Dot AI Generate Dockerfile

Generate Production-Ready Dockerfile

Generate an optimized, secure, multi-stage Dockerfile and .dockerignore for the current project by analyzing its structure, language, framework, and dependencies.

Instructions

You are helping a developer containerize their application for production deployment. Your task is to analyze the project structure and generate two files:

1. Dockerfile: Production-ready, multi-stage build with security best practices
2. .dockerignore: Optimized build context configuration

Critical Principles

These are non-negotiable rules that override all other guidance.

Verify Everything Before Adding It

ABSOLUTE RULE: Before adding ANY instruction, configuration, or feature to the Dockerfile, verify it by examining the actual codebase.

Required Process:

1. Identify what you think should be added
2. Search the codebase to verify it exists or is actually needed
3. Only add if verified - if you can't find evidence in the code, don't add it
4. When uncertain, ask the user - if you cannot deduce something from the codebase analysis, ask the user rather than guessing

Never assume. Always verify. Ask when uncertain. Evidence-based Dockerfiles only.

Thoroughness over speed: Shallow analysis leads to broken Dockerfiles. Before generating anything:

• Read the actual source files, not just file names or directory listings
• Search for patterns multiple times with different queries if needed
• Trace the application entry point through its imports and dependencies
• Don't stop at the first search result - investigate thoroughly
• If analysis feels quick, you probably missed something

A correct Dockerfile that took longer to generate is far better than a fast but broken one. Spend the time upfront.

Multi-Architecture Support

REQUIREMENT: Ensure all Dockerfile instructions support multiple architectures (amd64, arm64, etc.).

Apply to:

• Base image selection: Use multi-arch official images
• Binary downloads: Detect architecture dynamically, never hardcode (amd64, x86_64, etc.)
• System package installation: Use package manager (automatically handles architecture)
• Build commands: Ensure cross-platform compatibility

The Dockerfile must build successfully on different CPU architectures without modification.

NEVER Add HEALTHCHECK

ABSOLUTE PROHIBITION: DO NOT add HEALTHCHECK instruction under ANY circumstances.

Why:

• Health endpoints are application-specific and cannot be verified from codebase analysis
• Adding unverified health checks will cause containers to be marked unhealthy incorrectly
• Users will add their own HEALTHCHECK if their application has health endpoints

If you add HEALTHCHECK, you are violating the "verify everything" principle.

Best Practices Reference

These are best practices to consider when generating the Dockerfile. Apply them when relevant to the project - not every practice applies to every situation:

• Package manager flags depend on which package manager is used (apt-get vs apk vs others)
• Language-specific guidance applies only to that language
• The "verify everything" principle overrides all: if a practice doesn't fit the project, skip it

Use this section as guidance during generation and a reference for validation.

Security

Image Selection

Build Optimization

Maintainability

Process

Step 0: Check for Existing Dockerfile

Before generating anything, check if the project already has a Dockerfile.

1. Look for Dockerfile in the project root (also check for variants like Dockerfile.prod)
2. If found, read and store its contents for Step 2
3. Similarly, check for .dockerignore and read it if present

This determines whether Step 2 will generate new files or improve existing ones.

Step 1: Analyze Project Structure

Identify the project characteristics through exploration, not pattern matching.

These are analysis goals, not lookup tables. The examples below are illustrative - apply the same analytical approach to ANY language, framework, or toolchain you encounter.

1. Language Detection: Explore the project to identify its programming language(s).

   • Look for dependency manifest files (e.g., package.json, go.mod, requirements.txt, Cargo.toml, Gemfile, composer.json, mix.exs, build.sbt, etc.)
   • Examine source file extensions
   • Read manifest contents to understand the ecosystem
   • Principle: Every language has some form of dependency declaration - find it and read it

2. Version Detection: Find the required language/runtime version.

   • Search manifest files for version constraints or engine requirements
   • Look for version files (e.g., .node-version, .python-version, .ruby-version, .tool-versions)
   • Check CI configuration files which often specify versions
   • If project specifies a version → use that exact version
   • If no version specified → search online for the current LTS/stable version of that language/runtime
   • Principle: Use the project's required version if specified, otherwise look up the current recommended version - never guess

3. Framework Detection: Identify frameworks from dependencies and project structure.

   • Read the dependency list in manifest files
   • Look for framework-specific configuration files
   • Examine the project structure for framework conventions
   • Principle: Frameworks leave fingerprints - configuration files, directory structures, dependencies

4. Application Type: Determine what kind of application this is by examining entry points and configuration.

   • Web server/API: Look for HTTP server setup, route definitions, port binding
   • CLI tool: Look for argument parsing, command definitions, bin entries
   • Worker/background job: Look for queue consumers, scheduled tasks
   • Static site: Look for build output configuration, no server code
   • Principle: The entry point and its imports reveal the application's purpose

5. Port Detection: Search for port configuration in source code and configuration files.

   • Look for environment variable usage (e.g., PORT, HTTP_PORT)
   • Search for hardcoded port numbers in server initialization
   • Check configuration files for port settings
   • Only add EXPOSE if you find concrete evidence

6. Build Requirements: Identify how the project is built.

   • Read the manifest file for build scripts/commands
   • Identify the build tool (could be language-standard or third-party)
   • Determine build outputs (compiled binaries, transpiled code, bundled assets)
   • Principle: Every project that needs building has build instructions - find them

7. System Dependencies: Critical step - missing runtime binaries cause silent failures.

   • Search the codebase for code that executes external commands or binaries
   • Common patterns: shell execution, subprocess calls, exec functions, system calls
   • For each binary found, verify it's needed at runtime (not just build time)
   • Consider what the application actually does - does it need CLI tools, database clients, image processors?
   • When uncertain whether something is a runtime dependency, ask the user

8. Environment Variable Detection: Critical step - missing env vars cause runtime failures.

   • Search the codebase for environment variable access (every language has a way to read env vars)
   • Look for .env.example, .env.sample, or similar files that document required variables
   • Check configuration and startup code for env var usage
   • Determine which vars are required (no default, app fails without) vs optional (has default)
   • For required vars, set sensible defaults in the Dockerfile
   • Principle: If the code reads an env var, the container probably needs it configured

Step 2: Generate or Improve Dockerfile

If no existing Dockerfile → Generate a new multi-stage Dockerfile using the patterns below.

If existing Dockerfile found → Analyze it against the best practices and checklists below, then improve:

1. Evaluate against checklists - Check each item in the Builder and Runtime checklists
2. Identify issues - Security problems (running as root, :latest tags), missing optimizations (no multi-stage, COPY . .), maintainability issues
3. Preserve intentional customizations - Comments explaining decisions, custom configurations, environment-specific settings
4. Edit to fix issues - Apply best practices while keeping the existing structure where it's already correct
5. Explain changes - When presenting the improved Dockerfile, briefly note what was changed and why

Use the patterns and checklists below for both generation and validation.

The examples below show structural patterns, not copy-paste templates. Adapt the pattern to whatever language, package manager, and build tool the project uses.

Stage 1: Builder

# Build stage - use an image with build tools for this language
FROM <language-image>:<version>-<variant> AS builder

WORKDIR /app

# PATTERN: Copy dependency manifests FIRST for layer caching
# Examples: package.json, go.mod, requirements.txt, Gemfile, Cargo.toml, pom.xml
COPY <dependency-manifest-files> ./

# PATTERN: Install dependencies, clean cache in same layer
# Use whatever package manager the project uses
RUN <install-dependencies-command> && \
    <clean-cache-command>

# PATTERN: Copy only the source files needed for build
# Never use "COPY . ." - be explicit about what's needed
COPY <source-directories> ./
COPY <config-files-needed-for-build> ./

# PATTERN: Run the project's build command
RUN <build-command>

Builder stage checklist:

• Named stage (AS builder)
• Base image appropriate for the language (with build tools)
• Version derived from project files (not assumed)
• Dependency manifests copied before source code
• Dependencies installed with cache cleanup in same RUN
• Only required files copied (never COPY . .)
• Build command matches what the project actually uses

Stage 2: Runtime

# Runtime stage - use minimal image appropriate for the language
# Compiled languages: consider distroless, scratch, or alpine
# Interpreted languages: use slim or alpine variant with runtime only
FROM <minimal-runtime-image>:<version>

WORKDIR /app

# PATTERN: Create non-root user (syntax varies by base image)
# Alpine uses addgroup/adduser, Debian uses groupadd/useradd
RUN <create-group-command> && \
    <create-user-command>

# PATTERN: Copy ONLY runtime artifacts from builder
# What you copy depends on the language:
# - Compiled: just the binary
# - Interpreted: built output + runtime dependencies + minimal config
COPY --from=builder <build-outputs> ./
COPY --from=builder <runtime-dependencies> ./

# PATTERN: Set ownership to non-root user
RUN chown -R <user>:<group> /app

# Switch to non-root user BEFORE exposing ports or setting CMD
USER <non-root-user>

# Only if port was verified during analysis
EXPOSE <port>

# PATTERN: Use exec form for proper signal handling
# The command depends on how this application runs
CMD ["<executable>", "<args>"]

Runtime stage checklist:

• Minimal base image (alpine/slim/distroless/scratch as appropriate)
• Non-root user created (UID 10001+)
• Only runtime artifacts copied from builder
• No source code, tests, build tools, or dev dependencies
• Proper ownership set
• USER directive before CMD
• EXPOSE only if port was verified in analysis
• CMD in exec form (JSON array)

System Package Installation Pattern

When system packages are required, use the package manager appropriate for your base image. The principle is always the same: install only what's needed and clean the cache in the same layer.

Common examples (adapt to your base image's package manager):

# apt-get (Debian, Ubuntu)
RUN apt-get update && \
    apt-get install -y --no-install-recommends \
        package1 \
        package2 && \
    rm -rf /var/lib/apt/lists/*

# apk (Alpine)
RUN apk add --no-cache \
        package1 \
        package2

# yum/dnf (RHEL, Fedora, CentOS)
RUN yum install -y \
        package1 \
        package2 && \
    yum clean all && \
    rm -rf /var/cache/yum

Package installation checklist:

• Used the correct package manager for the base image
• Used flags to skip optional/recommended packages where available
• Packages sorted alphabetically for maintainability
• Cache cleaned in same RUN command
• Only packages actually required by the application

Step 3: Create or Improve .dockerignore

If no existing .dockerignore → Generate a minimal one based on the Dockerfile.

If existing .dockerignore found → Review it against the Dockerfile's COPY commands:

1. Remove redundant exclusions (directories not copied by Dockerfile anyway)
2. Add missing security exclusions (secrets inside copied directories)
3. Keep it minimal (~10-15 lines)

Generate a MINIMAL .dockerignore file based on the Dockerfile.

Since the Dockerfile uses explicit COPY commands (not COPY . .), .dockerignore serves a limited purpose:

1. Security - Exclude secret patterns that could exist INSIDE directories being copied
2. Performance - Exclude large directories that slow down build context transfer

Process

1. Review your Dockerfile's COPY commands - what directories does it copy?
2. Identify security risks inside those directories (secret files that could accidentally exist)
3. Identify large directories in the project (>1MB) that slow context transfer
4. Exclude ONLY those items

What NOT To Exclude

DO NOT exclude directories that aren't copied by your Dockerfile!

If your Dockerfile doesn't copy a directory, excluding it in .dockerignore is pointless redundancy.

Target Size

~10-15 lines maximum. If your .dockerignore exceeds 20 lines, you're likely adding unnecessary exclusions.

Step 4: Build, Test, and Iterate

Purpose: Verify the Dockerfile works before presenting to user. A Dockerfile isn't done until it's validated.

4.1 Build

Build the image to verify the Dockerfile syntax and instructions are correct:

docker build -t [project-name]-validation .

• If build succeeds → proceed to run
• If build fails → analyze the error, fix Dockerfile, retry

4.2 Run

Start a container to verify the application runs:

docker run -d --name [project-name]-test [project-name]-validation
sleep 5  # Allow startup time

Check container state:

docker inspect --format='{{.State.Status}}' [project-name]-test
docker inspect --format='{{.State.ExitCode}}' [project-name]-test

Expected behavior depends on application type (determined in Step 1):

• Services (web servers, APIs, workers): Container should still be running
• CLI tools / one-shot commands: Container should have exited with code 0

If container crashed or exited unexpectedly → proceed to log analysis to understand why.

4.3 Log Analysis

Capture and analyze container logs:

docker logs [project-name]-test 2>&1

Analyze logs using your knowledge of the project from Step 1. You know:

• What language and framework this is
• What the application is supposed to do
• What dependencies it requires
• What a successful startup looks like for this type of application

Use this context to determine if the logs indicate:

• The application started correctly, OR
• Something is wrong (errors, crashes, missing dependencies, permission issues, etc.)

If logs indicate a problem → identify root cause, fix Dockerfile or .dockerignore, retry.

4.4 Linting (if available)

If hadolint is installed, run it to catch Dockerfile best practice issues:

hadolint Dockerfile

• If hadolint is not installed → skip this check
• If hadolint reports issues → evaluate each issue, fix if appropriate, retry
• Some hadolint warnings may be intentional (use judgment based on project context)

4.5 Security Scan (if available)

If trivy is installed, scan the built image for vulnerabilities:

trivy image --severity HIGH,CRITICAL [project-name]-validation

• If trivy is not installed → skip this check
• If trivy reports HIGH/CRITICAL vulnerabilities in the base image → consider if a different base image version or variant would help
• If vulnerabilities are in application dependencies → note them for the user but don't block (dependency updates are outside Dockerfile scope)

4.6 Iterate

If any validation step fails:

1. Analyze the specific error message or behavior
2. Identify root cause - common issues include:
   • Missing file → incorrect COPY command or overly aggressive .dockerignore
   • Missing dependency → system package not installed
   • Permission denied → ownership or USER directive issue
   • Module not found → build step incomplete or wrong files copied
   • Hadolint warning → Dockerfile best practice issue
3. Fix the appropriate file (Dockerfile or .dockerignore)
4. Retry from step 4.1

Maximum 5 iterations. If still failing after 5 attempts:

• Stop and present current state to user
• Explain what's failing and what fixes were attempted
• Ask for guidance

4.7 Cleanup

Always clean up after validation, whether successful or not:

docker stop [project-name]-test 2>/dev/null || true
docker rm [project-name]-test 2>/dev/null || true
docker rmi [project-name]-validation 2>/dev/null || true

Only proceed to present the Dockerfile to user after:

• All validation steps pass, AND
• Cleanup is complete

Output Format

For New Dockerfiles (no existing file)

Present both files to the user:

1. Dockerfile with clear comments explaining each section
2. .dockerignore with organized sections

After generating, provide:

• Brief explanation of design choices (base images, build stages, security measures)
• Build command: docker build -t [project-name] .
• Run command: docker run -p [port]:[port] [project-name]
• Image size expectations

For Improved Dockerfiles (existing file found)

Present the improved files with a summary of changes:

1. Dockerfile - the improved version
2. Changes made - brief list of what was changed and why:
   • Security fixes (e.g., "Added non-root user - was running as root")
   • Optimization improvements (e.g., "Added multi-stage build to reduce image size")
   • Best practice updates (e.g., "Changed CMD to exec form for signal handling")
3. Preserved - note any intentional customizations that were kept
4. .dockerignore - improved version if changes were needed

For Both Cases

Recommended next steps (the Dockerfile has already been validated):

• Integrate into CI/CD pipeline
• Commit to version control

Success Criteria

Dockerfile Checklist

• Builds successfully without errors
• Uses multi-stage build (builder → runtime)
• Runs as non-root user (UID 10001+)
• Uses pinned version tags (no :latest)
• Uses minimal base images (alpine/slim/distroless)
• Copies dependency manifests before source (layer caching)
• Uses explicit COPY (no COPY . .)
• Combines RUN commands with &&
• Cleans package manager caches in same layer
• Uses --no-install-recommends (if apt-get used)
• Uses exec form for CMD (["executable", "arg"])
• No debugging tools unless required
• No secrets or credentials embedded

.dockerignore Checklist

• Minimal size (~10-15 lines)
• Excludes secrets inside copied directories
• Excludes large unnecessary directories
• Does NOT exclude directories not copied by Dockerfile

Validation Checklist (Step 4)

• Image builds successfully
• Container starts without crashing
• Logs show no errors indicating application failure
• Hadolint passes (if installed)
• Trivy shows no critical base image vulnerabilities (if installed)
• Test container and image cleaned up

Do not present Dockerfile to user until all validation checks pass.

Example Workflows

New Dockerfile (no existing file)

1. Check: "No existing Dockerfile found. Will generate new one."
2. Explore: "Let me find the dependency manifest... found <manifest-file>. Reading it to understand the ecosystem."
3. Identify: "This is a <language> project using <framework/tool>. The manifest indicates version <X>."
4. Trace: "The entry point is <file>. Following imports to understand runtime needs."
5. Structure: "Multi-stage build: builder stage needs <build-tools>, runtime stage needs only <runtime-artifacts>."
6. Dependencies: "Searching for external binary usage... found <binary>. This needs to be in the runtime image."
7. Generate: "Create Dockerfile and .dockerignore. Check against best practices checklists."
8. Build & Test: "Building image... Running container... Checking logs..."
9. Iterate (if needed): "Build failed due to missing package. Adding to Dockerfile and retrying..."
10. Cleanup & Present: "Validation passed. Removing test artifacts. Here's your Dockerfile."

Improving Existing Dockerfile

1. Check: "Found existing Dockerfile. Reading it to analyze..."
2. Analyze project: Same exploration as above to understand what the Dockerfile should do.
3. Evaluate: "Checking existing Dockerfile against best practices checklists..."
   • "❌ Running as root - no USER directive"
   • "❌ Using :latest tag instead of pinned version"
   • "✅ Multi-stage build already in place"
   • "✅ Dependency manifests copied first"
4. Preserve: "Keeping custom ENV variables and the specific port configuration - these appear intentional."
5. Improve: "Adding non-root user, pinning image version to match project requirements."
6. Build & Test: "Building improved image... Running container... Checking logs..."
7. Iterate (if needed): "Container crashed - logs show permission error. Fixing ownership and retrying..."
8. Cleanup & Present: "Validation passed. Removing test artifacts. Here are the improvements."

Key mindset: Investigate the actual project rather than matching against templates. Every project is unique. Don't present until validated.

Source: vfarcic/dot-ai — distributed by TomeVault.