# Jetson e2e Harness — Operator Setup

AZ-615 / AZ-602 cycle-2. Documents the one-time operator-side setup
that makes `scripts/run-tests-jetson.sh` work against a Jetson Orin Nano
reachable from the developer Mac over SSH.

## Why a separate Jetson harness exists

The Colima/Tier-1 smoke harness (`docker-compose.test.yml` +
`tests/e2e/Dockerfile`) verifies wiring, env config, fixture loading,
auto-sync, and JSONL schema — everything UP TO the GPU boundary. But
all three C7 inference strategies
(`pytorch_fp16_runtime.py`, `tensorrt_runtime.py`,
`onnx_trt_ep_runtime.py`) are CUDA-only by design (`model.half().cuda()`
on `pytorch_fp16_runtime.py:189`, no CPU fallback). The full Reality
Gate — including C3 matcher + C7 inference — therefore needs a
CUDA-capable host.

The Jetson harness runs the same test tree (`tests/e2e/`) on the Jetson
with `GPS_DENIED_TIER=2`, which turns OFF the auto-skip for
`@pytest.mark.tier2` tests (see `tests/conftest.py:31-44`).

## Hardware contract

Operator-confirmed environment (2026-05-17):

* Jetson Orin Nano dev kit
* JetPack 6.2.2+b24
* L4T R36.5.0 (Jan 2026)
* nvidia-container-toolkit 1.16.2
* ≥ 30 GB free on `/var/lib/docker` (l4t-pytorch base image ~7 GB +
  build cache + fixture volumes)
* Swap enabled (Orin Nano has 8 GB RAM; PyTorch + TensorRT loads spike)

## One-time setup

### 1. SSH key + alias (on the Mac)

```bash
# Generate a dedicated keypair (separate from your daily-dev key).
# This command produces BOTH halves in one go:
#   ~/.ssh/id_ed25519_jetson_e2e       — private (keep secret, never share)
#   ~/.ssh/id_ed25519_jetson_e2e.pub   — public (push to Jetson below)
ssh-keygen -t ed25519 -a 100 -f ~/.ssh/id_ed25519_jetson_e2e \
    -C "jetson-e2e $(date +%Y-%m-%d)"

# Push the public half to the Jetson (asks for the Jetson password once).
# Add `-p <port>` if the Jetson's sshd listens on a non-default port:
ssh-copy-id -i ~/.ssh/id_ed25519_jetson_e2e.pub <jetson-user>@<jetson-ip>
# or with a custom port:
# ssh-copy-id -p <port> -i ~/.ssh/id_ed25519_jetson_e2e.pub <jetson-user>@<jetson-ip>

# Verify the Jetson's host key (run this ON the Jetson, via HDMI/serial,
# not over the LAN you're about to trust):
#   ssh-keygen -lf /etc/ssh/ssh_host_ed25519_key.pub
# Then compare against what the Mac sees on first connect. Accept only
# if they match.

# Wire up ~/.ssh/config (gitignored, never committed). Add `Port <port>`
# if the Jetson's sshd listens on a non-default port.
#
# IMPORTANT: the leading blank line inside the heredoc is intentional.
# Without it, the appended block can fuse onto the previous file line
# (`IdentitiesOnly yesHost jetson-e2e` was a real failure mode).
cat >> ~/.ssh/config <<'EOF'

Host jetson-e2e
    HostName <jetson-ip>
    User <jetson-user>
    Port 22
    IdentityFile ~/.ssh/id_ed25519_jetson_e2e
    IdentitiesOnly yes
    AddKeysToAgent yes
    UseKeychain yes
    StrictHostKeyChecking accept-new
    ServerAliveInterval 30
    ServerAliveCountMax 4
EOF

# Cache the passphrase into macOS Keychain (one-time)
ssh-add --apple-use-keychain ~/.ssh/id_ed25519_jetson_e2e
```

### 2. Restrict the key's scope on the Jetson (recommended)

Edit `~/.ssh/authorized_keys` on the Jetson and prefix the line that the
`ssh-copy-id` step appended:

```
from="<mac-lan-ip>",no-port-forwarding,no-X11-forwarding,no-agent-forwarding ssh-ed25519 AAAA…  jetson-e2e
```

Optionally lock to "only run the e2e driver" by adding
`command="docker compose -f /home/jetson/gps-denied-onboard/docker-compose.test.jetson.yml up --abort-on-container-exit"` —
the key can't get a general shell, only invoke that one command.

### 3. Harden sshd (optional, recommended for an exposed test rig)

On the Jetson, create `/etc/ssh/sshd_config.d/10-e2e.conf`:

```
PasswordAuthentication no
PermitRootLogin no
PubkeyAuthentication yes
```

Then `sudo systemctl reload ssh`.

### 4. Verify the Jetson Docker + GPU pipeline

`nvidia-container-runtime` mounts `nvidia-smi` + CUDA libs from the
host into the container at runtime, so a tiny base image works for the
smoke test (no need to pull the 5 GB `l4t-jetpack` image just to check
GPU exposure):

```bash
ssh jetson-e2e 'docker run --rm --runtime=nvidia --gpus all \
    ubuntu:22.04 nvidia-smi'
```

Expected output: an `nvidia-smi`-style table listing the Orin GPU. If
this fails with "could not select device driver \"nvidia\"" or "no GPU
devices", reinstall `nvidia-container-toolkit` and
`sudo systemctl restart docker`.

If `nvidia-smi` works on the host directly but not inside a container,
the problem is always nvidia-container-toolkit, not the driver.

### 5. Confirm disk + swap

```bash
ssh jetson-e2e 'df -h /var/lib/docker && swapon --show && free -h'
```

Need ≥ 30 GB free on `/var/lib/docker`. Swap should be at least 4 GB
(JetPack default is 4 GB zram).

## Running the harness

From the developer Mac, repo root:

```bash
bash scripts/run-tests-jetson.sh
```

What happens:

1. `rsync` source → `jetson-e2e:~/gps-denied-onboard/` (excludes `.git`,
   `__pycache__`, build artefacts; LFS pointers transfer as text).
2. `ssh jetson-e2e docker compose -f docker-compose.test.jetson.yml build e2e-runner`
3. `ssh jetson-e2e docker compose ... up --abort-on-container-exit --exit-code-from e2e-runner`
4. stdout / stderr stream to the Mac terminal; exit code propagates.

Override the alias or remote dir if your setup differs:

```bash
JETSON_SSH_ALIAS=other-host JETSON_REMOTE_DIR=~/somewhere/else \
    bash scripts/run-tests-jetson.sh
```

## Smoke vs. Reality Gate split — at a glance

| Test category | Marker | Colima (Tier-1) | Jetson (Tier-2) |
|---------------|--------|-----------------|-----------------|
| AC-4a AST scan | (none) | runs | runs |
| AC-4b byte-equality | (none) | runs | runs |
| AC-7 skip-gate self-check | (none) | runs | runs |
| AC-9 helper unit tests | (none) | runs | runs |
| AC-1 / AC-2 / AC-3 / AC-5 / AC-6 (heavy) | `tier2` | **SKIPPED** | runs |
| AC-8 operator workflow | `skip` (AZ-616 blocks) | skipped | skipped |

`GPS_DENIED_TIER` env var controls the auto-skip:

* `GPS_DENIED_TIER=1` (Colima default) → `tier2` / `gpu` / `docker`
  marked tests auto-skipped via `tests/conftest.py:31-44`.
* `GPS_DENIED_TIER=2` (Jetson default) → all markers active; everything
  runs (subject to other skip gates like `RUN_REPLAY_E2E`).

## Troubleshooting

| Symptom | Likely cause | Fix |
|---------|--------------|-----|
| `cannot reach 'ssh jetson-e2e' non-interactively` | Agent isn't unlocked or key not in `authorized_keys` | `ssh-add -l` on Mac; check `~/.ssh/authorized_keys` on Jetson |
| `docker: Error response from daemon: could not select device driver "nvidia"` | nvidia-container-toolkit missing or daemon not restarted after install | `sudo apt install nvidia-container-toolkit && sudo systemctl restart docker` |
| `torch.cuda.is_available() == False` inside the container | `runtime: nvidia` block missing, or building on x86 host | Verify `docker-compose.test.jetson.yml` has `runtime: nvidia`; rebuild on the Jetson |
| `replay.auto_sync.ac8_validation_failed` | AZ-614 (tlog time-base mismatch) — not a harness bug | Fix AZ-614 in `tests/e2e/replay/_tlog_synth.py` |
| `not found` / `tag not found` on `nvcr.io/nvidia/l4t-base:r36.*` | `l4t-base` was deprecated in JetPack 6 | use `l4t-jetpack:r36.4.0` for smoke tests; the harness itself uses `dustynv/l4t-pytorch:r36.4.0` |
| `pull access denied for nvcr.io/nvidia/...` | NGC requires login for some tags | `docker login nvcr.io` (use NGC API key from developer.nvidia.com) |

## Related Jira

* AZ-615 — this harness (Jetson runner story)
* AZ-616 — replace `mock-sat` with real `../satellite-provider` service
* AZ-617 — mark heavy ACs with `tier2` (already applied; this story
  documents and verifies the auto-skip)
* AZ-614 — tlog time-base mismatch (currently blocks the heavy ACs
  from reaching the GPU stage)
* AZ-602 — parent Epic: E2E Tier-1 harness rehabilitation