How We Reduced Costs by 30% using Google Cloud (GCP) Multi-Cloud Strategy
Published on January 29, 2026
Most companies treat AWS as the default. They get comfortable, they stop optimizing, and their bill creeps up to $43,500/month. That was us. We were paying a "loyalty tax" for sticking to one cloud.
We stopped being loyal to a logo and started being loyal to our P&L. We moved compute to GCP, kept databases on AWS, and aggressively optimized both.
The Headline Number
$19,680 monthly savings. That's $236,000 per year added directly to our bottom line. We didn't fire anyone. We didn't degrade performance. We just stopped paying for waste.
Here is the 3-phase execution plan.
The Multi-Cloud Premise (Don't Put All Eggs in One Basket)
AWS, GCP, and Azure are not the same. They have different "loss leaders" and pricing sweet spots. If you put everything on one, you overpay for half your stack.
GCP Excels At:
Compute (Cheaper instances & sustained use discounts), BigQuery Analytics, and Kubernetes (GKE is years ahead).
AWS Excels At:
Managed Databases (RDS is rock solid), Enterprise Integrations, and Compliance ecosystems.
Phase 1: Quick Wins (The "Stupid" Waste)
Storage Lifecycle Policies
Problem: We stored 500GB of log data in S3 Standard tier. 350GB wasn't touched in a year.
The Fix
Auto-move data to Archive tier after 30 days.
Savings: 55% on Storage
Phase 2: Rightsizing (Stop Over-Provisioning)
Database Reality Check
Problem: We ran an RDS `db.r5.2xlarge` ($8k/month) because we were scared of downtime. Actual CPU usage? 12%.
The Fix
Downsized to `db.t4g.large` + Reserved Instance.
Savings: $7,200/month (90% reduction)
Phase 3: The Architecture Shift (GCP Migration)
This was the heavy lifting. We moved our compute workloads to Google Kubernetes Engine (GKE) while keeping the database on AWS.
Cost Impact: Before vs After
Compute (EC2)
Before: $22,000
After: $10,000
-55% via GCP CUDs
Dev/Staging
Before: $8,000
After: $2,000
-75% via Spot VMs
Total Bill
Before: $43.5k
After: $23.8k
$236k/Year Saved
Strategy #4: Spot VMs for Non-Production
Don't Pay Full Price for Testing
Problem: Dev servers ran 24/7 at full on-demand price.
Solution: We switched to GCP Spot VMs (91% cheaper) for all non-prod environments and auto-shutdown at 7 PM.
Result
Cost dropped from $800 to $120/month per server.
Frequently Asked Questions
Is multi-cloud more complex to operate?
Yes, but the 30% savings pay for the complexity. Modern tools like Terraform and Kubernetes abstract the differences. If you save $150k/year, the 200 hours of engineering time pays back in 4 months.
Can we move back to AWS if we outgrow GCP?
Services using portable APIs (SQL, Kubernetes) move easily. AWS-native services (DynamoDB) are harder. We use portable services where possible to maintain leverage.
Is migrating to multi-cloud worth the effort?
Only if you spend over $100k/year. Below that, the engineering effort outweighs the savings. At $500k/year spend, the ROI is under 6 months.
Stop The "Loyalty Tax"
You don't need to rebuild your entire stack to save money. We can show you which 20% of your workloads are costing you 80% of your budget—and move them to the right cloud.
Get A Cloud Cost Audit