How to Set Up Automated AI Code Reviews on GitHub (Step by Step)

Every pull request in your repo should be reviewed. But manual code reviews take time — often 2-4 hours per PR. And reviewers miss things when they are tired or rushed. AI code review tools read every PR automatically and leave comments in minutes. Not replacing human reviewers — augmenting them. The AI catches the obvious bugs, the human reviewer focuses on architecture and business logic. Here is how to set it up on GitHub. Three options — from easiest to most customizable. ...

April 11, 2026 · 7 min

The Best AI DevOps Tools in 2026: CI/CD, Code Review, Security, and Monitoring

DevOps used to be about writing YAML files and debugging pipelines at 2 AM. In 2026, AI handles most of that. AI DevOps tools now automate code reviews on every PR, scan for security issues before deployment, predict pipeline failures before they happen, and optimize your infrastructure costs automatically. Here are the tools that actually matter — organized by what they do. AI Code Review — Stop Reviewing Every Line Manually The biggest time sink in any development team: code reviews. AI code review tools read every pull request and give feedback in minutes instead of hours. ...

March 24, 2026 · 7 min

Docker Cheat Sheet 2026 — Commands, Dockerfile, and Compose

Bookmark this page. Use Ctrl+F (or Cmd+F on Mac) to find what you need. This cheat sheet covers Docker CLI commands, Dockerfile instructions, Docker Compose, volumes, networking, and production tips. Last updated: March 2026 How Docker Works ┌──────────────┐ docker build ┌──────────┐ docker run ┌────────────┐ │ Dockerfile │ ───────────────► │ Image │ ─────────────► │ Container │ │ (recipe) │ │ (template)│ │ (running) │ └──────────────┘ └──────────┘ └────────────┘ │ docker push │ ┌────▼───────┐ │ Registry │ │ (Docker Hub)│ └────────────┘ Container Commands Command Description docker run <image> Create and start a container docker run -d <image> Run in background (detached) docker run -it <image> bash Run interactively with shell (sh for Alpine) docker run -p 8080:80 <image> Map host port 8080 to container port 80 docker run --name myapp <image> Run with a custom name docker run --rm <image> Automatically remove container when it stops docker run -e KEY=value <image> Set environment variable docker run -v /host:/container <image> Mount a volume docker ps List running containers docker ps -a List all containers (including stopped) docker stop <container> Stop a running container docker start <container> Start a stopped container docker restart <container> Restart a container docker rm <container> Remove a stopped container docker rm -f <container> Force remove (even if running) docker exec -it <container> bash Open a shell inside a running container docker logs <container> View container logs docker logs -f <container> Follow logs in real-time docker inspect <container> Show detailed container info (JSON) docker stats Live resource usage for all containers docker cp <container>:/path ./local Copy file from container to host docker cp ./local <container>:/path Copy file from host to container docker container prune Remove all stopped containers docker kill <container> Force stop a container (SIGKILL) Image Commands Command Description docker images List all local images docker pull <image> Download an image from registry docker push <image> Upload an image to registry docker build -t myapp . Build image from Dockerfile in current dir docker build -t myapp:v1 . Build with a tag/version docker tag <image> <new-tag> Add a tag to an image docker rmi <image> Remove an image docker image prune Remove unused (dangling) images docker system prune -a Remove all unused images, containers, networks (not volumes) docker system prune -a --volumes Remove everything including volumes docker history <image> Show image layers and sizes docker login Log in to Docker Hub (required before push) docker logout Log out from registry docker save -o image.tar <image> Export image to tar file docker load -i image.tar Import image from tar file Dockerfile Reference # Base image FROM node:20-alpine # Set working directory WORKDIR /app # Copy dependency files first (for caching) COPY package.json package-lock.json ./ # Install dependencies RUN npm ci --production # Copy application code COPY . . # Expose a port (documentation only) EXPOSE 3000 # Default command when container starts CMD ["node", "server.js"] Dockerfile Instructions Instruction Description FROM <image> Base image (required, must be first) WORKDIR /app Set working directory for subsequent commands COPY <src> <dest> Copy files from host to image ADD <src> <dest> Like COPY but can extract tar and fetch URLs RUN <command> Execute command during build (creates a layer) ENV KEY=value Set environment variable ARG KEY=value Build-time variable (not available at runtime) EXPOSE <port> Document which port the app listens on CMD ["executable", "arg"] Default command (can be overridden) ENTRYPOINT ["executable"] Fixed command (CMD becomes arguments) VOLUME /data Create a mount point for persistent data USER <username> Switch to non-root user `HEALTHCHECK CMD curl -f http://localhost/ CMD vs ENTRYPOINT # CMD — default command, can be overridden CMD ["python", "app.py"] # docker run myapp → runs python app.py # docker run myapp bash → runs bash (overrides CMD) # ENTRYPOINT — fixed command, CMD becomes arguments ENTRYPOINT ["python"] CMD ["app.py"] # docker run myapp → runs python app.py # docker run myapp test.py → runs python test.py Multi-Stage Build # Stage 1: Build FROM node:20-alpine AS builder WORKDIR /app COPY package.json ./ RUN npm ci COPY . . RUN npm run build # Stage 2: Production (smaller image) FROM nginx:alpine COPY --from=builder /app/dist /usr/share/nginx/html EXPOSE 80 CMD ["nginx", "-g", "daemon off;"] Multi-stage builds produce smaller images — the final image only contains the production output, not the build tools. ...

March 19, 2026 · 6 min