Migration from GCP to Azure with Zero Downtime in just 30 days

A US-based AI-powered content intelligence platform that enables businesses and marketers to plan, research, create, and optimize content with a strong focus on SEO performance. They serve over 200,000 marketers and businesses across 150+ countries

The Problem Statement

As the business scaled, the existing GCP infrastructure began to hinder growth—manual VM management caused environment drift and operational overhead, while escalating costs and complex data migration challenges added further strain. With over 3.5 TB of assets and critical service dependencies, the team needed a scalable, cost-effective, and resilient infrastructure to support innovation without disruption or vendor lock-in.

Project Overview

Project Kickoff

March 2025

Completion

April 2025 (30-day migration window)

Core Tech Stack

Node.js, MySQL, MongoDB, Redis

Migration Type

VM-based lift-and-optimize

Top 3 Achievements

Full Azure Migration of Kefi

Application now fully operational on Azure.

Seamless Shopify 3rd-party API integrations with HTTP/3 fallback handling.

Zero-Downtime Database Upgrade

Performed zero-downtime MySQL 5.7→8.0 in-place upgrade using gh-ost, ensuring uninterrupted production traffic.

Schema issues (e.g., reserved columns) resolved pre-migration.

MongoDB and Redis clusters successfully provisioned and validated on Azure.

Webtune Stability and Parity Achieved

Final schema updates and infrastructure provisioning completed.

Post-migration validation ensured state parity with GCP environments.

Challenges

Fragmented VM Deployments

Individually managed environments (Dev, QA, Prod) led to configuration drift, manual scaling, inefficient resource utilization, and high operational overhead during updates.

Costly Managed Services

Fully managed GCP and Azure services exceeded budget, demanding self-managed, cost-efficient alternatives.

Static Data Migration Hurdles

Static assets over 3.5TB in GCP buckets triggered sync issues and 404 errors during transfer attempts.

Inefficient Load Balancing

Dedicated load balancers for each app increased cost, complexity, and management overhead.

Application Schema Complexity

MySQL schema limitations (e.g., reserved keywords) affected upgrade paths and replication logic during the database transition.

Post Migration Compatability

Redis and MySQL behaved differently post-migration, demanding real-time performance tuning and stability checks.

Solutions

Optimized Azure VMs

Replaced GCP VMs with right-sized Azure instances and shared gateway for cost-efficient scaling.

Incremental Data Migration

Used Azure Data Factory with checksum validation to securely migrate 3.5TB of static assets.

Schema Refactoring Tooling

Applied gh-ost to refactor MySQL schemas and resolve reserved keyword conflicts pre-migration.

Performance Tuning Post-Move

Adjusted MySQL parameters and retained Redis as a managed service to ensure post-migration stability.

Cost-Controlled Architecture

Replaced managed services with self-managed components to maintain flexibility and reduce recurring expenses.

Outcomes

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The entire multi-environment migration was completed within 30 days with zero downtime and uninterrupted business operations throughout.

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3.5TB static data migrated successfully using incremental, validated transfer methods.

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Significant cost reduction via shared services and infra consolidation

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Node.js services are restructured for modularity, scalability, and cloud portability.

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No vendor lock-in, all services managed with full portability

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