Hey everyone! 👋
I've spent the last year neck-deep in CI/CD for my team, and we just wrapped up a full 12-month cost analysis of GitHub Actions. We’re a team of about 10 engineers, with a mix of backend (Node.js, Python), some data pipelines, and a few microservices. When we started, the promise was simple: “It’s right there in your repo, just use it!” But as our monthly commit count and PRs grew, so did that line item from GitHub. I wanted to share our real numbers, our migration pitfalls (because of course I tried to optimize!), and whether I think it’s ultimately worth it.
**Our Usage Profile (The “What We Actually Did”):**
* **Repos:** ~25 active repositories
* **Workflow runs:** Averaged 2,800 runs/month by year’s end
* **PR builds:** Standard test suite on every push.
* **Scheduled jobs:** Nightly data aggregation and integrity checks (PostgreSQL & MongoDB).
* **Deployments:** Staging on every merge to main, production deployments tagged (~50/month).
* **Key point:** We used a mix of Ubuntu, Windows (for some legacy .NET), and macOS (for iOS builds) runners. The macOS minutes **hurt**.
**The Raw Invoice Breakdown:**
GitHub Actions pricing is based on compute minutes, and the included free minutes (3,000 per month for our GitHub Team plan) vanished in the first week. Here’s a snapshot from our peak month (last month):
| Runner Type | Minutes Used | Cost (USD) |
| :--- | :--- | :--- |
| **Ubuntu** | 42,500 | $127.50 |
| **macOS** | 7,200 | $375.00 |
| **Windows** | 3,100 | $155.00 |
| **Total** | **52,800** | **$657.50** |
That’s **~$660 for one month**. Over 12 months, our total spend was **$5,842.16**. Ouch.
**The Optimization Rabbit Hole (A Migration Story):**
I couldn't just accept that. My database-migration brain kicked in. We tried two things:
1. **Self-hosted runners on our own cloud VMs:** This *drastically* cuts cost for Ubuntu workloads. We set up a couple of `c5a.xlarge` EC2 instances as runners. The config in the repo is simple:
```yaml
jobs:
build:
runs-on: [self-hosted, linux, x64]
```
**Pitfall:** You now own the maintenance, security updates, and scaling. A misconfigured runner cache filled our disk and failed builds. The cost saving was real (~60% cheaper for Linux minutes), but it added operational overhead.
2. **Job Summarization & Caching:** We aggressively cached dependencies and made workflows share artifacts. This cut our average Linux job time from 8 mins to ~4. A must-do.
**The Verdict: Is it Worth It?**
For our **10-engineer team**, I’m going to say **yes, but with caveats**.
The **convenience and integration** are phenomenal. The context switching of moving to another CI tool has a real, hard-to-quantify cost. The matrix builds, the actions marketplace, and the secret management being right there... it speeds up development.
However, **you MUST optimize**:
* **NEVER use hosted macOS/Windows for heavy workloads.** Find an alternative or use self-hosted.
* **Cache everything.** It’s free savings.
* **Set spending limits** and alert on them immediately.
If you have a mostly Linux-based stack and higher engineering bandwidth to manage infra, a hybrid model (self-hosted for Linux, GitHub-hosted for macOS/Windows niche jobs) is the financial sweet spot. For us, the hybrid model brought our average monthly cost down to around ~$300, which feels palatable for the productivity gain.
I’d love to hear if others have done similar deep dives. What’s your burn rate look like, and have you found a better balance?
—B
Backup first.