dynamo-interconnect-check

What this skill does

# Dynamo Interconnect Check

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## Purpose

Confirm that the transport disaggregated serving depends on actually works. A
deployment can pass an endpoint smoke test while disagg is silently wrong: if
NIXL/UCX cannot reach the peer worker over RDMA or NVLink, KV transfer falls
back to a slow or broken path. Catch that with read-only checks before trusting
a disagg deployment or its benchmark numbers.

This skill is read-only. It never mutates the cluster and never prints secrets.

## Prerequisites

- Python 3.10+ on the operator machine.
- `kubectl exec` access to a worker pod in the target Dynamo deployment.
- Read access to the recipe directory (`recipes/<model>/<framework>/<mode>`).
- For node-capability checks: tools like `ibstat`, `nvidia-smi`, `lsmod` available in the worker pod image (missing tools are reported as `skipped`, not failures).

## When To Use

- After `dynamo-recipe-runner` deploys a **disagg** or multi-node recipe.
- Before reporting disagg throughput/latency, so numbers reflect the real
  transport.
- When agg works but disagg is slow, hangs, or returns wrong output and you
  suspect the fabric rather than the model.

For diagnosing pods that are already crashing or unschedulable, use
`dynamo-troubleshoot` first.

## Instructions

### 1. Check Transport Env Vars On The Recipe

```bash
python3 scripts/check_interconnect.py env recipes/<model>/<framework>/<mode>
```

Reports which NIXL/UCX/NCCL transport variables are set and flags
disagg-critical ones (e.g. `UCX_TLS`, `UCX_NET_DEVICES`, `NCCL_IB_HCA`) that are
absent. Missing here is only a warning — they may be baked into the image — so
confirm with the node and NIXL checks. See
`references/interconnect-env-vars.md` for what each variable does.

### 2. Check Node Capabilities

Locally on a GPU node, or inside a running worker pod:

```bash
python3 scripts/check_interconnect.py node \
  --namespace "${NAMESPACE}" --pod <worker-pod>
```

Probes (read-only) for: InfiniBand devices and Active links, GPUDirect RDMA
(`nvidia_peermem`), GDRCopy, and NVLink in the GPU topology. Missing tools are
reported as `skipped`, not failures.

### 3. Validate NIXL Reachability

```bash
python3 scripts/check_interconnect.py nixl \
  --namespace "${NAMESPACE}" --pod <worker-pod>
```

Looks for NIXL test tooling in the pod and surfaces the exact next step to run a
pairwise prefill↔decode transfer test. A full cross-pod transfer test requires
two scheduled GPU pods on the fabric.

## Available Scripts

| Script | Purpose | Arguments |
|---|---|---|
| `scripts/check_interconnect.py env` | Inspect NIXL/UCX/NCCL env vars on a recipe | positional recipe path |
| `scripts/check_interconnect.py node` | Probe InfiniBand, GPUDirect RDMA, GDRCopy, NVLink on a node or pod | `--namespace`, `--pod` |
| `scripts/check_interconnect.py nixl` | Surface NIXL transfer-test readiness for a pod | `--namespace`, `--pod` |

Invoke via the agentskills.io `run_script()` protocol:

```python
run_script("scripts/check_interconnect.py", args=["env", "recipes/qwen3-coder-480b/sglang/disagg"])
run_script("scripts/check_interconnect.py", args=["node", "--namespace", "dynamo-demo", "--pod", "qwen-worker-0"])
```

## Examples

Verify a disagg recipe's transport env shape before deploy:

```bash
python3 scripts/check_interconnect.py env recipes/qwen3-coder-480b/sglang/disagg
```

After deploy, validate a worker pod's fabric:

```bash
python3 scripts/check_interconnect.py node \
  --namespace dynamo-demo --pod qwen-worker-0
python3 scripts/check_interconnect.py nixl \
  --namespace dynamo-demo --pod qwen-worker-0
```

Equivalent through the agent protocol:

```python
run_script("scripts/check_interconnect.py", args=["nixl", "--namespace", "dynamo-demo", "--pod", "qwen-worker-0"])
```

## Output Contract

Each check returns `ok` / `warn` / `fail` / `skipped` with a one-line detail,
plus a rolled-up verdict on disagg transport readiness. Report:

- transport env vars present vs. disagg-critical ones missing
- RDMA / GPUDirect / NVLink capability status
- whether NIXL reachability was validated, and the next command if not
- a clear statement of whether disagg can be trusted, or what to fix first

## Limitations

- Read-only fabric probe; does not run a full pairwise NIXL transfer (requires two scheduled GPU pods and the in-pod NIXL test tools).
- `skipped` results for missing tools (`ibstat`, `nvidia-smi`, `lsmod`) are inconclusive, not a pass.
- Env-var check inspects the recipe text; values injected at runtime via initContainers or operator-applied envs are not detected.
- Single-node agg deployments do not exercise the transport — this skill is for disagg / multi-node validation.

## Troubleshooting

| Symptom | Likely cause | Next step |
|---|---|---|
| `env` reports all critical vars missing | Vars baked into image or injected by operator | Run the `node` check inside the worker pod to verify actual env |
| `node` reports no Active IB link | Fabric down or HCA not provisioned to the node | Contact cluster admin; verify `kubectl describe node` shows `nvidia.com/gpu` and IB labels |
| `nvidia_peermem` missing | GPUDirect RDMA module not loaded | Ask cluster admin to load `nvidia-peermem`; without it, NIXL falls back to staged copies |
| `nixl` finds no test tools | Worker image lacks NIXL test harness | Use a NIXL-enabled image or run the standalone transfer test from a debug pod |

## Benchmark

See `BENCHMARK.md` for the NVCARPS-EVAL performance report (auto-generated by the NVSkills CI pipeline). To refresh, re-run `/nvskills-ci` on an upstream PR touching this skill.

## References

- `references/interconnect-env-vars.md` — NIXL/UCX/NCCL env var catalog and IB
  capability checklist.
- Use `scripts/check_interconnect.py` for all read-only checks.