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Machinery

Machinery

EASILY CONTROL ENTIRE

DOCKER MACHINE BASED CLUSTERS

machinery is a command-line tool to operate on a whole cluster of Docker Machine virtual machines. machinery uses a YAML definition of the whole cluster to create machines, bring them up or down, or remove them at will. In addition, machinery provides Docker Swarm and Compose integration. It will automatically arrange for the created virtual machines to join the swarm cluster, generate the token as needed or even manage the life-cycle of several compose projects to be run on the cluster.

CENTRAL CONTROL

 

The YAML cluster definition file provides a clear view of all involved machines, but also their properties, location, images, core components, etc.

EASY VOCABULARY

 

Machinery provides a few, easy to remember, sub-commands to manage the machines in the cluster: with a few up, restart, destroy, swarm, your whole cluster will be up and running and dimensioned to your needs.

DISCOVERY

 

Through the provision of a central controlling point, machinery eases discovery. It will automatically set up a number of environment variables that you can use for direct service discovery or to initiate more advanced tools such as etcd or SkyDNS.

SWARM

 

Machinery makes it easy to associate labels to your machine and to use them to start components where you want. It also provides sub-commands to start few or many components through swarm.

machinery provides you with an at-a-glance view of your whole cluster, from all the (virtual) machines that build it up, to all the components that should be run, and on which machine(s).

OPEN SOURCE

 

Machinery is open source under a liberal license, you are free to use it in your projects without restrictions.

DOCUMENTATION

 

The documentation provides both a quick tour and a complete description of all features.

SOLUTIONS

 

Soon, this site will contain a number of examples and guides for a better understanding of machinery.

SCRIPTING

 

Machinery is coded in a scripting language to ease understanding but also quickly patch problems when they occur.

ISSUES

 

Machinery is hosted on github and benefits from its issue tracking facilities.

Copyright © 2015, Emmanuel Frécon