After six months of migrating our team's primary monorepo pipeline from GitLab CI to GitHub Actions, I've compiled concrete performance data. The context: a Node.js/Python monorepo with ~50 services, building Docker images and running integrated test suites. Our GitLab CI configuration was mature, but we were compelled by ecosystem alignment.
The most significant metric was pipeline duration. Using comparable runner specs (4 vCPU, 8GB RAM) on self-hosted infrastructure, the average pipeline time decreased by approximately **18%**. The improvement wasn't uniform across stages:
* **Dependency Caching:** GitHub Actions' `actions/cache` proved more effective for our `node_modules` and Python virtualenv layers. The restore speed was comparable, but cache hit rates increased due to finer-grained key strategies.
* **Docker Layer Caching:** This was a clear win. The `docker/build-push-action` with the `cache-from` and `cache-to` options provided more deterministic layer reuse than our GitLab CI `docker build` setup.
* **Job Startup Overhead:** GitHub Actions jobs exhibited lower initialization latency on our self-hosted runners, roughly 5-10 seconds faster per job.
However, configuration verbosity increased. A comparable build stage:
**GitLab CI (simplified)**
```yaml
build:
stage: build
image: docker:20.10
services:
- docker:20.10-dind
script:
- docker build --cache-from $CI_REGISTRY_IMAGE:latest --tag $CI_REGISTRY_IMAGE:$CI_COMMIT_SHA .
- docker push $CI_REGISTRY_IMAGE:$CI_COMMIT_SHA
```
**GitHub Actions**
```yaml
- name: Build and push
uses: docker/build-push-action@v4
with:
context: .
push: true
tags: |
${{ env.REGISTRY }}/${{ github.event.repository.name }}:${{ github.sha }}
cache-from: type=registry,ref=${{ env.REGISTRY }}/${{ github.event.repository.name }}:latest
cache-to: type=inline
```
The performance gains are tangible, but the trade-off is a more fragmented configuration syntax relying on composite actions. For teams deeply integrated into the GitHub ecosystem, the performance boost and seamless PR integration justify the migration. For others, the complexity of rewriting pipelines may outweigh these benefits.
--crusader
Commit early, deploy often, but always rollback-ready.
Hey, great data, thanks for sharing. I'm Isla, and I work on the content platform team for a mid-sized e-commerce company. We run a similar stack - Node.js microservices in a monorepo, with a big emphasis on fast Docker builds and integrated tests - so this hits home.
A few things I'd add from our own migration last year:
**Cost Structure Shifts**: Our spend moved, even on self-hosted runners. GitLab's per-user licensing was a fixed cost; GitHub's model felt more variable. We saw a 10-15% increase in auxiliary cloud storage costs for artifacts and packages because of how we structured our caching.
**Configuration Mental Load**: GitHub Actions YAML is more verbose for complex workflows. A matrix build that took 20 lines in GitLab CI could balloon to 50+ lines in Actions. The trade-off is finer control, but the maintenance overhead is real.
**Secret Management**: GitHub's organization secrets are fine, but environment-scoped secrets felt less granular than GitLab's. We had to implement a couple of workarounds for service-specific keys, adding a bit of custom scripting.
**Ecosystem Integration**: This was the big win for us. The direct integration with the GitHub API and marketplace actions for things like Slack alerts or Jira updates cut our "glue code" by maybe 30%. If you live in the GitHub universe, that alignment is powerful.
My pick depends heavily on where your team already lives. For a team deeply embedded in GitHub for issues and code review, I'd recommend Actions for the ecosystem cohesion alone. If the team's main pain point is complex pipeline logic or they use GitLab's built-in container registry heavily, staying put might be better. Could you share your team size and whether you're using GitHub Enterprise or GitLab Premium? That would clarify the call.
Words matter
You're blaming the tool for a 10-15% cost increase, but that's just your caching strategy being lazy. I've seen people burn money on Actions artifacts because they treat it like S3. GitLab's per-user cost is a tax on headcount, not a feature.
And the YAML verbosity thing? If you're writing 50 lines for a matrix build, you're probably doing it wrong. Actions has reusable workflows and composite actions. Or maybe you just miss the spaghetti of GitLab's include blocks.
What's the real pain point?
Wow, thanks for sharing all that data! I'm just starting to learn CI/CD and this kind of comparison is super helpful. The 18% drop in pipeline time sounds huge.
I'm still wrapping my head around caching strategies. Could you explain a bit more what you meant by "finer-grained key strategies" for the `actions/cache`? Like, did you hash specific files or use a combination of lockfile and OS version? I'm trying to figure out what works best for a small Node project I'm playing with, and any tips would be awesome.
Great question about the caching keys. The "finer-grained" part often means your cache key can be built from more specific inputs. While you can just use the hash of your lockfile, you can also include things like the OS, Node version, and even parts of your package.json.
For a small Node project, start simple. A key like `node-cache-${{ hashFiles('package-lock.json') }}-${{ runner.os }}` is solid. It'll create a new cache when your lockfile changes or you switch OS. The real power is in using a "restore-keys" fallback strategy, like trying to find a cache for just the OS if your exact lockfile hash isn't found. That can still save you some install time.
What's been your experience so far with caching?
— Jane