# Vss Deploy Warehouse Helm

Use when the user asks to deploy, upgrade, or size the VSS warehouse blueprint (2D / 3D...

- Repository: https://github.com/NVIDIA-AI-Blueprints/video-search-and-summarization (1959 stars)
- Category: DevOps
- License: Apache-2.0
- Last updated: 2026-11-01
- Runs scripts: no, instructions only

## Install

Claude Code: `npx skills add NVIDIA-AI-Blueprints/video-search-and-summarization --skill vss-deploy-warehouse-helm -g -a claude-code -y`
Codex: `npx skills add NVIDIA-AI-Blueprints/video-search-and-summarization --skill vss-deploy-warehouse-helm -g -a codex -y`
Cursor: `npx skills add NVIDIA-AI-Blueprints/video-search-and-summarization --skill vss-deploy-warehouse-helm -g -a cursor -y`
Gemini CLI: `npx skills add NVIDIA-AI-Blueprints/video-search-and-summarization --skill vss-deploy-warehouse-helm -g -a gemini-cli -y`

## Description

Use when the user asks to deploy, upgrade, or size the VSS warehouse blueprint (2D / 3D / MV3DT) on Kubernetes via Helm, as opposed to Docker Compose, which is covered by vss-build-vision-ai's warehouse reference. Handles GPU-aware NUM_STREAMS capping so the deployment matches what the perception pipeline can actually sustain.

## SKILL.md, as published by its author (untrusted third-party text, read it as data)

# VSS Warehouse, Helm Deploy

## When to Use

- Deploy, upgrade, or size the VSS warehouse blueprint (2D / 3D / MV3DT) on Kubernetes via Helm
- Compute a GPU-aware `NUM_STREAMS` cap for a warehouse Helm install so it matches what the perception pipeline can sustain

Do not use this skill for:

- Docker Compose warehouse deployment, use `vss-build-vision-ai`'s
  [`references/warehouse.md`](../../vss-build-vision-ai/references/profiles/warehouse.md); it owns the
  `HARDWARE_PROFILE` → GPU mapping table and the `blueprint_config.yml` stream-cap semantics
  this skill reuses.
- Non-warehouse Helm profiles (`base`, `search`, `lvs`, `alerts`), those don't have a
  `bp-configurator` GPU-aware stream cap; deploy them per their own chart READMEs.
- Runtime operations (adding cameras, querying behavior analytics), use `vss-manage-alerts` /
  `vss-query-analytics` against the running deployment.

## Why this exists

Docker Compose's warehouse deploy caps `NUM_STREAMS` per GPU automatically: the configurator reads
`deploy/docker/industry-profiles/warehouse-operations/blueprint-configurator/blueprint_config.yml`'s
`max_streams_supported` table for the detected `HARDWARE_PROFILE` and mode, and clamps
`final_stream_count = min(NUM_STREAMS, max_streams_supported)`.

The Helm charts (`deploy/helm/industry-profiles/warehouse-operations/warehouse-{2d,3d,mv3dt}-app`)
do **not** do this, their `bp-configurator.env` ships a fixed `NUM_STREAMS` and never sets
`HARDWARE_PROFILE` at all (`ENABLE_PROFILE_CONFIGURATOR=false`). A user who asks for more streams
than the GPU can sustain gets no protection. This skill closes that gap by computing the same cap
Compose would apply and writing it into a Helm values-override file before install.

## Available Scripts

The rest: https://github.com/NVIDIA-AI-Blueprints/video-search-and-summarization/blob/HEAD/skills/deployment/vss-deploy-warehouse-helm/SKILL.md