KreditBee: AI-First AWS-to-Google Cloud Migration in Just 3 Days
Project Overview
KreditBee partnered with Wohlig Transformations to validate a Google Cloud migration path for its AWS-native application stack — using an AI-assisted development workflow to compress the core migration into 2–3 days and dedicate the remaining engagement to end-to-end testing and standards definition.
KreditBee runs its core application stack on AWS — Lambda (Go), API Gateway, SNS/SQS, S3, and RDS MySQL. As part of its cloud strategy, KreditBee engaged Wohlig to evaluate Google Cloud Platform as a potential migration target. This Google Cloud DAF-funded proof-of-concept migrated the application development environment to GCP, validated the technical feasibility of the equivalent GCP stack, and established the standards that will drive the eventual production migration.
Using an AI-first approach, the engagement delivered 18 Cloud Run Functions, 11 Dockerfiles, 7 Apigee API proxies, and more than 50 Pub/Sub topics while documenting reusable patterns for future production rollout.
The Challenge
Multi-Service AWS Footprint
A core stack spanning Lambda, API Gateway, SNS/SQS, S3, RDS MySQL, Fargate crons, and Secrets Manager required credible Google Cloud equivalents rather than a simple lift-and-shift approach.
Compressed POC Window
The project had a 10-day implementation budget to validate migration feasibility without sacrificing quality, governance, or testing rigor.
Terraform Provider Switch
Existing AWS Terraform configurations needed to be translated to the Google Cloud provider across modules, resources, variables, and deployment workflows.
Delayed Messaging Semantics
AWS SQS delayed-message patterns do not map directly to Pub/Sub and required a different architectural approach to preserve business behavior.
Production-Path Standards
The proof of concept needed to establish reusable naming conventions, infrastructure standards, containerization patterns, and API governance models suitable for production scale.
Key Objectives
AI-First Migration: Accelerate conversion using AI-assisted development while maintaining human review and testing.
End-to-End Equivalence: Validate every AWS-to-GCP service mapping through integration testing.
Terraform-Managed Infrastructure: Deploy all resources as code with no manually configured infrastructure.
Delayed Messaging Support: Recreate SQS delayed-message behavior using native Google Cloud services.
Production Standards: Define scalable architecture, deployment, and governance patterns for future migrations.
The Solution: AI-Assisted AWS to GCP Migration
Service Mapping
AWS ServiceGoogle Cloud EquivalentAPI GatewayApigeeLambda (Go)Cloud Run FunctionsSNS / SQSPub/SubS3Cloud Storage (GCS)RDS MySQLSelf-managed MySQL on Compute EngineFargate (Cron Jobs)GKE Pilot / Cloud Run JobsCloudWatch / EventBridgeCloud SchedulerSecrets ManagerSecret ManagerDelayed SQS MessagesCloud Tasks
AI-Assisted Migration Workflow
The migration leveraged AI across three complementary approaches.
Inline IDE Assistance
Used for bulk Lambda-to-Cloud Run Function conversion, replacing AWS SDK integrations with Google Cloud client libraries and generating boilerplate code.
Agentic Migration
Handled Terraform provider translation, complex stateful functions, and messaging pattern conversions from SNS/SQS to Pub/Sub.
Model-Level Pattern Review
Provided reusable migration templates, architecture consistency checks, and QA reviews for AI-generated outputs.
Every workload followed a structured process:
Analyse → Generate → Human Review → Test → Commit
No function was deployed without human validation.
Landing Zone
A production-aligned Google Cloud foundation was established consisting of:
1 Organization
1 Folder
3 Projects (Network Host, Application, Shared Services)
Shared VPC
IAM controls
Organization Policies
Billing integration
Application Architecture
Apigee serves as the API gateway layer in front of Cloud Run Functions developed in Go.
Pub/Sub and Cloud Tasks manage asynchronous messaging workloads.
Cloud Storage handles object storage requirements.
MySQL runs on Compute Engine behind a bastion host.
Cloud Scheduler orchestrates cron-based processes, while Secret Manager stores application credentials.
CI/CD
Existing GitHub Actions pipelines were migrated to Google Cloud using Workload Identity Federation (WIF) for keyless authentication and Terraform-managed deployments.
Technology Stack
Cloud Run Functions, Apigee, Pub/Sub, Cloud Tasks, Cloud Storage, Cloud Scheduler, Secret Manager, Compute Engine, MySQL, Workload Identity Federation (WIF), Terraform, and GitHub Actions.
Key Benefits & Results
Faster Function Migration
Previous: Multi-week Lambda-by-Lambda migration.
Solution: AI-assisted conversion pipeline with engineering oversight.
Result: 18 Lambda functions migrated to Cloud Run Functions in 2–3 days.
Infrastructure-as-Code Modernization
Previous: AWS-specific Terraform dependencies.
Solution: AI-assisted Terraform provider conversion.
Result: Complete GCP Terraform module suite covering networking, databases, identity, storage, scheduling, messaging, and API management.
API Modernization
Previous: AWS-native API routing.
Solution: Apigee implementation.
Result: 7 API proxies supporting custom domains, CORS policies, and load balancing.
Messaging Modernization
Previous: SNS/SQS architecture.
Solution: Pub/Sub combined with Cloud Tasks.
Result: More than 50 Pub/Sub topics with preserved delayed-message functionality.
Repeatable Deployments
Previous: Console-configured infrastructure.
Solution: Fully Terraform-managed resources.
Result: Version-controlled, repeatable, and code-reviewed deployments.
Production Readiness
Previous: Temporary proof-of-concept implementations.
Solution: Standards-first architecture and documentation.
Result: Production-ready Terraform modules, naming standards, containerization patterns, and Apigee governance guidelines.
Technical Innovation
AI-First Migration Framework
A combination of IDE assistance, agentic workflows, and model-driven review accelerated migration timelines while maintaining engineering quality controls.
Cloud Tasks for Delayed Messaging
Because SQS delayed messages do not directly map to Pub/Sub, Cloud Tasks was introduced alongside Pub/Sub to preserve delayed-delivery behavior without changing business logic.
Workload Identity Federation Everywhere
GitHub Actions and inter-service communication relied on keyless authentication using Workload Identity Federation, eliminating long-lived service account keys.
Inverted Timeline Allocation
Traditional migrations often spend weeks on code conversion and days on validation.
This project completed conversion in 2–3 days and dedicated the majority of the engagement to integration testing and quality assurance.
Production-Scale Standards
All validated patterns—including Terraform modules, naming conventions, containerization approaches, and Apigee configurations—were designed for future production adoption rather than temporary proof-of-concept use.
Wohlig’s Approach
Catalogued and classified every Lambda function, trigger, environment variable, and AWS dependency.
Established the Google Cloud landing zone, Shared VPC, IAM model, organizational hierarchy, and billing foundation.
Used AI-assisted development to migrate 18 critical Lambda functions and convert Terraform configurations to Google Cloud equivalents.
Implemented supporting services including Pub/Sub, Cloud Tasks, Apigee, GitHub Actions migration, and Workload Identity Federation.
Performed end-to-end validation covering onboarding flows, messaging systems, database connectivity, scheduled jobs, and API routing.
Delivered migration runbooks, production recommendations, and knowledge-transfer sessions to the KreditBee engineering team.
About KreditBee
KreditBee, operated by Krazybee Services Limited, is a Bengaluru-based fintech company providing digital lending solutions for salaried and self-employed professionals across India. Founded in 2016, the company is an RBI-registered systemically important Non-Banking Financial Company (NBFC).
About Wohlig Transformations Pvt. Ltd.
Founded in 2015, Wohlig Transformations specializes in GenAI and DevOps, with more than 160 professionals across India and the United Kingdom.