Google Cloud Platform offers unique pricing advantages for on-premises migration — especially for analytics, AI and compute-intensive workloads. This guide covers the full on-prem to GCP TCO analysis.
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GCP automatically applies Sustained Use Discounts (SUD) for instances running more than 25% of the month — no reservation required. SUD can save up to 30% vs on-demand. Combined with 3-year Committed Use Discounts (CUD at 38% saving), GCP total compute savings rival AWS and Azure RI programmes.
n2-standard-4 (4 vCPU, 16GB): $0.1902/hr on-demand. With SUD (30-day running): $0.1332/hr. With 3yr CUD: $0.1188/hr (37.5% saving). Custom machine types let you specify exact vCPU/RAM — no paying for pre-defined sizes. Significant advantage for odd-sized workloads.
If your on-premises environment includes analytics databases or data warehouses, GCP BigQuery dramatically changes the economics. BigQuery on-demand: $5/TB scanned. BigQuery flat-rate (100-slot package): $2,000/month for unlimited queries. For organisations running Teradata, Exadata or SQL Server for analytics, BigQuery typically reduces analytics spend by 60-80%.
Hardware amortisation ($500-$2,000/server every 3-5 years), DC rent/power/cooling, hardware maintenance contracts, on-premises analytics infrastructure (Hadoop clusters, legacy data warehouses), and database licences if moving to Cloud SQL or BigQuery managed services.
GCP wins: analytics-heavy environments (BigQuery), AI/ML workloads (Vertex AI), Google Workspace-integrated organisations, Kubernetes-native environments (GKE is arguably the best managed Kubernetes). AWS wins: broadest service portfolio, most talent. Azure wins: Windows Server, SQL Server, Microsoft ecosystem.
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