CI runners that finish the same job 2–3.5× sooner
Promigence runs your existing GitHub Actions and GitLab CI jobs in its sandboxes. One line of the workflow changes (runs-on: promigence, or a runner tag in GitLab), the job itself does not. On the same job at the same size, measured against two hosted runner services, it finished 2–3.5× sooner and cost 7–10× less. Coding agents working inside CI have their own page, Agentic CI.
Who this is for: Teams on GitHub Actions or GitLab CI whose jobs are slow, costly, or too big for the default runner.
sooner on the same CI job, same size
less per CI job
end to end, through the CLI
Three things that are true of almost every team doing this
Billed by the minute
A 50-second job is billed as a full minute, and each step up in runner size multiplies the per-minute rate.
The default runner runs out of memory
On the TypeScript monorepo we measured, the default runner of both hosted services ran out of memory and never finished.
Bigger runners wait for a machine
A larger hosted runner can sit provisioning for minutes before the first step runs.
With Promigence underneath
One line moves a job
runs-on: promigencein GitHub Actions, a runner tag in GitLab CI. Steps, caches and secrets stay where they are.Per second, with a cap per job
Each job is billed for the seconds it runs, and a cap sets the most one job may cost.
A size per job
Name a size in
runs-on, and keep runners waiting when a job should start the moment it is queued.
jobs:
test:
runs-on: promigence # was: ubuntu-latest
steps:
- uses: actions/checkout@v4
- run: npm ci && npm test
# then, on any machine with the CLI:
# promigence runners github --repo your-org/your-repo
Language: yamlRun your own workload on it, free
Send a repo and the command you run against it, whatever that is: an eval suite, an RL rollout, a CI job, a queue of coding tasks. We build the environment once, run it a thousand times, and send back the timings, the failures and an exact price. Free, once, on your real workload.
- 1,000 runs of your own command, on your own repo
- What each one cost in wall clock, and anything that failed
- Whether a failure was your code or the environment
- An exact price for your real volume
Not ready to hand over a repo? Read the quickstart or check the numbers first.