Debugging Docker Operations

Overview

Systematic troubleshooting workflows for Docker build failures, runtime errors, AWS container services, platform-specific issues, and performance optimization. Designed for multi-platform environments (ARM64/AMD64/WSL2) with pharmaceutical compliance contexts requiring GAMP-5 validation.

When to Use

• Build Failures: Package installation errors, COPY failures, layer caching issues
• Runtime Errors: Container crashes, exit codes, DNS resolution, port conflicts
• AWS Container Services: ECR authentication, ECS pull failures, rate limiting
• Platform Issues: ARM64 vs AMD64 emulation, WSL2 integration, cross-platform builds
• Performance Problems: Slow builds, large images, QEMU emulation overhead
• Volumes/Networking: Permission errors, mount failures, port binding

Available Tools

Standard Tools

AWS MCP Tools

mcp__aws-api-mcp__call_aws

mcp__aws-knowledge-mcp__aws___search_documentation

mcp__aws-ccapi-mcp__list_resources

Core Workflow

Phase 1: Symptom Diagnosis

Objective: Identify problem category and gather diagnostic information

1. Identify Problem Type

   # For build failures
   docker build 2>&1 | tee build.log
   
   # For runtime errors
   docker logs <container-name>
   docker inspect <container-name>
   
   # For AWS issues
   aws ecr describe-repositories
   aws ecs describe-tasks --cluster <cluster> --tasks <task-arn>
   

2. Categorize the Issue

   • Build Failure (exit during

     docker build

     )
   • Runtime Error (container exits or crashes)
   • AWS ECR/ECS Issue (authentication, pull failures)
   • Platform/Architecture Issue (ARM64/AMD64 mismatch)
   • Performance Problem (slow or inefficient)
   • Networking/Volume Issue

3. Collect Context

   docker version && docker info | head -30
   uname -m  # Platform: x86_64 or aarch64
   

Quality Gate: Problem type identified, initial logs collected

Phase 2: Root Cause Analysis

Build Failures

Common Patterns:

# Check build log for specific failures
grep -E "ERROR|failed|error:" build.log

# Common patterns:
# "COPY failed" → File not in build context
# "returned a non-zero code" → Command failed
# "no matching manifest" → Platform mismatch

Key Checks:

• Build context:

  ls -la <path-to-file>

• .dockerignore:

  cat .dockerignore

• Layer caching:

  docker build --no-cache

See

reference/common-errors.md

Runtime Errors

Exit Code Quick Reference:

Diagnosis:

docker inspect <container> | jq '.[0].State'
docker logs --tail 100 <container>

AWS ECR/ECS Issues

ECR Authentication:

Error: "no basic auth credentials"

• Cause: ECR login token expired (12-hour validity)
• Fix:

  aws ecr get-login-password --region eu-west-2 | \
    docker login --username AWS --password-stdin \
    <account-id>.dkr.ecr.eu-west-2.amazonaws.com
  

ECS Pull Failures:

Error: "CannotPullContainerError"

• Checklist:
  1. Task execution role has ECR permissions
  2. VPC has NAT Gateway (for private subnets)
  3. Image tag exists in ECR

Using AWS MCP:

# Check ECR images
mcp__aws-api-mcp__call_aws: aws ecr describe-images --repository-name <repo>

# Check ECS task failures
mcp__aws-api-mcp__call_aws: aws ecs describe-tasks --cluster <cluster> --tasks <task-arn>

See

reference/aws-ecr-ecs.md

Platform/Architecture Issues

Slow Build Detection:

# Check if emulation is active (ARM64 host building AMD64)
docker run --rm --platform=linux/amd64 alpine uname -m
# If output shows x86_64 on ARM64 host → emulation active (slow)

Solutions:

1. Use native platform for development
2. Build target platform only for deployment
3. Use multi-stage with

   ${BUILDPLATFORM}

See

reference/platform-guide.md

Quality Gate: Root cause identified, specific error patterns documented

Phase 3: Solution & Validation

Build Failure Fixes

# Fix missing file in context
# Verify path exists: ls -la <path>
COPY main.py /app/

# Fix package installation with retry
RUN pip install --no-cache-dir -r requirements.txt || \
    (pip install --upgrade pip && pip install --no-cache-dir -r requirements.txt)

# Fix platform issues
# docker build --platform=linux/amd64 -t image:prod .

Runtime Error Fixes

# Fix permission issues
docker run --user $(id -u):$(id -g) image:tag

# Fix OOM (Exit 137)
docker run -m 2g --memory-swap 2g image:tag

# Fix port conflicts
docker run -p 8081:8080 image:tag  # Change host port

AWS Fixes

# Refresh ECR credentials
aws ecr get-login-password --region eu-west-2 | docker login --username AWS --password-stdin <account>.dkr.ecr.eu-west-2.amazonaws.com

# Fix Docker Hub rate limiting - use ECR Public
# FROM public.ecr.aws/docker/library/python:3.12-slim

Validation

# Rebuild with verbose output
docker build --progress=plain -f Dockerfile -t image:test .

# Test container startup
docker run --rm image:test

# Verify functionality
docker run -it image:test /bin/sh -c "command-to-test"

Quality Gate: Fix applied, container builds and runs without errors

Quick Reference Table

aws ecr get-login-password | docker login

ls -la <file>

docker inspect

--platform

.wslconfig

docker-compose down && up -d

docker ps

Best Practices

Build Optimization

• Layer ordering: Dependencies before code (cache efficiency)
• Multi-stage builds: Separate build and runtime environments
• Use .dockerignore: Exclude

  node_modules

  ,

  .git

  ,

  __pycache__

Security

# Non-root user
RUN adduser -D appuser
USER appuser

# Never COPY secrets - use --secret flag

Platform Handling

# Development (native platform - fast)
docker build -t image:dev .

# Production (target platform)
docker build --platform=linux/amd64 -t image:prod .

# Multi-platform with cache
docker buildx build \
  --platform linux/amd64,linux/arm64 \
  --cache-from type=registry,ref=<repo>:cache \
  --cache-to type=registry,ref=<repo>:cache \
  -t image:multi --push .

WSL2 Performance

• Store projects in WSL2 filesystem (

  ~/

  ), NOT Windows mount (

  /mnt/c/

  )
• Configure

  .wslconfig

  with memory limits
• Use

  wsl --shutdown

  to reclaim memory

See

reference/wsl2-optimization.md

Common Pitfalls

Don't: Use relative paths without verification

# WRONG - may fail if context is incorrect
COPY ../app/file.py /app/

# RIGHT - relative to build context root
COPY app/file.py /app/

Do: Use explicit platform for production

# WRONG - platform inferred (may differ from prod)
docker build -t api:latest .

# RIGHT - explicit platform
docker build --platform=linux/amd64 -t api:latest .

Do: Verify volume mounts work

# Check if container sees host files
docker exec <container> ls -la /app/

# Recreate containers after mount changes
docker-compose down && docker-compose up -d

Quality Checklist

• Problem type identified (build/runtime/AWS/platform/network/volume)
• Diagnostic logs collected and analyzed
• Root cause determined with specific error patterns
• Solution applied with appropriate fix
• Build succeeds without errors
• Container starts and runs successfully
• Functionality validated
• Platform architecture verified (matches deployment target)
• Security checked (non-root user, no exposed secrets)

Detailed References

• Docker Commands:

  reference/docker-commands.md

• Common Error Matrix:

  reference/common-errors.md

  (20+ error patterns)
• AWS ECR/ECS Guide:

  reference/aws-ecr-ecs.md

• Platform Guide:

  reference/platform-guide.md

  (ARM64/AMD64/WSL2, buildx caching)
• WSL2 Optimization:

  reference/wsl2-optimization.md

• Build Optimization:

  reference/build-optimization.md

• Security Hardening:

  reference/security-hardening.md

Diagnostic Scripts

• Build Failure Analysis:

  scripts/analyze-build-failure.sh <log-file>

• Container Inspection:

  scripts/inspect-container.sh <container-name>

• Platform Check:

  scripts/check-platform.sh

Remember: Docker issues are systematic and diagnosable. Follow the three-phase workflow (Symptom → Root Cause → Solution), use AWS MCP tools for ECR/ECS issues, and reference the detailed guides for complex scenarios. Always validate fixes before considering the issue resolved.