What is deploy-runai-kai?

A deployment guide for adding or removing KAI Scheduler or Run:ai on a Kubernetes cluster that runs GPU workloads. Kubernetes is a system for managing containers across machines.

It is for enabling fractional-GPU scheduling and diagnosing KAI or Run:ai installation and scheduling failures.

It makes the required checks and cluster-wide installation steps explicit before changing GPU scheduling.

deploy-runai-kai — Skill for Claude Code and Codex by NVIDIA/deepops

About the project

DeepOps is a collection of automation tools for deploying and managing compute clusters that use NVIDIA GPUs with Kubernetes or Slurm. It supports environments ranging from full data-center clusters to individual machines needing GPU drivers, Docker, and NVIDIA container support.

NVIDIA/deepops · 1,485 stars · on GitHub

Install

Getting it into your agent

It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.

Clone the repo

git clone --depth 1 https://github.com/NVIDIA/deepops

agentmods

npx agentmods add skills/nvidia/deepops/deploy-runai-kai

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

README.md

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Your own site

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Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

Your own site · 80×15

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Per session 48 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 1,062 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.

Origin original No closer match found in the catalogue.

Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

Model	Per session	Once invoked
Fable 5.1	$0.00048	$0.01062
Opus 5.5	$0.00019	$0.00425
Sonnet 5.5	$0.00010	$0.00212
Haiku 4.5	$0.00005	$0.00106

Measured 18d ago against content hash cd0209179bfe, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

deploy-runai-kai scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 18d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/deploy-runai-kai/SKILL.md · 68 lines

How it starts

The opening of the file, as written. The whole thing — 68 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Deploy KAI Scheduler or Run:ai (optional)

Run commands from the DeepOps repository root. This adds GPU-aware scheduling on top of a working Kubernetes GPU cluster. It is off by default and never changes the GPU Operator or the NVIDIA driver. Full guide: docs/k8s-cluster/runai.md.

Preconditions

python3 scripts/validation/validate_k8s.py --json --cuda-smoke reports "ok": true (the cluster already runs GPU pods). If not, use skills/deploy-k8s-gpu-cluster/ first.
Confirm the inventory is the intended cluster and nobody else's workloads run there; the install adds cluster-wide admission webhooks.
Pick one mode. kai and platform exclude each other (the platform ships its own KAI). platform is experimental and also needs a default StorageClass, kube-prometheus-stack 88.6.5+, a DNS name and TLS (see the guide).
Fractioning with hard memory limits (runai_kai_gpu_fractioning: true) needs GPU Operator v26.7.1+ and an r615+ driver already in place. Do not change the default driver to get it without the cluster owner's agreement.

Procedure

Set runai_mode (and, for platform, the domain, admin user and a vaulted login value) in config/group_vars/k8s_cluster.yml.
Preview: ansible-playbook -l kube_control_plane playbooks/k8s-cluster/runai.yml --check --diff
Apply: ansible-playbook -l kube_control_plane playbooks/k8s-cluster/runai.yml. Rerun once; the second run must report changed=0.
Verify with the validator, not with the playbook result:
```
python3 scripts/validation/validate_runai.py --json                      # kai
python3 scripts/validation/validate_runai.py --json --memory-enforcement # + fractioning
```
Require exit 0 and "ok": true with gpu_job_ok and fraction_job_ok true. Platform mode: add --mode platform --platform-domain <fqdn>, set RUNAI_USERNAME/RUNAI_PASSWORD in the environment (never as arguments), and use a Run:ai project's namespace and queue.
Remove: add -e runai_state=absent, then python3 scripts/validation/validate_runai.py --json --verify-uninstalled must report "ok": true.

Read the full file on GitHub · 68 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

18d ago First seen · 68 lines · 48 tokens per session scan A cd0209179bfe

Subscribe to this mod's changes

deploy-runai-kai is a skill published in the GitHub repository NVIDIA/deepops (1,485 stars, last pushed yesterday), licensed BSD-3-Clause. It adds 48 tokens to every session and 1,062 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-10-20.

Cloud DevOps and cloud Hardware and IoT

deploy-runai-kai next to 6 skills from other repositories
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