AWS to GCP migration is driven by BigQuery analytics, Vertex AI capabilities and Google Workspace integration. This guide covers the full assessment, service mapping and cost analysis.
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Google BigQuery for analytics (simpler and cheaper than Redshift at scale), Vertex AI and Google DeepMind for AI/ML workloads, Google Workspace deep integration, GCP global network performance, Committed Use Discounts (CUD) competitive with AWS RIs.
EC2→Compute Engine (n2/c2/m2), S3→Cloud Storage (Standard/Nearline/Coldline), RDS→Cloud SQL, DynamoDB→Firestore or Bigtable, Lambda→Cloud Functions or Cloud Run, EKS→GKE, CloudWatch→Cloud Monitoring, IAM→Cloud IAM, VPC→GCP VPC (global, unlike AWS regional), Route53→Cloud DNS.
Sustained Use Discounts (SUD): automatic up to 30% — no reservation needed. Custom machine types: specify exact vCPU and memory. Per-second billing for Linux. Free inter-zone transfer within same region (AWS charges cross-AZ). BigQuery on-demand at $5/TB often cheaper than AWS Athena.
Google Storage Transfer Service (free, pulls from S3 to Cloud Storage), direct internet transfer (AWS egress $0.09/GB, GCP ingress free), Google Transfer Appliance for datasets over 10PB. For most migrations under 100TB, direct internet transfer is fastest.
Set up: GCP resource hierarchy (Org→Folders→Projects), Cloud Identity with AD federation, Shared VPC with Cloud NAT and Cloud Armor, Security Command Center Premium, VPN or Interconnect to on-prem or remaining AWS workloads. TCOIQ covers GCP Cloud Foundation requirements.
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