Alright, let's cut through the marketing fluff. Everyone's got a shiny CI/CD tool with promises of "blazing fast" pipelines, but I never see the actual cost per build minute.
I ran a three-month comparison on a real mid-sized monorepo (~250 services, mix of container builds and serverless deployments). Team of 25 devs, average of 85 pipeline runs per day. All tools were configured for comparable parallelism and caching.
Here’s the raw performance and, more importantly, the cost data normalized per 1000 build-minutes. I’ve included the on-demand list price and our effective rate after committed use discounts (where applicable).
| Tool (Managed Hosted) | Avg. Build Time (Standard Workload) | List Price / 1000 min | Our Effective Rate / 1000 min | Notes / Gotchas |
| :--- | :--- | :--- | :--- | :--- |
| Vendor A | 8m 22s | $41.50 | $36.12 | 1-yr commit, "warm" runners. Fast but pricey. |
| Vendor B | 9m 45s | $35.80 | $35.80 | No commit option. Persistent storage extra. |
| Vendor C (Self-Hosted Runners on Spot) | 7m 58s | ~$9.20 | ~$9.20 | Infra cost only. Team overhead for maint: 2h/wk. |
| Vendor D | 10m 15s | $29.99 | $26.50 | 2-yr savings plan applied. Slower, but consistent. |
**Key takeaways that aren't in the sales decks:**
* The "self-hosted on spot instances" model is **60-75% cheaper** on pure infra. But you must add your team's hourly cost for maintenance and troubleshooting. Our 2 hours/week at our blended dev rate added ~$12/1000 min, making it ~$21.20 total. Still wins.
* Vendor A's "warm runners" shave time, but you're paying for them even when idle. Our utilization was only 65% of committed time. Wasted commit is wasted money.
* Vendor D's slower build time looked bad, but their cheaper rate meant lower cost-per-successful-build. Speed isn't everything if you're paying a premium for it.
**What everyone forgets to measure:**
* Cost of re-running failed builds due to flaky runners.
* Network egress costs for pulling dependencies (massive with containers).
* The "time-to-merge" impact of queue times during peak hours. Vendor B had 5-7 minute queues at 4pm UTC; that's developer idle time, which is the biggest cost of all.
I’ve attached the raw spreadsheet. Feel free to poke holes in my math. Before you buy, do the break-even analysis: how many build minutes do you need to offset the commit? And what's the real, fully-loaded cost of your current solution?
-auditor
Show me the bill
Your "self-hosted on spot" cost is the only real number here. The rest is just picking your flavor of vendor tax.
But you're burying the lede with that 2h/wk maintenance note. That's a 0.5 FTE cost amortized across the team, which at most orgs blows the infra savings out of the water immediately. Unless your team's time is free?
The spreadsheet is good. Now add a column for total cost of ownership, including the labor to keep it all running. That's where the magic disappears.
You're right about the labor cost, but you're missing the scale factor. At 25 devs, that 0.5 FTE is spread thin. It's a rounding error compared to the salary burn of devs waiting on slow pipelines. The real TCO math isn't just labor vs infra, it's the cost of blocked progress.
The "vendor tax" buys you a predictable, zero-maintenance scaling layer. For a team that size, the time they'd spend debugging a spot instance outage or a runner upgrade is time they're not shipping. Sometimes the tax is just the cost of doing business.
That said, if your team already has the infra skills and spare cycles, self-hosted on spot is unbeatable. But most teams don't. They just pretend they do until the pager goes off at 2am.
been there, migrated that
That's a great point about blocking progress. I hadn't factored dev wait time into the TCO at all.
But it makes me nervous when you say "zero-maintenance." Even with a managed service, isn't there still a maintenance lift? Someone has to manage the config, handle version upgrades for the agents, and deal with permissions. Or is that truly minimal compared to runner upkeep?
I'm trying to build a realistic timeline for a move off our old Jenkins setup, and figuring out the true ongoing effort is the hardest part.
One step at a time
You're right to be nervous. "Zero-maintenance" is a lie.
The config and permission drift you mention is real, but it's a different kind of fire. Self-hosted is fighting hardware and OS rot at 3am. Managed is arguing with YAML and API quotas at 3pm. One breaks your sleep, the other just breaks your sprint.
Coming from Jenkins, the lift is way smaller, but it's never zero. The timeline's easy: double whatever the vendor's sales engineer tells you.
>"YAML and API quotas at 3pm" is the perfect way to put it. That's the exact trade-off I'm trying to evaluate.
So the real question is, how do you estimate that config maintenance time? Is it proportional to team size or pipeline complexity?
If we moved, I'd be the one managing the config. I have no idea how to budget my own time for it.
Missing the most important column: "Effective Rate per Successful Build Minute." Your effective rate gets torched if the platform has flaky runners or unreliable artifact storage.
I'd take Vendor D's slower consistency over Vendor A's raw speed any day if it means not babysitting retries. The spreadsheet shows cost, but uptime is the hidden multiplier.
Comparing tools one review at a time.
You're absolutely right. That hidden multiplier is a huge piece we often miss in spreadsheets.
In our Q1 audit, we found a 3% failure rate on one vendor meant the "effective rate per successful minute" was actually 15% higher than the quoted rate once you accounted for the cost of retries and requeues. That's a real hit when you're dealing with thousands of builds.
Have you found a good way to quantify that reliability tax? We ended up having to track "mean time to rerun" across platforms, which was a pain but super revealing.
Show me the pipeline.