Datasets:

InfraBench
/

infrabench

InfraBench evaluates AI agents on real infrastructure operations — provisioning, diagnosis, and repair across hardware, local systems, distributed systems, and user applications.

This repository publishes task specifications (instruction, environment, verifier). The evaluation runtime (Syscraft) is not open-sourced yet; see the README. You can still contribute by authoring a well-structured task that matches the layout below.

Task layout

my-task/
├── task.toml          # environment type, resources, timeout, metadata
├── instruction.md     # natural-language brief for the agent
├── environment/
│   └── Dockerfile     # docker tasks
│   # or setup.sh + bootstrap.sh for vm / vm-cluster
├── solution/
│   └── solve.sh       # reference solution (optional, used by oracle agents)
└── tests/
    └── test.sh        # verifier — writes reward to /logs/verifier/

Start from tasks/hello-world (smallest Docker example), then study a paper task at the layer you care about under tasks/.

Verifier contract

Emit either a scalar reward:

echo 1.0 > /logs/verifier/reward.txt

or structured JSON with partial credit:

{
  "reward": 0.0,
  "checks": [
    {"name": "service health", "passed": true, "scored": false},
    {"name": "root cause fixed", "passed": false, "scored": true}
  ]
}

scored: true — checks that measure meaningful repair progress (contribute to partial score).
scored: false — diagnostics / anti-bypass / reachability (affect pass/fail, do not inflate partials).

`task.toml` templates

Docker

[task]
name = "myorg/my-task"

[metadata]
difficulty = "easy"          # easy | medium | hard
category = "infrastructure"

[environment]
type = "docker"
cpus = 2
memory_mb = 4096

[agent]
timeout_sec = 300

Single-node VM

[task]
name = "myorg/my-vm-task"

[environment]
type = "vm"
base_image = "ubuntu-24.04"
cpus = 2
memory_mb = 4096
storage_mb = 20480

[agent]
timeout_sec = 300

VM tasks use environment/setup.sh (cached package install) and optional bootstrap.sh (per-trial) instead of a Dockerfile.

VM cluster

[task]
name = "myorg/my-cluster-task"

[environment]
type = "vm-cluster"
network = "192.168.100.0/24"

[[environment.nodes]]
name = "primary"
cpus = 2
memory_mb = 4096
storage_mb = 20480

[[environment.nodes]]
name = "worker"
cpus = 2
memory_mb = 4096
storage_mb = 20480

[agent]
timeout_sec = 600

The agent SSHes into the first node (primary). Nodes resolve each other by hostname.

What makes a strong InfraBench task

Real ops, not toy puzzles — grounded in incident response, deployment, or repair that a human SRE would recognize.
Layered stack — situate the failure in L1 hardware → L2 local systems → L3 distributed → L4 user applications when possible.
Honest verifiers — prefer multi-check reward.json over a single opaque pass/fail; resist reward hacking.
Clear instructions — instruction.md states the goal and constraints without leaking the root cause unless that is part of the scenario.
Reproducible environment — pin packages / images; document BM Cluster / CloudLab profiles or base images in a short task README if needed.

Submission checklist

Directory matches the layout above
instruction.md is self-contained
Verifier writes /logs/verifier/reward.txt or reward.json
task.toml declares type, resources, and [metadata].difficulty
Reference solution/solve.sh works under the intended environment (when you have runner access)
Open a PR against this repo with a short description: layer, backend, what is being tested

Agent-oriented notes

If you are an coding agent authoring a task, also read AGENTS.md.

Questions

Open an issue on this repository, or contact the authors listed in the HotInfra '26 paper.

Contributing a task to InfraBench