docker-optimization
Optimize Docker images and containers for size, build speed, and runtime performance
- Installs
- 72
- Last 24h
- —
- Trending rank
- —
- Security
- Not audited
Install
Works with every agent the skills CLI supports.
npx skills add https://github.com/pluginagentmarketplace/custom-plugin-docker --skill docker-optimization- 01
Install
Run the command in your project. The CLI asks which agents to install for.
- 02
Describe the task
Ask your agent for something this skill covers. It loads docker-optimization automatically when relevant.
- 03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.
SKILL.md
The instructions your agent reads when the skill is triggered.
Docker Optimization Skill
Comprehensive optimization techniques for Docker images and containers covering size reduction, build caching, and runtime performance.
Purpose
Reduce image size, improve build times, and optimize container performance using 2024-2025 industry best practices.
Parameters
| Parameter | Type | Required | Default | Description |
|---|---|---|---|---|
| target | enum | No | all | size/build/runtime/all |
| base_image | string | No | - | Current base image |
| current_size | string | No | - | Current image size |
Optimization Strategies
1. Image Size Reduction
Base Image Selection
| Base | Size | Use Case |
|---|---|---|
| scratch | 0 | Static Go/Rust binaries |
| distroless | 2-20MB | Production containers |
| alpine | 5MB | General purpose |
| slim | 80-150MB | When apt packages needed |
| full | 500MB+ | Development only |
# Before: 1.2GB
FROM node:20
# After: 150MB (88% smaller)
FROM node:20-alpine
Layer Optimization
# Bad: 3 layers, 150MB
RUN apt-get update
RUN apt-get install -y curl
RUN rm -rf /var/lib/apt/lists/*
# Good: 1 layer, 50MB
RUN apt-get update && \
apt-get install -y --no-install-recommends curl && \
rm -rf /var/lib/apt/lists/*
Remove Unnecessary Files
# Clean package manager cache
RUN npm cache clean --force
RUN pip cache purge
RUN apt-get clean && rm -rf /var/lib/apt/lists/*
# Use .dockerignore
# node_modules, .git, *.md, tests/, docs/
2. Build Speed Optimization
Layer Caching Strategy
# Dependencies first (rarely change)
COPY package*.json ./
RUN npm ci
# Source code last (frequently changes)
COPY . .
RUN npm run build
BuildKit Cache Mounts
# syntax=docker/dockerfile:1
FROM node:20-alpine
# Cache npm packages
RUN --mount=type=cache,target=/root/.npm \
npm ci
# Cache pip packages
RUN --mount=type=cache,target=/root/.cache/pip \
pip install -r requirements.txt
Parallel Multi-Stage
# Parallel stages (BuildKit)
FROM node:20-alpine AS deps
COPY package*.json ./
RUN npm ci
FROM deps AS builder
COPY . .
RUN npm run build
FROM deps AS linter
COPY . .
RUN npm run lint
3. Runtime Performance
Resource Limits
services:
app:
deploy:
resources:
limits:
cpus: '1'
memory: 512M
reservations:
cpus: '0.5'
memory: 256M
Container Tuning
# Set memory limits
docker run --memory=512m --memory-swap=512m app
# CPU limits
docker run --cpus=1.5 app
# I/O limits
docker run --device-read-bps=/dev/sda:1mb app
Optimization Checklist
Size Checklist
- Using smallest viable base image?
- Multi-stage build implemented?
- Package manager cache cleaned?
- Dev dependencies excluded?
- .dockerignore configured?
Build Speed Checklist
- Dependencies copied before code?
- BuildKit enabled?
- Cache mounts used?
- Parallel stages where possible?
Runtime Checklist
- Resource limits set?
- Health checks configured?
- Non-root user?
- Read-only filesystem where possible?
Analysis Tools
# Image size analysis
docker images --format "table {{.Repository}}\t{{.Tag}}\t{{.Size}}"
# Layer analysis
docker history <image> --format "{{.Size}}\t{{.CreatedBy}}"
# Deep dive analysis
dive <image>
# Build time analysis
DOCKER_BUILDKIT=1 docker build --progress=plain .
Error Handling
Common Issues
| Issue | Cause | Solution |
|---|---|---|
| Large image | No multi-stage | Implement multi-stage |
| Slow builds | Poor layer order | Dependencies before code |
| Cache not working | Context changes | Use .dockerignore |
| OOM at runtime | No limits | Set memory limits |
Troubleshooting
Debug Checklist
- BuildKit enabled? (
DOCKER_BUILDKIT=1) - Cache being used? (Check build output)
- .dockerignore working? (Check context size)
- Layers optimized? (Run
dive)
Usage
Skill("docker-optimization")
Related Skills
- docker-multi-stage
- dockerfile-basics
- docker-production
FAQ
What does the docker-optimization skill do?
Optimize Docker images and containers for size, build speed, and runtime performance
How do I install docker-optimization?
Run npx skills add https://github.com/pluginagentmarketplace/custom-plugin-docker --skill docker-optimization in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/docker-optimization/ (personal) or .claude/skills/docker-optimization/ (project).
Which AI agents can use docker-optimization?
Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.
Is docker-optimization safe to install?
No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.
Who maintains docker-optimization?
It is published by pluginagentmarketplace in pluginagentmarketplace/custom-plugin-docker. It has 72 recorded installs.
More from pluginagentmarketplace/custom-plugin-docker
docker-compose-setup
pluginagentmarketplace/custom-plugin-docker
Set up multi-container applications with Docker Compose including services, networks, and volumes
docker-swarm
pluginagentmarketplace/custom-plugin-docker
Docker Swarm orchestration, cluster management, and production deployments
docker-ci-cd
pluginagentmarketplace/custom-plugin-docker
Docker integration with CI/CD pipelines for automated builds, testing, and deployments
Popular devops & cloud skills
microsoft-foundry
microsoft/azure-skills
Build, deploy, evaluate, optimize, fine-tune, and manage Microsoft Foundry agents, models, and resources end to end. USE FOR: foundry, azd ai agent, azd provision/deploy, hosted agent scaffold/develop/run/deploy/troubleshoot, prompt agent create, managed harness agent create, GitHub Copilot harness agent, create agent, update agent, add tool to agent, invoke agent, agent insights, evaluate agent, batch eval, continuous eval, continuous monitoring, agent CI/CD, optimize prompt, improve prompt, optimize agent instructions, Agent Optimizer scaffold, dataset curation from traces, deploy model, model fine-tuning (SFT/DPO/RFT), Foundry project, RBAC, role assignment, permissions, quota, capacity, region, deployment failure, AI Services, create Foundry resource, knowledge index, customize deployment, onboard, availability, training-data, grader, distillation, large file upload. DO NOT USE FOR: Azure Functions, App Service, general Azure deploy (use azure-deploy), general Azure prep (use azure
azure-diagnostics
microsoft/azure-skills
Debug Azure production issues on Azure using AppLens, Azure Monitor, resource health, and safe triage. WHEN: debug production issues, troubleshoot app service, app service high CPU, app service deployment failure, troubleshoot container apps, container app 503 or target port mismatch, troubleshoot functions, function telemetry missing or stopped after a config/connection-string change, troubleshoot AKS, VM RDP, Linux SSH, VM black screen, can't connect to VM, reset VM password, NSG or firewall blocking, kubectl cannot connect, kube-system/CoreDNS failures, pod pending, crashloop, node not ready, upgrade failures, analyze logs, KQL, insights, image pull failures, cold start issues, health probe failures, resource health, root cause of errors, troubleshoot event hubs, troubleshoot service bus, messaging SDK error, AMQP connection failure, message lock lost, lock renewal during long-running processing, service bus dead letter.
azure-prepare
microsoft/azure-skills
Prepare azd-based Azure projects for deployment: generates azure.yaml, infrastructure (Bicep/Terraform), and Dockerfiles for the Azure Developer CLI (azd) workflow. USE ONLY when the user explicitly wants to use azd as the deployment tool, or the project already has an azure.yaml file. DO NOT USE FOR: non-azd deployments, Python App Service code-only deploys (use python-appservice-deploy), or cross-cloud migration (use azure-cloud-migrate). WHEN: prepare app for azd, create azure.yaml, set up azd infrastructure, modernize app for Azure with azd, deploy with azd, function app, timer trigger, service bus trigger, event-driven function, managed identity, generate Bicep, generate Terraform, create and deploy to Azure.
azure-ai
microsoft/azure-skills
Use for Azure AI: Search, Speech, OpenAI, Document Intelligence. Helps with search, vector/hybrid search, speech-to-text, text-to-speech, transcription, OCR. WHEN: AI Search, query search, vector search, hybrid search, semantic search, speech-to-text, text-to-speech, transcribe, OCR, convert text to speech.
azure-deploy
microsoft/azure-skills
Execute Azure deployments for ALREADY-PREPARED applications that have existing .azure/deployment-plan.md and infrastructure files. DO NOT use this skill when the user asks to CREATE a new application — use azure-prepare instead. This skill runs azd up, azd deploy, terraform apply, and az deployment commands with built-in error recovery. Requires .azure/deployment-plan.md from azure-prepare and validated status from azure-validate. WHEN: "run azd up", "run azd deploy", "execute deployment", "push to production", "push to cloud", "go live", "ship it", "bicep deploy", "terraform apply", "publish to Azure", "launch on Azure". DO NOT USE WHEN: "create and deploy", "build and deploy", "create a new app", "set up infrastructure", "create and deploy to Azure using Terraform" — use azure-prepare for these.
azure-validate
microsoft/azure-skills
Pre-deployment validation for Azure readiness. Run deep checks on configuration, infrastructure (Bicep or Terraform), RBAC role assignments, managed identity permissions, and prerequisites before deploying. WHEN: validate my app, check deployment readiness, run preflight checks, verify configuration, check if ready to deploy, validate azure.yaml, validate Bicep, test before deploying, troubleshoot deployment errors, validate Azure Functions, validate function app, validate serverless deployment, verify RBAC roles, check role assignments, review managed identity permissions, what-if analysis, validate Container Apps deployment.