umac-ai-deploy-prod

What problem does it solve?

This Skill eliminates the risk of inconsistent, error-prone manual deployments for the UMAC AI project by providing a standardized, end-to-end production deployment standard operating procedure (SOP) that covers all core services and infrastructure components.

Core Features & Use Cases

• Full-Stack Deployment Workflow: Provides step-by-step instructions for deploying the UMAC AI backend (ECS + Prisma), frontend (S3 + CloudFront), and AWS CDK infrastructure, including code commit, Docker image build/push, ECS service updates, and frontend asset synchronization.
• Infrastructure Drift Detection: Includes a 6-probe quick check recipe to identify if the project has migrated off AWS, preventing wasted effort on outdated infrastructure configurations.
• Production Troubleshooting Guide: Documents pre-identified fixes for common production issues including ECS task crashes, CloudFront 502 errors, SES email delivery failures, and admin login failures.
• Use Case: A developer deploying a UMAC AI feature update can use this Skill to follow the correct deployment order, avoid common pitfalls like forgetting to force a new ECS deployment or invalidate the CloudFront cache, and verify the deployment succeeded with predefined health check commands.

Quick Start

Use the umac-ai-deploy-prod skill to execute the full production deployment process for the UMAC AI project, following the provided SOP to push code, update services, and verify functionality.