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How to Deploy Software

Make your team’s deploys as boring as hell and stop stressing about it.

By: Zach Holman

Let's talk deployment

Whenever you make a change to your codebase, there's always going to be a risk that you're about to break something.

No one likes downtime, no one likes cranky users, and no one enjoys angry managers. So the act of deploying new code to production tends to be a pretty stressful process.

It doesn't have to be as stressful, though. There's one phrase I'm going to be reiterating over and over throughout this whole piece:

Your deploys should be as boring, straightforward, and stress-free as possible.

Deploying major new features to production should be as easy as starting a flamewar on Hacker News about spaces versus tabs. They should be easy for new employees to understand, they should be defensive towards errors, and they should be well-tested far before the first end-user ever sees a line of new code.

This is a long — sorry not sorry! — written piece specifically about the high-level aspects of deployment: collaboration, safety, and pace. There's plenty to be said for the low-level aspects as well, but those are harder to generalize across languages and, to be honest, a lot closer to being solved than the high-level process aspects. I love talking about how teams work together, and deployment is one of the most critical parts of working with other people. I think it's worth your time to evaluate how your team is faring, from time to time.

A lot of this piece stems from both my experiences during my five-year tenure at GitHub and during my last year of advising and consulting with a whole slew of tech companies big and small, with an emphasis on improving their deployment workflows (which have ranged from "pretty respectable" to "I think the servers must literally be on fire right now"). In particular, one of the startups I'm advising is Dockbit, whose product is squarely aimed at collaborating on deploys, and much of this piece stems from conversations I've had with their team. There's so many different parts of the puzzle that I thought it'd be helpful to get it written down.

I'm indebted to some friends from different companies who gave this a look-over and helped shed some light on their respective deploy perspectives: Corey Donohoe (Heroku), Jesse Toth (GitHub), Aman Gupta (GitHub), and Paul Betts (Slack). I continually found it amusing how the different companies might have taken different approaches but generally all focused on the same underlying aspects of collaboration, risk, and caution. I think there's something universal here.

Anyway, this is a long intro and for that I'd apologize, but this whole goddamn writeup is going to be long anyway, so deal with it, lol.

Table of Contents

  1. Goals

    Aren't deploys a solved problem?

  2. Prepare

    Start prepping for the deploy by thinking about testing, feature flags, and your general code collaboration approach.

  3. Branch

    Branching your code is really the fundamental part of deploying. You're segregating any possible unintended consequences of the new code you're deploying. Start thinking about different approaches involved with branch deploys, auto deploys on master, and blue/green deploys.

  4. Control

    The meat of deploys. How can you control the code that gets released? Deal with different permissions structures around deployment and merges, develop an audit trail of all your deploys, and keep everything orderly with deploy locks and deploy queues.

  5. Monitor

    Cool, so your code's out in the wild. Now you can fret about the different monitoring aspects of your deploy, gathering metrics to prove your deploy, and ultimately making the decision as to whether or not to roll back your changes.

  6. Conclusion

    "What did we learn, Palmer?"
    "I don't know, sir."
    "I don't fuckin' know either. I guess we learned not to do it again."
    "Yes, sir."

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