With this post, I’d like to start a series of CI-related tips, targeted mostly at GitLab, since that’s my go-to tool for things CI/CD-related. I’m sure most of them could be easily applied to other CI systems, though.
While GitLab does a great job at many things (repository hosting and related stuff, like MRs, pipelines, issue boards, etc.), it sometimes lacks more specialized features in some areas. With heavy usage of pipelines in my projects, I often had to look for workarounds and smart tricks. So I’d like to share some of them now, based on my experiences.
An example CI definition could look something like this:
stages: - test - build - deploy test: image: golang:1.11 stage: test script: - go test ./... - go vet ./... build: image: golang:1.11 stage: build script: - go build -o ./bin/my-app ./cmd/my-app artifacts: paths: - bin/ deploy: stage: deploy script: - ... # upload bin/ somewhere
I have some issues with using bare bash commands like this. See what happens when you need to change something in one of your jobs:
- You need to push a new commit in the application repository, triggering full pipeline for the project.
- Your changes won’t propagate to other branches, unless your commit from
masteris merged by other developers.
- Your changes will affect only this one repository. If you maintain more similar projects, you need to push the changes to all of them.
Common scripts repository
One of the things I missed when starting out with GitLab pipelines was a place for common scripts, which could be used by multiple repositories. At that time include was not yet available, but even now it hardly solves the issue for me.
Reusing parts of the YAML definition is one thing, but the other is reusing the standard scripts across all of your projects. I’d prefer things like “build app”, “package app”, “deploy app” to be one-liners in the pipeline.
I also feel that this fits nicely into the DevOps mindset: ops prepare the scripts, which are easy to use by developers. The scripts are developed using the same good practices as the application code itself: with code reviews and their own pipeline including unit tests and static checks.
I usually end up with a mix of bash and Python scripts. Bash works well for simple scripts, but for more complex stuff, going with Python (or other scripting language you like) should save you some future headaches. Python is usually easier to read by other people too, but keep in mind it may not be included in every docker image you’ll be using in your jobs.
The idea is pretty simple: fetch the scripts repository every time a job is run.
This should be as simple as adding global settings in your
variables: SCRIPTS_REPO: https://gitlab.com/threedotslabs/ci-scripts before_script: - export SCRIPTS_DIR=$(mktemp -d) - git clone -q --depth 1 "$SCRIPTS_REPO" "$SCRIPTS_DIR"
You could also move the variables to the project’s CI/CD variables. Or
include this config from
another location. Or use your own docker images with the scripts repository baked in and run
git pull in it.
The basic idea stays the same.
Let’s say you have a bunch of Golang applications and you’d prefer to have a consistent build process for all of them.
Why would you want it, when a simple
go build should be enough? For example, you might want to bake the version number
into every one of your services: it’s usually useful to know which version you’re running! Putting
that into a common script ensures that none of your applications will skip this step.
In the next post, I’ll show you how to generate semver versions for commits. For now, we’ll stick with git commit hash as our version number.
#!/bin/bash # Build generic golang application. # # Example: # build-go cmd/server example-server pkg.version.Version set -e if [ "$#" -ne 3 ]; then echo "Usage: $0 <package> <target_binary> <version_var>" exit 1 fi readonly package="$1" readonly target_binary="$2" readonly version_var="$3" readonly bin_dir="$CI_PROJECT_DIR/bin/" mkdir -p "$bin_dir" go build -ldflags="-X $version_var=$CI_COMMIT_SHA" -o "$bin_dir/$target_binary" "$package"
This script expects that the resulting binary will be kept in the
bin directory. It’s just another
thing you might want to have consistent across repositories.
This script should be put in your scripts repository.
Don’t forget to set the execute permissions (
The last thing you need to do is use the script in your application repository:
build: image: golang:1.11 stage: build script: - $SCRIPTS_DIR/golang/build . example-server main.Version artifacts: paths: - bin/
And this is it! Your scripts should now always be up-to-date across your repositories. Of course this setup won’t make much sense if you’re using just one repository, so keep that in mind. Don’t overcomplicate it, if you can.
Using deploy tokens is a bit easier, so let’s see it in action.
- In the scripts repository: generate new deploy token. You’ll find it in the
Settings -> Repository -> Deploy tokenssection.
- In the application repository: add the generated user and token as new variables called
SCRIPTS_TOKEN. You can do this in the
Settings -> CI / CD -> Variablessection.
- Modify the
SCRIPTS_REPOvariable in your application CI definition:
variables: SCRIPTS_REPO: https://$SCRIPTS_USER:$SCRIPTS_TOKEN@gitlab.com/threedotslabs/ci-scripts
Testing the changes
If you’ve worked with multiple repositories before, you should already know that it adds some
synchronization overhead. For example, pushing a broken script to the
master branch could break builds
in all your projects. That’s why code reviews and unit tests are very much welcome.
If unit testing the scripts is hard or just not possible, you could try testing them on branches
first, before merging to
master. You would just need to checkout to the chosen branch after cloning.
What’s cool, you can retry the failed job this way just after pushing changes to the script, without running the
complete pipeline again.
What about Makefiles?
Moving all bash commands to
Makefile can tidy up your CI definition and allows developers to run the
same checks and tests that will be run in the pipeline. For example, you could introduce
target that will run unit tests,
make lint for static checks and so on.
Sadly, this will mean duplicating the
Makefile across all your repositories and it doesn’t really
solve the issues mentioned above. Makefiles also have their own quirks, so better make sure you know
what you’re doing or you might run into unexpected issues (e.g. silently passing on errors).
While the script we’ve used is really trivial, this shows how this integration can be used for keeping all CI-related scripts in one place. I’ll show more advanced examples in the next posts, so stay tuned!
If you have any questions or you’d like to share other ideas for similar workflow, hit me on Twitter.Follow @m1_10sz