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Infrastructure as code architect

Skill teckedd-code2save/ai-build-tools/cli/skills/infrastructure-as-code-architect

From product spec to live URL — scaffold a backend with Forge, ship to your VPS with ship-to-vps

Install

npx -y skills add teckedd-code2save/ai-build-tools --skill infrastructure-as-code-architect

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What its author says it does

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Translates local database and cache requirements (e.g. docker-compose setup with Postgres, Redis, Elasticsearch) into production-ready Infrastructure as Code using Terraform, Pulumi, or Bicep for AWS, Azure, or GCP. Use when a user wants to deploy their application or data platform to the cloud.

SKILL.md

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Infrastructure as Code Architect

Translate local development setups (like a loaded docker-compose.yml) into enterprise-ready, production infrastructure deployments using Terraform, Pulumi, or Bicep.

🎯 When to Use

After a data platform is generated using the forge skill.
When the user asks "How do I deploy this?" or "Can you write the Terraform for this?"
When migrating from a local Docker environment to managed cloud services (e.g., AWS RDS, Azure Cache for Redis).
When standing up fresh environments (staging, production).

🛠️ Step-by-Step Workflow

1. Identify Existing Requirements

Scan the current project for docker-compose.yml, .env.example, and package files.
Identify the core components:
- Database (PostgreSQL, MySQL, etc.)
- Cache/Message Queue (Redis, RabbitMQ)
- Search/Analytics (Elasticsearch, OpenSearch)
- Application Runtimes (Node.js, Python FastAPI, .NET)

2. Determine the Target Cloud and Tool

Ask the user if they have a preference for:

Cloud Provider: AWS, Azure, or GCP?
Tool: Terraform, Pulumi, or Bicep (Azure only)?

If they don't have a preference, default to Terraform on AWS.

3. Generate Infrastructure Code

Create the necessary IaC files (Terraform, Pulumi, or Bicep).

Container Mandate:

Docker: Always generate a production-ready Dockerfile for each application component. Implement multi-stage builds for smaller images and security scan points.
Kubernetes (K8s): For production-grade platforms, map local docker-compose services to K8s Manifests or Helm Charts.

Local Component	Managed K8s Equivalent	AWS RDS/ElastiCache Equivalent
PostgreSQL	EKS / AKS / GKE (via StatefulSet)	Amazon RDS
Redis	EKS / AKS / GKE	Amazon ElastiCache
App Container	K8s Deployment + Service	App Runner / Container Apps

4. Implement CI/CD (GitHub Actions Mandate)

MANDATORY: Provide a complete .github/workflows/deploy.yml file that:

Builds and Pushes Docker Images: Uses docker/build-push-action to push to ECR, ACR, or GCR.
Scans for Vulnerabilities: Integrates Snyk or Trivy scans within the pipeline.
Applies Infrastructure: Automatically runs IaC plan/apply from the pipeline.
Deploys to K8s: Updates K8s deployments with the new image tag.

5. Infrastructure Best Practices

Security: Private subnets only. No public IPs for DBs/Caches. Use Managed Identities/IAM Roles.
State Management: Use remote backends (S3/Blob/GCS) with locking.
Observability: Include basic monitoring/logging resources (CloudWatch, Azure Monitor).

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