docker-split-service

Name: docker-split-service
Availability: InStock
Author: JakoError

Enforce a canonical two-stage Docker build and docker-compose layout.

3|Updated Apr 22, 2026

Search Tags:#devops #dependencies #docker #dockerfile #docker-compose #entrypoint #two-stage-build

Ready to run

npx skills add https://github.com/JakoError/claude-research-skills --skill docker-split-service

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: docker-split-service
Source: https://github.com/JakoError/claude-research-skills/tree/main/skills/docker-split-service
Command: npx skills add https://github.com/JakoError/claude-research-skills --skill docker-split-service

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Standardize Dockerized service development by enforcing a canonical two-stage build (deps + app), standardized docker-compose layouts, and consistent entrypoint and env-driven configuration across projects.

Core Features & Use Cases

Two-stage build pattern: a heavy Dockerfile.deps for dependencies and a lightweight Dockerfile.app for application code.
Standardized docker-compose integration and entrypoint conventions for predictable local development and deployment across services.
Framework-agnostic guidance with a PyTorch-oriented example, enabling rapid onboarding for new services and safe refactors.

Quick Start

Follow the pattern to scaffold a new service and wire it into the repo's docker-compose server workflow.

Frequently Asked Questions about docker-split-service

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

What is a two-stage Docker build pattern and when should I use it for my services?▼

A two-stage Docker build separates dependency installation from application code using a heavy Dockerfile.deps and a lightweight Dockerfile.app. This pattern is needed when you want deterministic image tagging, faster rebuilds, and reliable service deployment across research projects.

How do I standardize docker-compose workflows for local development and production?▼

Standardize docker-compose workflows by enforcing consistent repository layouts, entrypoint conventions, and env-driven configuration. This approach provides a repeatable docker-compose workflow that works predictably for both local development and production service deployment.

Does the two-stage Docker build pattern work with PyTorch and other research frameworks?▼

Yes, the two-stage Docker build pattern is framework-agnostic and includes a PyTorch-oriented example. It applies to creating or refactoring Dockerized services across research projects, ensuring per-axis version pins and deterministic image tagging regardless of the framework used.

How do I structure my Dockerfile for dependencies versus application code layers?▼

Structure your Docker build by creating a heavy Dockerfile.deps for dependencies and a lightweight Dockerfile.app for application code. This separation enables faster rebuilds, deterministic image tagging, and consistent entrypoint conventions across container orchestration workflows.

Why does my Dockerized service deployment fail across different research projects?▼

Dockerized service deployment often fails due to inconsistent repository layouts and non-standard entrypoint conventions. Enforcing a canonical two-stage Docker build pattern with consistent docker-compose integration and env-driven configuration solves these reliability issues across projects.

Can I use this two-stage Docker build approach to refactor existing services safely?▼

Yes, the canonical two-stage Docker build pattern applies to both creating new services and safely refactoring existing Dockerized services. It enforces standardized docker-compose layouts and entrypoint conventions to ensure reliable deployment during service refactoring.