The post is interesting, but it doesn't mention two major difficulties: zero downtime deploys and database migrations.
As far as database migrations are concerned, GitHub (and others, of course) takes the perspective of migrating before the code that uses those migrations go out. In other words, as @herge says in a sibling comment, the code that gets pushed needs to support two branches of code and two branches of data simultaneously. It's certainly some extra work (and can be pretty gnarly depending on the scope of the migration), but once you get to a certain point it's kind of the only way to do no-downtime migrations.
There's many possibilities to help with the actual migration process, depending on what database you're using. With MySQL, for example, you can do something like the process in lhm: https://github.com/soundcloud/lhm
Zero-downtime deploys aren't super difficult in Rubyland anymore (many have written how they achieve it in Unicorn, for example), although I'm not as familiar with how other folk do it across other languages and platforms these days.
...well, once someone says it out loud. :)
After that, of course it makes sense that they would have a need for an API compatibility window across at least two versions. It's exactly the same issues as supporting a backend and client side where you can't instantaneously force an update to all clients. With your DB, you're in control of the version, but you're certainly not in control of making it "instantaneously", so the same rules apply as when you're waiting for some curmudgeon user to update: API versioning and a support window.
Now, if only we had an automagic way to make it less painful for a project to support two different versions of an API from the same codebase....
If we are trying to deploy migration #1, first deploy a version B of the code that supports (but provides the same set of features as before) the db both after migration #1 and before migration #1 (maybe with the help of a feature flag that is set in the migration). Do the migration. The deploy a version C of the code which removed the feature check above. But all this requires 2 different versions of the code and a lot of process just to ship out one migration. It gets combinatorically worse if you have more than one migration to deploy.
Zero (no crash) downtime deployments seems like too much effort for too little gain.
That and some other methods are described in a post on the Yelp engineering blog[1].
1: http://engineeringblog.yelp.com/2015/04/true-zero-downtime-h...
If you can, always make migrations backwards compatible with the previous version of the code, so they don't need to be rolled back if the code needs to be rolled back. Having a good migration rollback procedure is nice too, but usually unnecessary if testing has gone well.
If you need to add a new field to the model then always create it as nullable, whether or not you use a default value. That'll allow this particular database migration to run on previous versions of the code. You can test this by generating the migration SQL and running it on the database for your test/dev environment which is running your current production code.
Once the new code and migration is running in production and you're satisfied with it, immediately create a new change which makes the previous migration more strict (remove nullable, use a data migration or default value for existing nulls). Test, stage, deploy that.
Having backwards compatible migrations leads into zero downtime deploys also. Once the data migration has run, your app servers can be running version X or X-1. Before you push new code to a node, do a graceful shutdown (allowing queued requests to complete) or remove the node from the cluster (haproxy socket api for example), update the code, bring the node back into the cluster.
Caveats:
- not all database migrations can be backward compatible, but most can be made so by breaking your change into two or more changes. First - make the change without strict integrity checks. Second, enforce integrity checks and provide defaults.
- zero downtime deploys requires multiple nodes (counter example would be welcome, but I can't think of one).
I would have agreed with you before working at GitHub, but the end result is that deploying is so easy that 3 deploys does not feel like "a lot of process." On most of our applications I can do this in 15 minutes or less.
[1] http://www.se-radio.net/2012/06/episode-186-martin-fowler-an...