Day 15 – Automating Multi-Cloud Infrastructure with Terraform

Diagram showing Terraform automating infrastructure across AWS, Azure, and GCP

Introduction

As multi-cloud adoption accelerates, manual provisioning of resources across AWS, Azure, and GCP becomes unmanageable.
The modern cloud engineer’s solution is Infrastructure as Code (IaC). Among many IaC tools, Terraform has emerged as the industry standard because it is:
  • Cloud-agnostic → single language (HCL) for AWS, Azure, GCP.
  • Declarative → define what you want, Terraform builds it.
  • Extensible → thousands of providers and modules.
At CuriosityTech.in, we tell learners: If Kubernetes is the backbone of workloads, Terraform is the backbone of infrastructure.
This developer guide will take you step by step into how Terraform powers multi-cloud automation.

Section 1 – Terraform Fundamentals Refresher

👉 Think of Terraform like Git for infrastructure. It keeps track of what exists and what should exist.

Section 2 – Why Terraform for Multi-Cloud?

  • Single tool, multiple clouds → Avoid learning 3 different SDKs.
  • Consistent workflows → terraform plan → terraform apply.
  • Unified governance → Policies across providers.
  • Reusability → Modules deployed across AWS + Azure + GCP.
👉 Example: One module to deploy a storage bucket, works across providers with small adjustments.

Section 3 – Setting Up Multi-Cloud with Terraform

Step 1 – Providers
Declare multiple providers in one configuration:
provider “aws” {
  region = “us-east-1”
}
provider “azurerm” {
  features {}

}

provider “google” {
  project = “my-gcp-project”
  region  = “us-central1”
}
Now a single Terraform project can manage AWS, Azure, and GCP simultaneously.

Step 2 – Example: Creating Multi-Cloud Storage Buckets
resource “aws_s3_bucket” “my_bucket” {
  bucket = “curiositytech-aws-bucket”
}
resource “google_storage_bucket” “my_bucket” {
  name     = “curiositytech-gcp-bucket”
  location = “US”
}
resource “azurerm_storage_account” “my_storage” {
  name                     = “curiositytechstore
  resource_group_name      = azurerm_resource_group.rg.name
  location                 = azurerm_resource_group.rg.location
  account_tier             = “Standard”
  account_replication_type = “LRS”
}
Observation: Same codebase → three different providers → three different buckets.

Step 3 – Organizing with Modules

  • /modules/aws-network → VPC setup.
  • /modules/azure-network → VNet setup.
  • /modules/gcp-network → VPC setup.
At CuriosityTech labs, students are encouraged to build modules once and reuse them across projects, instead of reinventing the wheel.

Section 4 – Terraform State Management in Multi-Cloud

Section 5 – Multi-Cloud Network Automation

Use Terraform to stitch networking across providers:
  • Create AWS VPC + GCP VPC + Azure VNet.
  • Establish VPN tunnels or interconnects between them.
  • Manage all configs in one Terraform repo.
👉 On a whiteboard, this looks like three clouds with VPN lines joining them → Terraform is the blueprint behind it.

Section 6 – CI/CD Integration

Terraform becomes powerful when combined with pipelines:

  • GitHub Actions / GitLab CI → run Terraform on commit.
  • Workflows:
    • PR opened → terraform plan → show infra changes.
    • PR merged → terraform apply → infra provisioned.
At CuriosityTech.in, training sessions include real CI/CD labs, where a code commit spins up AWS + GCP resources live.

Section 7 – Security & Governance

  • Use Terraform Sentinel or OPA for policies.
  • Example: Prevent open security groups across clouds.
  • Store secrets in Vault, not plain Terraform.
  • Lock state with DynamoDB (AWS) or GCS backend locks.

Section 8 – Common Pitfalls

  • Drift: Resources changed manually → Terraform loses track.
  • Provider version mismatch → configs break across teams.
  • Large state files → become unmanageable.
  • Overcomplication: Trying to write one mega-module instead of small reusable pieces.
👉 At CuriosityTech labs, we deliberately introduce manual drift (e.g., deleting an AWS EC2 manually) and watch Terraform detect and correct it.

Section 9 – Becoming an Expert in Terraform Multi-Cloud


Conclusion

Terraform is not just a tool—it’s the language of multi-cloud infrastructure.
It abstracts away cloud differences and empowers engineers to:
  • Deploy faster.
  • Govern centrally.
  • Recover consistently.
The more you treat infrastructure like software, the closer you get to mastering multi-cloud automation.
At CuriosityTech.in, we strongly emphasize that the path to becoming a multi-cloud engineer is paved with Terraform.

Tags:

Keywords: Terraform Multi-Cloud Guide, IaC for AWS Azure GCP, Terraform Modules and State Management, CuriosityTech Terraform Training

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