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Docker Production

  • 29 installs
  • 2 repo stars
  • Updated January 5, 2026
  • pluginagentmarketplace/custom-plugin-docker

docker-production is an agent skill that guides solo builders through a Docker production checklist before and after release.

About

docker-production is a configuration-oriented agent skill that packages a Docker production playbook as skill metadata plus a four-part checklist: pre-deployment, monitoring, high availability, and backup/recovery. Solo builders shipping APIs or SaaS in containers can use it as a repeatable gate before promoting images, instead of improvising ops steps in chat. The bundled schema toggles validation strictness by environment (looser in development, strict in production) and wires optional integrations for git, linter, and formatter. It does not replace a full platform runbook, but it gives your coding agent a consistent vocabulary and ordered concerns when reviewing Dockerfiles, compose files, or deployment manifests for production readiness.

  • Pre-deployment checklist: image scan, secrets, resource limits, health checks, logging
  • Production monitoring block: CPU/memory metrics, centralized logs, alerts, dashboard
  • High availability: replicas, load balancer, graceful shutdown, rolling updates
  • Backup & recovery: volume backups, tested recovery, documented rollback
  • Environment overrides with strict_mode enabled in production

Docker Production by the numbers

  • 29 all-time installs (skills.sh)
  • Ranked #863 of 1,453 DevOps & CI/CD skills by installs in the Skillselion catalog
  • Security screen: HIGH risk (skills.sh audit)
  • Data as of Jul 26, 2026 (Skillselion catalog sync)
npx skills add https://github.com/pluginagentmarketplace/custom-plugin-docker --skill docker-production

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Listed on Skillselion
Installs29
repo stars2
Security audit1 / 3 scanners passed
Last updatedJanuary 5, 2026
Repositorypluginagentmarketplace/custom-plugin-docker

What it does

Run a structured Docker production readiness checklist before you ship containers to real users.

Who is it for?

Best when you're containerizing a backend or SaaS and want agent-guided release hardening without hiring a dedicated platform team.

Skip if: Local-only dev containers with no production target, or teams already standardized on a managed PaaS that owns scanning and HA end-to-end.

When should I use this skill?

You are preparing or operating Docker workloads in production and need a consistent checklist-driven review.

What you get

You get an ordered production checklist and environment-aware validation defaults so releases and ongoing ops follow the same Docker standards.

  • Production readiness review against the checklist
  • Environment-tuned validation settings (dev vs production strict_mode)

By the numbers

  • 4 checklist sections: pre-deployment, monitoring, high availability, backup & recovery

Files

SKILL.mdMarkdownGitHub ↗

Docker Production Skill

Master production-grade Docker deployments with monitoring, logging, health checks, and resource management.

Purpose

Configure containers for production with proper observability, resource limits, and deployment strategies.

Parameters

ParameterTypeRequiredDefaultDescription
monitoringenumNoprometheusprometheus/datadog
loggingenumNojson-filejson-file/loki/elk
replicasnumberNo1Number of replicas

Production Configuration

Health Checks

HEALTHCHECK --interval=30s --timeout=3s --retries=3 --start-period=60s \
  CMD curl -f http://localhost:3000/health || exit 1
# Compose health check
services:
  app:
    healthcheck:
      test: ["CMD", "curl", "-f", "http://localhost:3000/health"]
      interval: 30s
      timeout: 10s
      retries: 3
      start_period: 60s

Resource Limits

services:
  app:
    deploy:
      resources:
        limits:
          cpus: '1'
          memory: 1G
        reservations:
          cpus: '0.5'
          memory: 512M
      restart_policy:
        condition: on-failure
        delay: 5s
        max_attempts: 3

Logging Configuration

services:
  app:
    logging:
      driver: json-file
      options:
        max-size: "10m"
        max-file: "3"
        labels: "app,environment"

Monitoring Stack

Prometheus + Grafana

services:
  prometheus:
    image: prom/prometheus:latest
    volumes:
      - ./prometheus.yml:/etc/prometheus/prometheus.yml
    ports:
      - "9090:9090"

  grafana:
    image: grafana/grafana:latest
    ports:
      - "3001:3000"
    environment:
      GF_SECURITY_ADMIN_PASSWORD: ${GRAFANA_PASSWORD}

  cadvisor:
    image: gcr.io/cadvisor/cadvisor:latest
    volumes:
      - /:/rootfs:ro
      - /var/run:/var/run:ro
      - /sys:/sys:ro
      - /var/lib/docker/:/var/lib/docker:ro
    ports:
      - "8080:8080"

Prometheus Config

# prometheus.yml
global:
  scrape_interval: 15s

scrape_configs:
  - job_name: 'docker-containers'
    docker_sd_configs:
      - host: unix:///var/run/docker.sock

Deployment Strategies

Rolling Update (Zero Downtime)

deploy:
  update_config:
    parallelism: 1
    delay: 10s
    failure_action: rollback
    order: start-first
  rollback_config:
    parallelism: 1
    delay: 10s

Blue-Green

# Deploy new version
docker compose -p myapp-green up -d

# Switch traffic (update nginx/load balancer)
# Remove old version
docker compose -p myapp-blue down

Error Handling

Common Errors

ErrorCauseSolution
unhealthyHealth check failingCheck endpoint, increase start_period
OOMKilledMemory exceededIncrease limit or optimize
restart loopApp crashCheck logs, fix application

Recovery

1. Check logs: docker logs --tail 100 <container> 2. Verify health: docker inspect --format='{{.State.Health.Status}}' 3. Rollback if needed

Troubleshooting

Debug Checklist

  • [ ] Health check passing?
  • [ ] Resources sufficient? docker stats
  • [ ] Logs showing errors?
  • [ ] Metrics collecting?

Diagnostics

# Resource usage
docker stats --format "table {{.Name}}\t{{.CPUPerc}}\t{{.MemUsage}}"

# Restart count
docker inspect --format='{{.RestartCount}}' <container>

# Recent events
docker events --filter 'container=<name>' --since 1h

Usage

Skill("docker-production")

Related Skills

  • docker-debugging
  • docker-ci-cd
  • docker-security

Related skills

How it compares

Use as a structured checklist skill instead of asking the agent for generic “Docker best practices” in one-off prompts.

FAQ

Who is docker-production for?

Developers who deploy their own Docker images and want a repeatable production readiness review with their AI coding agent.

When should I use docker-production?

Use it in Ship before go-live to verify scans, secrets, and health checks; in Operate when setting monitoring, backups, and rollback plans for running containers.

Is docker-production safe to install?

Treat it as guidance and config templates—review the Security Audits panel on this Prism page and inspect any generated compose or secret-handling advice before applying to prod.

DevOps & CI/CDdeployinframonitoring

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