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Migrate 40+ production VMs from Azure to GCP with minimal downtime

IndustryECommerce
StageSeries A Startup
Business Size50-200 Employees

A category leading startup providing product warranty backend for ecommerce brands

The Challenge

Vendor lock-in on Microsoft Azure, escalating enterprise compute costs, and a desire to leverage Google's superior data analytics tools.

The Result

Successfully migrated 40+ production Virtual Machines with minimal disruption, reducing monthly infrastructure spend by 35%.

The Challenge

A well-established ECommerce brand with years of operational history was hosted entirely on Microsoft Azure. As the company grew, the architecture—consisting of over 40 distinct Virtual Machines running Windows Server, Linux, and legacy SQL databases—became increasingly unwieldy.

Core Issues:

  • Cost Escalation: Long-term Azure commitments were expiring, and compute costs were skyrocketing beyond budget.
  • Analytics Bottleneck: The data team urgently wanted to utilize Google BigQuery and native GCP Machine Learning tools for customer analytics, but extracting terabytes of data daily from Azure was cost-prohibitive due to egress fees.
  • The Catch-22: The business operated 24/7. Any migration plan had to guarantee absolute minimal disruption to revenue-generating operations.

Our Approach

We orchestrated a "Lift, Shift, and Optimize" strategy, using specialized tooling to duplicate the environment across cloud borders.

1. Block-Level Data Replication

To ensure zero data loss and minimize the cutover window, we did not rely on standard backups. Instead, we implemented continuous block-level replication from the Azure VMs directly to GCP Compute Engine. This ensured the GCP environment was always within milliseconds of sync with the live Azure environment.

2. Infrastructure as Code Translation

We reverse-engineered their manually-created Azure networking infrastructure (vNets, Security Groups, ExpressRoutes) and comprehensively mapped them into declarative Terraform configurations for Google Cloud (VPCs, Firewall Rules, Cloud VPN).

3. The Cutover Strategy

We established a heavily rehearsed runbook for the final cutover window:

  1. Paced the site into brief "maintenance read-only" mode at 3:00 AM EST.
  2. Severed the replica links and promoted the GCP instances to Primary.
  3. Updated global Cloudflare DNS routing to point at the new GCP ingress load balancers.
  4. Performed automated health-checks and brought the site fully online.

The Result

The migration allowed the brand to unlock the modern data tools they needed while immediately improving their bottom line.

  • Near-Zero Disruption: The entire production cutover, including DNS propagation, was executed flawlessly in under 2 hours, well below the client's risk threshold.
  • Immediate ROI: By moving to GCP's custom machine sizing and sustained use discounts, total monthly infrastructure expenditure was immediately slashed by 35%.
  • Data Unlocked: The engineering team successfully integrated Google BigQuery within a week of migration, empowering the marketing team with advanced real-time customer analytics.
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