Question

We are developing a distributed application in Python. Right now, we are about to re-organize some of our system components and deploy them on separate servers, so I’m looking to understand more about deployment for an application such as this. We will have several back-end code servers, several database servers (of different types) and possibly several front-end servers.

My question is this: what / which are good deployment patterns for distributed applications (in Python or in general)? How can I manage pushing code to several servers (whose IP’s should be parameterized in the deployment system), static files to several front ends, starting / stopping processes in the servers, etc.? We are looking for possibly an easy-to-use solution, but mostly, something that once set-up will get out of our way and let us deploy as painlessly as possible.

To clarify: we are aware that there is no one standard solution for this particular application, but this question is rather more geared towards a guide of best practices for different types / parts of deployment than a single, unified solution.

Thanks so much! Any suggestions regarding this or other deployment / architecture pointers will be very appreciated.

Answer 1

It all depends on your application.

You can:

• use Puppet to deploy servers,
• use Fabric to remotely connect to the servers and execute specific tasks,
• use pip for distributing Python modules (even non-public ones) and install dependencies,
• use other tools for specific tasks (such as use boto to work with Amazon Web Services APIs, eg. to start new instance),

It is not always that simple and you will most likely need something customized. Just take a look at your system: it is not so “standard”, so do not expect it to be handled in a “standard” way.