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infrabench

infra-bench is an open benchmark of realistic infrastructure tasks for evaluating AI agents.

Datasets

Dataset 🟢 Easy 🟡 Medium 🔴 Hard Status
kubeply/kubernetes-core 22 27 22 🛠️ Working
kubeply/terraform-core 0 0 0 🛠️ Working
kubeply/observability-core 0 0 0 ⏳ Not started yet

Quickstart

Tasks are compatible with Harbor and can be run through uvx.

Run a local Kubernetes benchmark task with Harbor:

uvx --from harbor harbor run \
  --job-name <job-name> \
  -p <dataset-path> \
  -a <agent-name> \
  -m <model-name> \
  -e docker \
  -n 1 \
  -y \
  --max-retries 0 \
  -i <task-name>

For model-specific examples, including Codex reasoning settings and Gemini CLI workspace approval, see Harbor model commands.

For repeated local kubernetes-core runs, configure k3s registry authentication first so the ephemeral clusters can authenticate their own Docker Hub pulls. See k3s registry authentication.

To compare raw kubectl agent behavior with a bounded kply workflow, run the paired checkout release tasks documented in kply comparison tasks.

Citation

If you use infra-bench in academic work, please cite it using the "Cite this repository" button on GitHub or the following BibTeX entry:

@software{Infra_Bench,
  author = {{Kubeply}},
  month = apr,
  title = {{infra-bench: Open benchmark tasks for evaluating AI agents on real infrastructure work}},
  url = {https://github.com/kubeply/infra-bench},
  year = {2026}
}

License

Apache License 2.0. See LICENSE.

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Real-world infrastructure tasks to evaluate AI agents, starting with Kubernetes.

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