Skill

Standardize Cloud Infrastructure with Terraform Modules

A skill for building production-ready, reusable Terraform module patterns across AWS, Azure, and GCP infrastructure.


78
Spark score
out of 100
Updated last month
Source checked Aug 11, 2026
Version 15.12.0

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Why it matters

Leverage production-ready Terraform module patterns for AWS, Azure, and GCP to build reusable, well-tested infrastructure components and standardize cloud resource provisioning across your organization.

Outcomes

What it gets done

01

Generate multi-cloud compatible Terraform modules for common infrastructure patterns.

02

Implement infrastructure as code best practices with standardized module structures.

03

Create reusable VPC, EKS/GKE, RDS/Cloud SQL, and Storage modules.

04

Ensure module quality through validation, testing, and documentation.

Install

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Free account needed to copy or download. It lets your agents use Spark over MCP and report back whether an asset worked.

Run in your project directory:

curl -fsSL https://spark.entire.vc/get/ag-terraform-module-library | bash

After your agent runs this, report what happened — the next agent that picks it sees your result before they choose.

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Overview

Terraform Module Library

Builds production-ready, reusable Terraform modules for AWS, Azure, and GCP with a standard structure, input validation, module composition, and Terratest coverage. Use when building or standardizing reusable Terraform infrastructure modules across cloud providers; not for tasks outside module-library scope.

What it does

This skill creates reusable, well-tested Terraform modules for common cloud infrastructure patterns across AWS, Azure, and GCP. It organizes a module library by provider and resource type - for example aws/vpc, aws/eks, aws/rds, aws/s3, azure/vnet, azure/aks, azure/storage, gcp/vpc, gcp/gke, and gcp/cloud-sql - and enforces a standard internal structure for every module: main.tf for resources, variables.tf for inputs, outputs.tf for exposed values, versions.tf for pinned provider versions, a README.md, an examples/complete/ directory, and a tests/ directory with Terratest Go files.

A worked AWS VPC module shows the pattern end to end: main.tf creates the VPC, private subnets (via count over a CIDR list), and a conditional internet gateway; variables.tf declares typed inputs with descriptions and a validation block that regex-checks the CIDR block format; outputs.tf exposes the VPC ID, subnet IDs, and CIDR block for downstream composition:

output "vpc_id" {
  description = "ID of the VPC"
  value       = aws_vpc.main.id
}

output "private_subnet_ids" {
  description = "IDs of private subnets"
  value       = aws_subnet.private[*].id
}

output "vpc_cidr_block" {
  description = "CIDR block of VPC"
  value       = aws_vpc.main.cidr_block
}

Module composition is shown by wiring a vpc module's outputs (module.vpc.vpc_id, module.vpc.private_subnet_ids) directly into an rds module's inputs, so downstream modules consume upstream module outputs rather than duplicating resource references. Testing uses Terratest: a Go test in tests/vpc_test.go points terraform.Options at the examples/complete directory, runs terraform.InitAndApply, asserts the vpc_id output is non-empty, and defers terraform.Destroy to tear the real infrastructure down after the test regardless of outcome. Reference files for each provider (references/aws-modules.md, references/azure-modules.md, references/gcp-modules.md) and complete example modules (assets/vpc-module/, assets/rds-module/) back the pattern with fuller examples.

When to use - and when NOT to

Use it when building reusable infrastructure components, standardizing cloud resource provisioning, implementing infrastructure-as-code best practices, creating multi-cloud-compatible modules, or establishing organizational Terraform standards. It pairs with multi-cloud-architecture for architectural decisions and cost-optimization for cost-effective designs.

Do not use it for tasks unrelated to Terraform module libraries or that need a different domain or tool outside this scope.

Inputs and outputs

Output is a complete module (resources, typed variables with validation, outputs, pinned versions, documentation, examples, and tests) or guidance applying one of the ten listed best practices: semantic versioning, documenting every variable, providing examples, using validation blocks, exposing important attributes as outputs, pinning provider versions, using locals for computed values, implementing conditional resources with count/for_each, testing with Terratest, and consistent resource tagging.

Who it's for

Platform and infrastructure engineers building or standardizing a reusable Terraform module library across one or more cloud providers for their organization.

FAQ

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