Automation is one of the best ways to improve productivity. Even as a
development team of one, spending a bit of time on DevOps and improving your
developer quality of life can pay off immensely.
Automated tasks strip away cognitive load. No more forgetting to deploy code
because the process was manual and easy to forget. Take it a step further with
automated linting and testing.
With platforms like GitLab aiming to make it dead simple to build out automated
pipelines, it’s never been easier. You don’t even need any specialized software,
shell scripts and a bit of Linux knowledge is more than enough to implement a
full and complete continuous integration and deployment pipeline.
When I approach building out a new SaaS product, the stack of services tends to
look like this:
- Static [marketing] website (
www
) running on Jekyll. - Front-end application (
app
) with React (TypeScript). - Back-end API (
api
) using Express (also TypeScript).
Each of these “services” lives in a monorepo under the directories api
, app
and www
. No dependencies are shared between them and each can be deployed
independently of the rest if I felt so inclined to do so.
At the very earliest stage, I host all of these “services” on a single machine,
each with a slightly different build process. If there are database concerns, I
will throw in a separate server for that, which makes it easier to split out the
services down the road if/when that day comes.
So with these three different parts to the project, there are a few separate
steps that need to take place to go from code in the repository to deployed
application:
- Dependencies need to be installed.
- The code needs to be linted (
app
andapi
only). - The test suite needs to be run (same deal,
app
andapi
only). - The project needs to be built.
- The built code needs to be copied to the server.
- Services need to be bounced (
pm2
in this case). - Caches need to be reset (usually just Cloudflare CDN).
- Old builds should be removed.
Quite a few steps, especially if you’re doing it manually as some of those steps
have to be done 2-3 times depending on the services that it applies to.
The aforementioned steps can easily be grouped up 3 or so stages and with
GitLab’s parallelization of stages, can be broken out further to isolate each
service that we’re working with:
- Build
- Install dependencies and build the
www
. - Install dependencies and build the
app
. - Install dependencies and build the
api
.
- Install dependencies and build the
- Test
- Lint and run tests for the
app
. - Lint and run tests for the
api
.
- Lint and run tests for the
- Deploy
- Copy code to the server:
* Copy the build for thewww
.
* Copy the build for theapp
.
* Copy the build for theapi
. - Link to the new build:
* Link to the new build for thewww
.
* Link to the new build for theapp
.
* Link to the new build for theapi
. - Reload
pm2
to start serving the new build of theapi
. - Purge the Cloudflare CDN cache.
- Clean up builds older than 30 days old.
You very well could run this all in a single stage, but I find that it’s a ton
easier to track down issues when you have things abstracted out, even if it’s
going to take a bit longer due to bringing up new containers for each step.
You may be wondering why I’m not bouncing a web server as part of this flow. In
my experience, the web server (in my case, nginx
) tends to need updated pretty
rarely, especially after the initial paths are configured and such. I also try
to avoid doing any super user actions in my automated deployments (in this case,
using systemctl
). Call it paranoia if you want, but I’d much rather that my
automated deployments don’t have said elevated privileges, just in case of a
breach.
Before getting into the meat and potatoes of my .gitlab-ci.yml
file, I want to
discuss a few of the assumptions that I have baked in here.
First, I use a directory structure like this for releases:
/home/username/releases
├── api
│ ├── 20200221194212-5ab009659b110c534bbc8a30abb9f418f4b150df
│ ├── 20200221201443-258e011dd4524e4ba25268593ab1051c6a7c95ef
│ └── current -> /home/username/releases/api/20200221201443-258e011dd4524e4ba25268593ab1051c6a7c95ef
├── app
│ ├── 20200221194212-5ab009659b110c534bbc8a30abb9f418f4b150df
│ ├── 20200221201443-258e011dd4524e4ba25268593ab1051c6a7c95ef
│ └── current -> /home/username/releases/app/20200221201443-258e011dd4524e4ba25268593ab1051c6a7c95ef
└── www
├── 20200221194212-5ab009659b110c534bbc8a30abb9f418f4b150df
├── 20200221201443-258e011dd4524e4ba25268593ab1051c6a7c95ef
└── current -> /home/username/releases/www/20200221201443-258e011dd4524e4ba25268593ab1051c6a7c95ef
This gives me a pretty solid structure for the inevitable day when one of the
services needs moved to a new box / cluster. Nothing is shared between the
services and that’s a great thing.
The other set of assumptions has a lot to do with my development stack choices
as a whole. I build things with Node.js and React leveraging TypeScript. I
prefer static websites to WordPress installs. That’s all just my thing, you can
apply this same pipeline to your current choices, just tweak things where it’s
appropriate.
In terms of server software, I use pm2
for the api
service and have nginx
proxying back to it, while also serving the www
and app
build directly. I
don’t want to get weighed down with discussing every single configuration file
in this post, and focus more on the pipeline itself, so YMMV if you don’t have
your server configured yet.
In terms of configuration, staying true to The Twelve-Factor App, my
.gitlab-ci.yml
file doesn’t contain any secrets or anything of that nature.
For that stuff, I am using GitLab’s CI/CD variables (masked when possible).
The variables needed to use this particular pipeline are as follows:
CLOUDFLARE_AUTH_EMAIL
– Authentication email for Cloudflare.CLOUDFLARE_AUTH_KEY
– Authentication key / token for Cloudflare.CLOUDFLARE_ZONE_ID
– Zone ID for the site in Cloudflare.SSH_HOSTNAME
– Hostname / IP Address for the server.SSH_PORT
– Port number for the server.SSH_PRIVATE_KEY
– Private key for the deploy user on the server.SSH_USERNAME
– Username of the deploy user on the server.
In the past I’ve also carried around a variable with the known hosts to drop
into the SSH configuration, but have since dropped that in favor of some
additional configuration to skip the name check. In my own experience, most of
the time I would bork the known hosts data the first time or so, so it’s always
been a pain point to manage for me.
For the sake of speed, and to keep each stage of the process isolated in it’s
intent, I am leveraging artifacts to carry the build
and node_modules
between each step in the process.
To help manage configuration files, I keep them in the repository, but had to be
mindful to copy those files into the build directory to ensure they were
deployed with the rest of the build.
Outside of the dependencies, the only other thing that this pipeline needs to
run is curl
, openssh-client
and rsync
. Of course, if you don’t need to
purge anything from Cloudflare, you could even drop curl
since that’s the only
thing using it.
In the past I would use curl
to talk to slack to let me know about the status
of the deployment, but have since opted to use GitLab’s Slack integration
instead of maintaining any of that myself.
Also worth noting, the build
and test
stages both are configured to run on
every branch (which the status shows up on merge requests) but will only deploy
when on the master
branch.
So after quite a bit of tweaks, and many failed builds and deploys, here’s the
final product (at the time of this writing, at least ;):
image: node:13
stages:
- build
- test
- deploy
variables:
CI: "true"
GIT_STRATEGY: clone
build_api:
stage: build
artifacts:
paths:
- ./api/build
- ./api/node_modules
script:
- cd api
- npm install
- npm run build
- cp {ecosystem.config.js,nginx.conf} build
- cp -R node_modules build/
build_app:
stage: build
artifacts:
paths:
- ./app/build
- ./app/node_modules
script:
- cd app
- npm install
- npm run build
- cp nginx.conf build
build_www:
image: jekyll/jekyll:4.0
stage: build
variables:
JEKYLL_ENV: production
artifacts:
paths:
- ./www/_site
script:
- cd www
- bundle config set path '.bundle'
- bundle install
- bundle exec jekyll build
- cp nginx.conf _site
test_api:
stage: test
services:
- mongo
script:
- cd api
- npm run lint
- npm run test
test_app:
stage: test
script:
- cd app
- npm run lint
- npm run test
deploy:
stage: deploy
only:
- master
before_script:
- RELEASE="$(date +%Y%m%d%H%M%S)-$CI_COMMIT_SHA"
- RELEASES_DIR="/home/$SSH_USERNAME/releases"
- API_RELEASE_DIR="$RELEASES_DIR/api/$RELEASE"
- API_CURRENT_DIR="$RELEASES_DIR/api/current"
- APP_RELEASE_DIR="$RELEASES_DIR/app/$RELEASE"
- APP_CURRENT_DIR="$RELEASES_DIR/app/current"
- WWW_RELEASE_DIR="$RELEASES_DIR/www/$RELEASE"
- WWW_CURRENT_DIR="$RELEASES_DIR/www/current"
- apt-get update
- apt-get install -y curl openssh-client rsync
- eval $(ssh-agent -s)
- echo "$SSH_PRIVATE_KEY" | tr -d 'r' | ssh-add - > /dev/null
- mkdir -p ~/.ssh && chmod 700 ~/.ssh
- echo -e "Host *ntStrictHostKeyChecking nonn" > ~/.ssh/config
script:
- >
rsync -avz -e "ssh -p $SSH_PORT"
./api/build/ "$SSH_USERNAME@$SSH_HOSTNAME:$API_RELEASE_DIR"
- >
rsync -avz -e "ssh -p $SSH_PORT"
./app/build/ "$SSH_USERNAME@$SSH_HOSTNAME:$APP_RELEASE_DIR"
- >
rsync -avz -e "ssh -p $SSH_PORT"
./www/_site/ "$SSH_USERNAME@$SSH_HOSTNAME:$WWW_RELEASE_DIR"
- >
ssh -A "$SSH_USERNAME"@"$SSH_HOSTNAME" -p "$SSH_PORT"
ln -nsf "$API_RELEASE_DIR" "$API_CURRENT_DIR"
- ssh -A "$SSH_USERNAME"@"$SSH_HOSTNAME" -p "$SSH_PORT" pm2 reload api
- >
ssh -A "$SSH_USERNAME"@"$SSH_HOSTNAME" -p "$SSH_PORT"
ln -nsf "$APP_RELEASE_DIR" "$APP_CURRENT_DIR"
- >
ssh -A "$SSH_USERNAME"@"$SSH_HOSTNAME" -p "$SSH_PORT"
ln -nsf "$WWW_RELEASE_DIR" "$WWW_CURRENT_DIR"
after_script:
- >
curl -s -X DELETE
"https://api.cloudflare.com/client/v4/zones/$CLOUDFLARE_ZONE_ID/purge_cache"
-H "X-Auth-Email: $CLOUDFLARE_AUTH_EMAIL"
-H "X-Auth-Key: $CLOUDFLARE_AUTH_KEY"
-H "Content-Type: application/json"
--data '{"purge_everything":true}'
- >
ssh -A "$SSH_USERNAME"@"$SSH_HOSTNAME" -p "$SSH_PORT"
find $RELEASES_DIR/{api,app,www} -mindepth 1 -maxdepth 1
-type d -mtime +30 -exec rm -rf {} +
Honestly not much to it. If you wanted to deploy to multiple servers, you just
need to tweak things a bit, either running through a list of IP addresses or
breaking the deploy
stage apart. Still want the after_script
clean up to run
after all of your deploys
can finished, simply move that to the .post
stage!
I’m sure at least somebody out there is saying to themselves “this is great, but
how do you manually deploy stuff, Josh?”. Simply put, I don’t. I know there are
edge cases that come up that require getting your hands dirty, but I don’t ever
want to make that a habit, so I simply avoid it entirely by not giving myself a
way to deploy outside of the CI/CD pipeline.
Maybe that’s not for everybody, and definitely eliminates doing manual deploys
to a staging environment, but that’s just how I work. In most cases, when I do
need to work in some sort of manual flow, I try to automate that as well, just
because I’d rather spend a bit more time up front, than recurring time recalling
stuff from my mental archives because the information doesn’t get used to often.
Of course, this pipeline is pretty opinionated in terms of how code is
structured and how it’s shipped to production. Doesn’t mean that I’m averse to
comments, if anything seems off, or you have a better way to go about something
I’m doing here, by all means, drop me a comment!