docker-essentialsEssential Docker commands and workflows for container management, image operations, and debugging.
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Essential Docker commands for container and image management.
# Run container from image
docker run nginx
# Run in background (detached)
docker run -d nginx
# Run with name
docker run --name my-nginx -d nginx
# Run with port mapping
docker run -p 8080:80 -d nginx
# Run with environment variables
docker run -e MY_VAR=value -d app
# Run with volume mount
docker run -v /host/path:/container/path -d app
# Run with auto-remove on exit
docker run --rm alpine echo "Hello"
# Interactive terminal
docker run -it ubuntu bash
# List running containers
docker ps
# List all containers (including stopped)
docker ps -a
# Stop container
docker stop container_name
# Start stopped container
docker start container_name
# Restart container
docker restart container_name
# Remove container
docker rm container_name
# Force remove running container
docker rm -f container_name
# Remove all stopped containers
docker container prune
# Show logs
docker logs container_name
# Follow logs (like tail -f)
docker logs -f container_name
# Last 100 lines
docker logs --tail 100 container_name
# Logs with timestamps
docker logs -t container_name
# Execute command in running container
docker exec container_name ls -la
# Interactive shell
docker exec -it container_name bash
# Execute as specific user
docker exec -u root -it container_name bash
# Execute with environment variable
docker exec -e VAR=value container_name env
# Inspect container details
docker inspect container_name
# Get specific field (JSON path)
docker inspect -f '{{.NetworkSettings.IPAddress}}' container_name
# View container stats
docker stats
# View specific container stats
docker stats container_name
# View processes in container
docker top container_name
# Build from Dockerfile
docker build -t myapp:1.0 .
# Build with custom Dockerfile
docker build -f Dockerfile.dev -t myapp:dev .
# Build with build args
docker build --build-arg VERSION=1.0 -t myapp .
# Build without cache
docker build --no-cache -t myapp .
# List images
docker images
# Pull image from registry
docker pull nginx:latest
# Tag image
docker tag myapp:1.0 myapp:latest
# Push to registry
docker push myrepo/myapp:1.0
# Remove image
docker rmi image_name
# Remove unused images
docker image prune
# Remove all unused images
docker image prune -a
# Start services
docker-compose up
# Start in background
docker-compose up -d
# Stop services
docker-compose down
# Stop and remove volumes
docker-compose down -v
# View logs
docker-compose logs
# Follow logs for specific service
docker-compose logs -f web
# Scale service
docker-compose up -d --scale web=3
# List services
docker-compose ps
# Execute command in service
docker-compose exec web bash
# Restart service
docker-compose restart web
# Rebuild service
docker-compose build web
# Rebuild and restart
docker-compose up -d --build
# List networks
docker network ls
# Create network
docker network create mynetwork
# Connect container to network
docker network connect mynetwork container_name
# Disconnect from network
docker network disconnect mynetwork container_name
# Inspect network
docker network inspect mynetwork
# Remove network
docker network rm mynetwork
# List volumes
docker volume ls
# Create volume
docker volume create myvolume
# Inspect volume
docker volume inspect myvolume
# Remove volume
docker volume rm myvolume
# Remove unused volumes
docker volume prune
# Run with volume
docker run -v myvolume:/data -d app
# View disk usage
docker system df
# Clean up everything unused
docker system prune
# Clean up including unused images
docker system prune -a
# Clean up including volumes
docker system prune --volumes
# Show Docker info
docker info
# Show Docker version
docker version
Development container:
docker run -it --rm \
-v $(pwd):/app \
-w /app \
-p 3000:3000 \
node:18 \
npm run dev
Database container:
docker run -d \
--name postgres \
-e POSTGRES_PASSWORD=secret \
-e POSTGRES_DB=mydb \
-v postgres-data:/var/lib/postgresql/data \
-p 5432:5432 \
postgres:15
Quick debugging:
# Shell into running container
docker exec -it container_name sh
# Copy file from container
docker cp container_name:/path/to/file ./local/path
# Copy file to container
docker cp ./local/file container_name:/path/in/container
Multi-stage build:
# Dockerfile
FROM node:18 AS builder
WORKDIR /app
COPY package*.json ./
RUN npm install
COPY . .
RUN npm run build
FROM nginx:alpine
COPY --from=builder /app/dist /usr/share/nginx/html
docker run flags:
-d: Detached mode (background)-it: Interactive terminal-p: Port mapping (host:container)-v: Volume mount-e: Environment variable--name: Container name--rm: Auto-remove on exit--network: Connect to networkdocker exec flags:
-it: Interactive terminal-u: User-w: Working directory.dockerignore to exclude files from build contextRUN commands in Dockerfile to reduce layers--rm for one-off containersdocker-compose for multi-container appsdocker system pruneOfficial docs: https://docs.docker.com/
Dockerfile reference: https://docs.docker.com/engine/reference/builder/
Compose file reference: https://docs.docker.com/compose/compose-file/
Generated Feb 26, 2026
Developers use Docker to create isolated, reproducible development environments for applications. This ensures consistency across team members and eliminates 'it works on my machine' issues by containerizing dependencies and runtime.
Organizations deploy microservices architectures using Docker containers to manage and scale individual services independently. This enables efficient resource utilization, rapid deployment cycles, and easier maintenance in cloud-native environments.
Teams integrate Docker into CI/CD pipelines to run automated tests in isolated containers. This provides consistent testing environments, speeds up build processes, and ensures code quality by testing against the same configurations as production.
Database administrators use Docker to quickly spin up and manage database instances like PostgreSQL or MySQL for development, testing, or staging. This allows for easy version management, data isolation, and simplified backup processes through volume mounts.
Instructors and trainers leverage Docker to provide hands-on learning environments for students in courses on containerization, DevOps, or software engineering. Containers offer sandboxed setups that can be easily reset or shared across participants.
Companies offer software-as-a-service solutions where each customer's instance runs in isolated Docker containers. This enables multi-tenancy, scalable resource allocation, and simplified updates, reducing infrastructure costs and improving deployment efficiency.
Consulting firms provide Docker expertise to help businesses containerize their applications, set up CI/CD pipelines, and optimize cloud deployments. This includes ongoing management, monitoring, and support for containerized environments.
Platforms host and distribute pre-configured Docker images for common software stacks, databases, or tools. Developers can quickly deploy these images, with revenue generated through licensing fees, premium support, or enterprise features.
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