How to Run an MLflow Tracking Server in a Cloud Sandbox

sbx new --name mlflow --type small
id=sb_rotvpjxf8y    # the id that sbx new printed; note its "subdomain" too

sbx exec $id --timeout 600 "uv venv -q ~/mlflow-venv --python 3.12 && \
  VIRTUAL_ENV=~/mlflow-venv uv pip install -q mlflow==3.17.2 && ~/mlflow-venv/bin/mlflow --version"

mlflow, version 3.17.2

sbx exec $id "mkdir -p ~/mlflow && sudo tee /etc/systemd/system/mlflow.service >/dev/null <<EOF
[Unit]
Description=MLflow tracking server
After=network-online.target

[Service]
User=user
WorkingDirectory=/home/user/mlflow
ExecStart=/home/user/mlflow-venv/bin/mlflow server --host 127.0.0.1 --port 5000 \
  --backend-store-uri sqlite:////home/user/mlflow/mlflow.db \
  --artifacts-destination /home/user/mlflow/artifacts \
  --allowed-hosts fond-vernal-walrus-5000.box.sandboxer.com \
  --cors-allowed-origins https://fond-vernal-walrus-5000.box.sandboxer.com
Restart=always

[Install]
WantedBy=multi-user.target
EOF
sudo systemctl daemon-reload && sudo systemctl enable --now mlflow && \
until curl -sf localhost:5000/health >/dev/null; do sleep 0.2; done; systemctl is-active mlflow"

active

sbx host $id 5000 --localhost --title MLflow

https://fond-vernal-walrus-5000.box.sandboxer.com?_token=<token>

/health                                   200 OK
/                                         403 Invalid Host header - possible DNS rebinding attack detected
/ajax-api/2.0/mlflow/experiments/search   403 Invalid Host header - possible DNS rebinding attack detected

POST experiments/create, Origin: https://fond-vernal-walrus-5000.box.sandboxer.com   403 Cross-origin request blocked

POST experiments/create, Origin: https://fond-vernal-walrus-5000.box.sandboxer.com   200 {"experiment_id": "2"}
POST experiments/create, Origin: https://evil.example                                403 Cross-origin request blocked

MlflowException API request to endpoint /api/2.0/mlflow/experiments/search failed with error code 401 != 200. Response body: '<!doctype html>…

# MLFLOW_URL="https://…-5000.box.sandboxer.com?_token=…" python log_run.py
import os, time
from urllib.parse import urlsplit
import requests, mlflow
from mlflow.tracking.request_header.abstract_request_header_provider import RequestHeaderProvider
from mlflow.tracking.request_header.registry import _request_header_provider_registry

full = os.environ["MLFLOW_URL"]
r = requests.get(full, allow_redirects=False)  # trade ?_token= for the __sbx_auth cookie
cookie = r.headers["set-cookie"].split(";")[0]

class SandboxerCookie(RequestHeaderProvider):
    def in_context(self):
        return True
    def request_headers(self):
        return {"Cookie": cookie}

_request_header_provider_registry.register(SandboxerCookie)

u = urlsplit(full)
mlflow.set_tracking_uri(f"{u.scheme}://{u.netloc}")
mlflow.set_experiment("sandbox-demo")

t0 = time.perf_counter()
with mlflow.start_run(run_name="laptop-run") as run:
    mlflow.log_params({"lr": 0.01, "epochs": 5})
    for step in range(5):
        mlflow.log_metric("loss", round(1 / (step + 1), 3), step=step)
    with open("notes.txt", "w") as f:
        f.write("trained from a laptop\n")
    mlflow.log_artifact("notes.txt")
print(f"run {run.info.run_id} logged in {time.perf_counter() - t0:.2f} s")

got = mlflow.get_run(run.info.run_id)
print("params:", got.data.params)
print("metrics:", got.data.metrics)
print("artifacts:", [a.path for a in mlflow.MlflowClient().list_artifacts(run.info.run_id)])

pip install mlflow-skinny==3.17.2 requests
MLFLOW_URL="<full private URL>" python log_run.py

… INFO mlflow.tracking.fluent: Experiment with name 'sandbox-demo' does not exist. Creating a new experiment.
…
run e37271f40bd14e7698d401116ab6426b logged in 1.99 s
params: {'lr': '0.01', 'epochs': '5'}
metrics: {'loss': 0.2}
artifacts: ['notes.txt']

~/mlflow/artifacts/3/e37271f40bd14e7698d401116ab6426b/artifacts/notes.txt
~/mlflow/mlflow.db