/deploy

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🚨 EXECUTION NOTICE FOR CLAUDE

When you invoke this command via SlashCommand, the system returns THESE INSTRUCTIONS below.

YOU are the executor. This is NOT an autonomous subprocess.

• ✅ The phases below are YOUR execution checklist
• ✅ YOU must run each phase immediately using tools (Bash, Read, Write, Edit, TodoWrite)
• ✅ Complete ALL phases before considering this command done
• ❌ DON't wait for "the command to complete" - YOU complete it by executing the phases
• ❌ DON't treat this as status output - it IS your instruction set

Immediately after SlashCommand returns, start executing Phase 0, then Phase 1, etc.

See @CLAUDE.md section "SlashCommand Execution - YOU Are The Executor" for detailed explanation.

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Arguments: $ARGUMENTS

Goal: Generate production-ready deployment configurations for Celery workers, beat scheduler, and flower monitoring

Core Principles:

• Ask clarifying questions about deployment platform and requirements
• Detect existing Celery configuration before generating deployment files
• Use environment variables with placeholders (never hardcode secrets)
• Follow platform-specific best practices for scaling and reliability

Phase 1: Discovery Goal: Understand deployment requirements and existing setup

Actions:

• Parse $ARGUMENTS for target platform (systemd/docker/kubernetes)
• If platform unclear, use AskUserQuestion to gather:
  • Which deployment platform? (systemd, Docker Compose, Kubernetes)
  • How many worker processes needed?
  • Will you deploy beat scheduler and flower monitoring?
  • What are your scaling requirements?
• Detect project structure and package manager
• Example: !{bash ls requirements.txt pyproject.toml setup.py docker-compose.yml Dockerfile 2>/dev/null}
• Locate existing Celery configuration
• Example: !{bash find . -name "celery.py" -o -name "celery_app.py" 2>/dev/null | grep -v pycache | head -5}

Phase 2: Analysis Goal: Understand current Celery setup

Actions:

• Read Celery configuration file for broker and backend settings
• Check for existing deployment configurations
• Identify task modules and queue configuration
• Verify broker type (Redis/RabbitMQ/SQS)
• Load application entry point

Phase 3: Planning Goal: Design deployment architecture

Actions:

• Outline deployment architecture based on platform:
  • systemd: Service units for worker, beat, flower
  • Docker: Multi-container compose with health checks
  • Kubernetes: Deployments, ConfigMaps, Secrets, HPA
• Plan scaling strategy (manual vs autoscaling)
• Design health check approach
• Determine resource limits
• Present deployment plan to user

Phase 4: Implementation Goal: Generate deployment configurations

Actions:

Task(description="Generate deployment configs", subagent_type="celery:deployment-architect", prompt="You are the deployment-architect agent. Generate production deployment configurations for this Celery application.

Platform: $ARGUMENTS Detected configuration: [broker type, task modules, queues]

Requirements:

• Create platform-specific deployment files (systemd/Docker/K8s)
• Configure celery worker with appropriate concurrency
• Set up beat scheduler as singleton service
• Include flower monitoring dashboard
• Use environment variables with placeholders only
• Add graceful shutdown handling (SIGTERM)
• Configure health checks for all services
• Set reasonable resource limits
• Include security best practices

Deliverables:

• Complete deployment configuration files
• .env.example with placeholder values only
• Deployment documentation with setup steps
• Scaling and troubleshooting guide")

Phase 5: Verification Goal: Validate generated configurations

Actions:

• Verify all configuration files were created
• Check for hardcoded secrets (should be none)
• Confirm .env.example uses placeholders only
• Validate syntax based on platform:
  • Docker: !{bash docker-compose config 2>&1 || echo "Validation pending"}
  • Kubernetes: !{bash kubectl apply --dry-run=client -f . 2>&1 || echo "Validation pending"}
• Ensure documentation is complete

Phase 6: Summary Goal: Document deployment setup

Actions:

• List all generated configuration files
• Highlight key configuration parameters
• Explain deployment workflow
• Provide platform-specific commands:
  • systemd: sudo systemctl start celery-worker@1
  • Docker: docker-compose up -d
  • Kubernetes: kubectl apply -f .
• Show monitoring access (Flower URL)
• Note scaling procedures
• List next steps for production readiness