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docker-advanced

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Docker best practices for AI/ML workloads.

Software Engineering#security#production#containerization#docker#gpu#ml#multistage-builds
Authorinfantesromeroadrian
Version1.0.0
Installs0

System Documentation

What problem does it solve?

Docker enables packaging and deployment of AI/ML workloads, but without best practices you risk insecure containers, brittle builds, and inefficient GPU usage. This Skill provides guidance to containerize ML apps securely and efficiently, with scalable production workflows.

Core Features & Use Cases

  • GPU-accelerated containerization using the NVIDIA toolkit and compatible base images.
  • Security hardening including non-root users, seccomp, AppArmor, and read-only file systems.
  • Production-ready multi-stage builds, image sizing, and deployment considerations for CI/CD.
  • Guidance on base images, tooling, and runtime configurations for reliable ML pipelines.

Quick Start

Review the Docker-advanced guidelines and implement a GPU-enabled, non-root container workflow for your AI/ML project.

Dependency Matrix

Required Modules

None required

Components

Standard package

💻 Claude Code Installation

Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.

Please help me install this Skill:
Name: docker-advanced
Download link: https://github.com/infantesromeroadrian/arca-claude-code/archive/main.zip#docker-advanced

Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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