Version Control – Source Control Branch Design for Deployed Environments

With distributed SCMs like git or mercurial (which is what bitbucket uses), branching is still possible but often unnecessary. What you do instead is (basic workflow):

• Set up a repository in a location that is accessible for all developers (a network share, a server that people can ssh into, a third-party service like github or bitbucket). This will be your authoritative repository.
• Clone this repository onto each developer's machine, and do whatever you have to to create a suitable development environment.
• Work on your local copy; commit whenever you want to. Commits are local, so you won't hurt anyone. Be sure to pull from the central repo from time to time, so that your local copy doesn't go out of sync.
• When you have something you think is ready for production, push from your local clone to the central repo.
• On the central repo, whenever you have a version you want to mark as release candidate, tag it. This way, you can update any given clone to that exact version later on.

Since distributed SCMs allow unlimited clones to your repository, and each clone can serve as the master, you can build more complex workflows from this base. For example, you can have several central repositories: one for development, one for QA, one for production. You can use a dedicated clone just for a build server. You can use more than one clone locally; instead of branching, you just create another clone, and if it doesn't work out, you simply delete it.

Another nice benefit is that if the central repository breaks beyond repair, you'll still have several copies around; all you need to do is clone one developer's repo back to the central server and all is good (you do lose uncommitted changes on the central server though, but ideally, nobody should make changes there directly anyway, so the only thing left to do is for everyone to push their latest changes again).

Tracking databases is hard; normally, you want to track the structure, but not the data - data changes a lot, isn't really relevant for the code, and may contain sensitive information you better not make accessible that way. A common approach is to make a script that sets up the database in its current form, and maybe another that populates it with typical test data. Alternatively, you keep track of incremental change scripts - you'll have one script that creates the database as designed on day one, and then a bunch of scripts that, if applies in order, modify the database until you finally end up with the current state of things. Those are less reliable than tracking code changes though, and they require more manual work, so whatever you do, you want to have a good backup / restore plan for your production database.

My general take on the best practices is that any member of the development team should be able to perform any action on the tree presuming those actions don't do things like kick off a production deployment. In cases where a specific branch / tag / repository does act as a source for automated deployments putting in some reasonable change control or barriers to entry make sense, more from a keeping mistakes merely mistakes perspective than some control-freak angle. I would encourage developers to create branches and improve the build scripts. I would find ways to get developers access to production if needed. Part of the point of source control is it is an effective magic eraser of mistakes -- the worst you'll need to do is roll back a rev or two and branch off that.

Unfortunately this doesn't sound like the approach they have taken here. In order to defeat this I think you need to cover a few angles:

a) Prove that these policies are detrimental to developing things. Log all the time you spend waiting on ops to get working on something. This alone should sell reasonable management on why this is a bad policy.

b) Make some friends in Ops -- perhaps there is a reason for this policy. Perhaps that reasoning could be addressed in a more effective manner.

Hope this helps.