//self-hosted github actions runners · your aws account

self-hosted runners, done properly.

You tuned ARC's autoscaler, fought the controller, and gave up on Windows. RunsOn is the version that just runs: ephemeral EC2 in your own AWS account, one CloudFormation stack, any instance per job.

self-host it → see the hard parts

the label is a query — pick constraints, resolved at launch

.github/workflows/ci.yml yaml

# the label is a query — each line one constraint
jobs:
  build:
    runs-on:
      - runs-on=${{ github.run_id }}
      - cpu=16
      - family=c7i
      - image=ubuntu24-full-x64
      - extras=s3-cache
    steps: [...]

cpu

family

image

extras

see all job labels →

→ resolves to c7i.4xlarge · spot · ~$0.23/hr github-hosted 16cpu: $2.52/hr ≈ 11× cheaper

7–12×

cheaper than GitHub-hosted runners — you pay AWS directly, no per-minute markup.

do the math on your bill →

1.5M+

jobs every day — ephemeral runners launched and destroyed, one box per job.

8M+

vCPUs daily — from 1 to 896 per runner, across x64 · arm64 · gpu.

running in production, every single day — ~1.5% of all github actions runs

the hard parts, handled

everything you had to bolt on yourself.

The runner is the easy 20%. The other 80% is why you're reading this page — RunsOn ships it as defaults, not as a weekend project.

dynamic instance selection

The instance is the job. The label is a query — family, cpu, ram, image, volume — resolved against live spot capacity at launch. No pools to size, no scale sets to babysit.

1–96cpu x64 · arm64 · gpu spot → on-demand

caching that's actually fast

Flip extras=s3-cache and actions/cache is backed by an S3 bucket in your account — same region, same VPC, no 10GB ceiling. Nothing else in the workflow changes.

no 10GB cap in-VPC restores

nested virt, both OSes

KVM for Linux, Hyper-V for Windows — nested virtualization is just a label. Android emulators, VM-based e2e suites, Windows containers: they run.

KVM Hyper-V m8i · c8i · r8i

+ docker layer caching · per-job cost reporting · spot→on-demand retry · static egress IPs · warm pools · byo AMIs

sixty seconds

same goal. a lot less to operate.

The Kubernetes cluster, the controller, the autoscaler — then the same job on ephemeral EC2 in your own account. Watch the moving parts fall away.

the reasons teams stay

“Saved around 75% of our costs, and tests now run 5× faster on gigantic spot instances.”

Tim Dumol — Founding Engineer, Expedock

“After benchmarking a lot of tools, it's the best. Costs divided by 4 — thousands of jobs per day.”

Corentin Smith — CTO, Dashdoc

“Costs down 70%, CI runtime improved up to 80%. A clear win with virtually no downside.”

Théophile D. de Segonzac — Lead DevOps, Lingoda

read all testimonials →

install

three steps. one line to migrate.

deploy the stack

One CloudFormation template — or the official Terraform module. VPC, cache bucket, IAM, and the scheduler come up together.

connect the repo

Install the GitHub App on your org. RunsOn registers ephemeral runners on demand — nothing stays running idle.

change one label

Swap a single line in your workflow. Every existing action, cache step, and secret keeps working untouched.

# the entire migration, in one diff
runs-on: ubuntu-latest
runs-on: runs-on=${{ github.run_id }}/runner=2cpu-linux-x64

launch the stack → read the docs