Enterprise Migration to Google Cloud Platform
Wolk Inc designs and executes enterprise GCP migrations: Landing Zone build, GKE workload modernisation, BigQuery analytics migration, Vertex AI infrastructure, and FinOps governance. Senior-engineer-led with documented wave-by-wave delivery.
GKE
Best-in-Class Kubernetes
BigQuery
Serverless Analytics Warehouse
Vertex AI
ML Platform Migration
30–50%
Typical Post-Migration Savings
GCP Migration Deliverables
Google Cloud Foundation & Landing Zone
Resource hierarchy design (Organisations, Folders, Projects), VPC network topology, Shared VPC configuration, organisation policy constraints, IAM binding framework, and Cloud Armor / Security Command Center baseline. Built using Google Cloud Foundation Toolkit or custom Terraform following Google's Enterprise Foundation blueprint.
GKE Cluster Design & Workload Migration
Production GKE Autopilot or Standard cluster design with Workload Identity, Binary Authorization, and Config Connector. Workload migration from self-managed Kubernetes, EKS, or AKS to GKE — including Helm chart adaptation, ingress configuration with GKE Gateway API, and Cloud DNS integration.
BigQuery & Data Warehouse Migration
Migration of analytics workloads to BigQuery: schema design for BigQuery's columnar model, pipeline re-engineering from Redshift or on-premises Hadoop/SQL Server, dbt model migration, and Looker or Looker Studio dashboard validation. Includes BigQuery slot reservation planning and cost governance via information schema monitoring.
AI/ML Infrastructure & Vertex AI
Vertex AI pipeline configuration for teams migrating ML training and serving workloads to GCP. Includes Vertex AI Feature Store setup, custom training job migration from SageMaker or self-hosted, model serving via Vertex AI Prediction endpoints, and integration with existing MLOps tooling (Kubeflow, MLflow, or Argo Workflows).
How a GCP Migration Engagement Works
GCP Readiness Assessment
Workload inventory, dependency mapping, GCP Migrate assessment for VM workloads, and BigQuery/GKE compatibility analysis. Output: prioritised migration wave plan with GCP service mapping for each workload.
Foundation Build
Google Cloud Landing Zone provisioned via Terraform. Resource hierarchy, networking, IAM, Security Command Center, and Cloud Logging/Monitoring baseline configured before workload migration begins.
Migration Waves
Non-production environments migrated and validated first. Production workloads migrated in sequenced waves with defined rollback procedures and parallel-run validation periods before final DNS and traffic cutover.
Optimisation & Handoff
Committed Use Discount and Sustained Use Discount analysis, resource label taxonomy, Cloud Billing budget alerts, team training sessions, and full runbook documentation handoff.
Senior GCP Engineers. Foundation-First Delivery.
GCP Migration Questions
What types of workloads is GCP best suited for?▾
GCP is particularly strong for data-intensive workloads (BigQuery, Dataflow, Pub/Sub), AI/ML infrastructure (Vertex AI, TPUs), Kubernetes (GKE has the deepest feature set of any managed Kubernetes service), and multi-cloud architectures that include Google Workspace integration. Teams with significant analytics or ML spend often see the most compelling GCP economics compared with AWS or Azure.
Does Wolk Inc use the Google Cloud Foundation Toolkit or custom Terraform?▾
Wolk Inc uses the Google Cloud Foundation Toolkit (fabric FAST or Enterprise Foundation blueprint) as the starting architecture for most GCP Landing Zone engagements. For teams with existing Terraform modules or specific compliance requirements, we adapt the foundation using custom Terraform with the Google provider. All infrastructure is version-controlled, documented, and handed off with runbooks.
Can Wolk Inc migrate a Redshift data warehouse to BigQuery?▾
Yes. Wolk Inc handles Redshift-to-BigQuery migrations including schema conversion (using BigQuery Migration Service as a starting point), SQL dialect adaptation for stored procedures and views, dbt model migration, historical data load, and pipeline re-engineering. BigQuery's pricing model (on-demand versus slot reservations) requires careful planning — we include a cost model comparison and slot reservation recommendation as part of the migration scope.
How long does a GCP migration take?▾
A GCP Landing Zone build typically takes 2–4 weeks. Full migration timelines depend on workload volume: a 20–50 workload migration typically runs 8–16 weeks across waves. BigQuery data warehouse migrations with significant dbt model adaptation can take 4–10 weeks depending on model complexity and data volumes. Wolk Inc provides per-wave timelines after the discovery assessment.
Does Wolk Inc work on GCP and AWS simultaneously for multi-cloud architectures?▾
Yes. Wolk Inc regularly designs and implements multi-cloud architectures where GCP hosts analytics and ML workloads while AWS handles primary application infrastructure (or vice versa). We design the connectivity (VPN or Dedicated Interconnect + Direct Connect), data replication strategy, and IAM federation so that both clouds operate within a single governance framework.