StarSling vs Ubicloud runners for GitHub Actions

Choose StarSling when you want faster Ubuntu jobs and reviewable improvements to caching, dependency installs, parallelization, and test execution.

• Give each job faster compute: Adaptive Compute combines Sandbox Router's placement on the fastest available sandbox with Afterburner's extra CPU and RAM during a running step, at no extra cost.
• Improve the work your pipeline performs: StarSling agents deliver reviewable optimization PRs for workflow improvements. Inspect the changes in real repositories and merge the ones that fit your team.
• Turn CI findings into fixes: ci-speedup, ci-score, and ci-secure give your coding agent workflow-specific findings and fixes for speed, configuration, and security, applying CI optimization best practices.
• Own your code review: Review Runners run your chosen model, repo-native skills, scripts, and team-defined reviewers. Version review logic alongside your code.
• Give GPU tests their own hardware: GPU Runners provide dedicated NVIDIA GPUs for GPU tests, CUDA builds, and model evaluations, keeping CI off your production GPUs.
• Diagnose failures and wasted time: the sling CLI explains failed jobs with evidence and next steps and breaks wall-clock time into runner-lifecycle phases.

In RunsOn's public GitHub Actions runner benchmark of Rust and TypeScript builds on x64 runners at 8 to 12 vCPU (p90 wait + job time, September 30 to October 4, 2026), StarSling ranked first on both builds with Rust 1m 54s and TypeScript 1m 07s. Ubicloud recorded Rust 2m 30s and TypeScript 1m 33s.

Each figure is a provider's best runner in that size range, on a cold Rust build and a cold TypeScript build. RunsOn runs the benchmark and sells one of the runners it measures. Its harness and raw results carry all nine providers, and our write-up walks through them.

Ubicloud installs as the Ubicloud Managed Runners GitHub App. A job moves to Ubicloud when its runs-on label changes from ubuntu-latest to a Ubicloud label such as ubicloud-standard-2, and each job gets an isolated, clean and ephemeral VM.

Ubicloud's managed runner VMs run in Germany by default, with a US fleet Ubicloud enables per account.Ubicloud's source code is available under the AGPL license, so a team can also run the software itself.

Ubicloud's transparent cache serves actions/cache, the package-manager caches in actions/setup-*, and Docker layer caching through type=gha, with 30 GB of cache storage per repository per week. Ubicloud recommends the transparent cache, and its older ubicloud/cache action is a drop-in replacement for actions/cache.

When moving a workflow between providers, list those cache actions next to the runner label, and restore GitHub Actions caching where the trial needs it.

Choose a representative Ubuntu job with a clear success condition. Keep the same commit, tests and build outputs across the comparison, and record queue time separately from execution time.

• Install the StarSling GitHub App for the trial repository, then choose a label from StarSling runner sizes. The default starsling-ubuntu-26.04 selects 4 vCPU; match the size to the Ubicloud label you are comparing.
• Prepare a small workflow PR. Where the job uses ubicloud/cache, switch it back to actions/cache in the same PR. Preserve required check names, permissions and test commands.
• Run repeated cold-cache and warm-cache trials. Compare completed work, error rate, queue time, execution time and billed usage. Use the GitHub Actions pricing guide to compare the cost of your actual workload.
• Keep the original workflow revision available. Roll back the trial by reverting the runner label and any cache edits together.

Read the public Mastra optimization PRs and results and Better Auth case study to see changes to real workflows, the measured windows and the work behind each result. Use those examples to identify a testable improvement in your own pipeline.

Optimization PRs are on paid plans, off by default for new accounts.