Migration to GCP Reimagined with Gemini CLI

For years, “cloud migration” meant long timelines, manual refactoring, and complex DevOps workflows. But the game has changed.
Google Cloud’s Gemini CLI is revolutionizing how teams modernize infrastructure, combining AI-driven automation with developer-friendly workflows that turn multi-week migration projects into same-day transformations.

 Why Gemini CLI Is a Cloud Migration Game-Changer

Modern cloud initiatives aren’t just about “lifting and shifting.” True modernization requires:

 ✅ Refactoring legacy code
✅ Converting old configurations to cloud-native equivalents
✅ Updating CI/CD pipelines
✅ Optimizing application logic for scalability, availability & performance

The Gemini CLI steps in as your AI engineering ally, streamlining all these tasks:

1. Refactor legacy applications to cloud-ready architectures

2. Translate Terraform / scripts to GCP-friendly IaC patterns

3. Suggest Cloud Run, GKE, and Cloud Functions deployment patterns

4. Auto-generate configuration files and GCP service bindings

5. Provide intelligent code fixes & modernization snippets

Getting Started with Gemini CLI

1. Install Node.js – Download from the official website (prerequisite).

2. Install the CLI – Run: npm install -g @google/gemini-cli

3. Authenticate Securely

On its first run, the CLI prompts for authentication. The secure "Login with Google" option links the tool to your account in seconds.

 AI-Assisted Migration Workflow

Here’s how teams are using Gemini CLI to accelerate their GCP transition:

Step	Task	Gemini CLI Advantage
1️⃣	Analyze legacy repo & workloads	AI reviews architecture and proposes migration strategy
2️⃣	Refactor code bases	Auto-suggests modern cloud-native patterns
3️⃣	Convert IaC to GCP	Translates Terraform, Docker, YAML to GCP-optimized equivalents
4️⃣	Generate deployment configs	Creates gcloud, Cloud Run, GKE, Artifact Registry configs
5️⃣	Validate and optimize	Recommends cost-efficient and scalable resource settings

How to Refactor an AWS Serverless App to GCP in 15 Minutes with the Gemini CLI

Traditional refactors are tedious — especially when porting event-driven AWS architectures to GCP.

Here’s how Gemini CLI automated that entire process.

Phase 1: The "Before" State: Our AWS Application

We began with a typical AWS setup:

• An S3-to-Lambda function that triggers on object uploads.

• Infrastructure defined in Terraform (with main.tf, variables.tf, and backend configuration).

https://github.com/Cloud-Evonence/AWS-infra-IAC.git

Phase 2: Validate AWS Code & Initial Review

With the "before" state defined, I validated the code.

1. Validate the AWS Terraform Code (terraform init & terraform plan/validate)

2. Get an Initial Baseline Review

Prompt for AI Review:

Phase 3: The Refactoring Demo(The "Magic")

1. Initialize Gemini CLI in the Copied Directory

2. Start Chatting: The Refactoring Prompt

This is the most important step. I gave Gemini a single, complex prompt, using the @ syntax to pass my local files directly into its context.

3. Get Updated Terraform and Function Code via Gemini CLI

Gemini processed the request and provided the fully refactored GCP code for both Terraform and Python.

With the Gemini CLI, we simply ask it to apply its own changes instead of tedious copy-pasting. In seconds, our project is fully refactored and ready for review and deployment, all within the terminal.

Phase 4: Final Review and GCP Deployment

Next, Gemini performed an AI-based code review, suggesting production-grade improvements like IAM best practices and safer resource configurations.

Gemini provided a critical review, validating the code's correctness and suggesting production improvements (like removing force_destroy = true)

2. Apply the Refactored Terraform Code

Confident in the code, we exited the CLI (/quit) and set our project. We ran terraform init. This time, it correctly downloaded the Google Cloud provider. With the provider initialized, we create our deployment plan.

Next, terraform plan. The output was the "proof" that the refactor worked: it listed only GCP resources to be created.

Phase 5: The Grand Finale — Success!

After delegating the IAM permissions, We re-ran terraform plan and terraform apply. 

In about 15 minutes, I had analyzed, refactored, applied, reviewed, and deployed a full function migration from AWS-to-GCP.

️Key Benefits You’ll See After Implementing Gemini CLI

Benefit	Description
Faster migration timelines	Complex refactors happen in minutes
Smooth CI/CD and IaC modernization	Standardized, error-free configs
Reduced operational overhead	Less manual engineering effort
Cloud-optimized architecture	Better performance & scalability
Cost-aware suggestions	AI recommends right-sized services