s Structure Data conference on Thursday.

Here’s how the company describes Loom on its GitHub page:

“Loom is cluster management software that manages clusters on public and private clouds. Clusters created with Loom utilize templates of any hardware and software stack, from simple standalone LAMP-stack servers and traditional application servers like JBoss, to full Apache Hadoop clusters comprised of thousands of nodes. Clusters can be deployed across many cloud providers (Rackspace, Joyent and OpenStack) while utilizing common SCM tools (Chef and scripts).”


As applications built using big data tools and expected to analyze lots of information proliferate, developers are going to need better tools to get the underlying resources off the ground. In that sense, Loom is potentially a very valuable tool for data scientists and anyone else who wants to work with data without getting hung up on the infrastructure. For a company like Continuuity, open sourcing Loom is theoretically good for business because developers who have a better experience launching their clusters might want to move up the stack to and use Continuuity’s application-development platform.

Loom isn’t the only open source software designed to tackle this problem. There’s another project, called Apache Mesos, that’s popular at companies such as Twitter and Airbnb, and is presently the focus of a startup called Mesosphere.