Can I use this for production environments?

Yes, it specifically generates multi-stage builds and minimal runtime images designed for secure, production-grade deployments with non-root user access.

Does it support SQLModel and Neon databases?

Absolutely, it includes specific configurations for SQLModel and connection pooling patterns optimized for serverless databases like Neon.

Is it compatible with Poetry or pip?

While UV is highly recommended for performance, the skill analyzes your project structure and can adapt to Poetry or standard pip requirements if needed.

Does this skill manage Kubernetes clusters?

No, Docker Rocker focuses on containerization (Docker and Docker Compose); it does not handle Kubernetes orchestration or cloud-specific container registries.

How does Docker Rocker improve build times?

It utilizes the UV package manager and advanced layer caching strategies to reduce dependency installation time by up to 70% compared to standard pip installs.

Docker Rocker

Name: Docker Rocker
Author: alijilani-dev

byalijilani-dev

デプロイメントとDevOps

Automates the creation of optimized, multi-stage Docker containers for Python FastAPI applications using the UV package manager.

概要

Docker Rocker is a specialized Claude Code Skill designed to streamline the containerization of FastAPI, SQLModel, and Pydantic projects. It implements production-grade best practices, including multi-stage builds to minimize image size, the UV package manager for rapid dependency installation, and security hardening through non-root user configurations. This skill is ideal for developers looking to bridge the gap between local development and production-ready deployments with optimized layer caching and specialized support for modern database connections like Neon PostgreSQL.

主な機能

Multi-stage Dockerfile generation (Builder, Runtime, Testing, Dev)
Advanced layer caching strategies for rapid CI/CD and local rebuilds
Optimized database connection patterns for SQLModel and Neon PostgreSQL
UV package manager integration for 50-70% faster dependency installation
Security hardening with non-root user and permission configurations
0 GitHub stars

ユースケース

Setting up high-performance CI/CD pipelines with containerized testing stages
Optimizing Python web API container images for production performance
Standardizing containerization across FastAPI and Pydantic project ecosystems

概要

主な機能

Multi-stage Dockerfile generation (Builder, Runtime, Testing, Dev)
Advanced layer caching strategies for rapid CI/CD and local rebuilds
Optimized database connection patterns for SQLModel and Neon PostgreSQL
UV package manager integration for 50-70% faster dependency installation
Security hardening with non-root user and permission configurations
0 GitHub stars

ユースケース

Setting up high-performance CI/CD pipelines with containerized testing stages
Optimizing Python web API container images for production performance
Standardizing containerization across FastAPI and Pydantic project ecosystems