Opsio - Cloud and AI Solutions
GCP Migration

GCP Migration Services — Built for Data & AI Workloads

Google Cloud leads in data analytics, machine learning, and Kubernetes — but migrating to GCP requires expertise in Google's unique networking model, IAM approach, and service architecture. Opsio executes GCP migrations optimized for BigQuery, GKE, and Vertex AI workloads.

Trusted by 100+ organisations across 6 countries

GCP

Specialist

BigQuery

Migration

GKE

Expert

0

Downtime

Google Cloud
BigQuery
GKE
Vertex AI
Terraform
Zero Downtime
Delivered by Opsio

What's Included

01

GCP Migration Assessment

Evaluate your workloads for GCP suitability with analysis of compute, database, data warehouse, and ML workloads against GCP services and pricing models. We build the business case with projected ROI, TCO comparison against current platform, and detailed migration roadmap.

02

Compute Migration

Migrate for Compute Engine provides automated VM replication from VMware, AWS, and Azure source environments to GCP. Continuous block-level replication enables zero-downtime cutover with tested rollback procedures for every migration wave and non-disruptive test environment validation.

03

Database Migration

GCP Database Migration Service for MySQL, PostgreSQL, and SQL Server to Cloud SQL or AlloyDB. Oracle migrations to PostgreSQL-compatible AlloyDB deliver significant license savings while maintaining application compatibility. Continuous replication ensures near-zero downtime cutover.

04

Data Warehouse Migration

Migrate from Teradata, Netezza, Oracle, Redshift, or Synapse to BigQuery. ETL pipeline migration to Dataflow and Cloud Composer ensures analytics workflows continue uninterrupted. BigQuery's serverless architecture eliminates cluster management and delivers significant price-performance improvement.

05

Container Migration to GKE

Containerize applications and migrate to Google Kubernetes Engine with Docker image optimization, Helm chart creation, GKE cluster design with Autopilot mode for simplified operations, workload identity configuration for pod-level security, and service mesh setup for complex microservices.

06

ML Pipeline Migration

Migrate ML training and serving infrastructure to Vertex AI including model retraining pipeline setup, serving endpoint configuration with autoscaling, feature store migration, GPU resource optimization with preemptible VMs, and end-to-end MLOps pipeline automation for production workloads.

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Verified customer
Opsio's focus on security in the architecture setup is crucial for us. By blending innovation, agility, and a stable managed cloud service, they provided us with the foundation we needed to further develop our business. We are grateful for our IT partner, Opsio.
Opus Bilprovning logo

Jenny Boman

CIO · Opus Bilprovning

Migrate to GCP for Data and AI Excellence

Google Cloud Platform offers best-in-class capabilities for data analytics with BigQuery, machine learning with Vertex AI, and container orchestration with GKE. If your workloads are data-intensive, AI-driven, or container-native, a GCP migration delivers compelling performance advantages and significant price-performance improvements over alternative platforms. Opsio executes GCP migration projects using Migrate for Compute Engine for server migration, Database Migration Service for Cloud SQL and AlloyDB, and containerization strategies for GKE deployment. Opsio specializes in data platform migrations — moving data warehouses from Teradata, Redshift, or Synapse to BigQuery, and ML training pipelines to Vertex AI with zero-downtime methodology.

For organizations already using GCP or evaluating it alongside AWS and Azure, we provide vendor-neutral assessment and GCP-specific migration planning. Our GCP migration experts understand Google Cloud's unique project hierarchy, VPC networking model, IAM service accounts, and pricing structure — knowledge that prevents costly mistakes during migration.

The GCP landing zone includes Organization setup, folder hierarchy for environment separation, VPC networking with Shared VPC for centralized management, IAM policies with service accounts and workload identity, centralized logging with Cloud Logging, and security baseline with Security Command Center — all deployed with Terraform for reproducibility.

Common GCP migration challenges: understanding Google's project-based resource hierarchy, configuring VPC networking that differs from AWS/Azure VPC models, migrating from proprietary data warehouse systems to BigQuery's serverless architecture, containerizing applications for GKE deployment, and optimizing Committed Use Discounts that work differently from AWS Reserved Instances.

Evaluating google cloud platform migration cost? Assessment runs $5,000-$12,000. Standard compute migration costs $25,000-$55,000. Data warehouse migration to BigQuery ranges from $30,000-$100,000+ depending on data volume and ETL pipeline complexity. GCP's price-performance advantages often deliver ongoing savings that compound quarterly. Featured reading from our knowledge base: GCP Migration: Flytta till Google Cloud Platform, AWS MAP for Windows Workloads: Migration Strategies and Licensing, and Azure Data Migration from On Premise to Cloud: Expert Guidance. Related Opsio services: Database Migration Services — Zero Data Loss, Minimal Downtime, Platform Engineering Consulting, AWS Migration Services — MAP Funded, Zero-Downtime, and AWS Cloud Migration Consulting — Plan & Execute.

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Database MigrationGCP Migration
Data Warehouse MigrationGCP Migration
Container Migration to GKEGCP Migration
ML Pipeline MigrationGCP Migration
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Container Migration to GKEGCP Migration
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How Opsio Compares

CapabilityDIY MigrationSystem IntegratorOpsio
GCP platform expertiseLearning curveGeneralistCertified GCP architects + data specialists
BigQuery migrationManual ETL rewriteBasic transferFull pipeline migration + optimization
GKE containerizationDeveloper self-serviceBasic DockerProduction GKE with Autopilot + security
Migration methodologyAd hocWaterfallAgile waves with zero-downtime
Cost optimizationStandard pricingBasic CUDsFull FinOps — CUD + sustained use + spot
Post-migration supportDIY operationsSeparate contractSame team, seamless transition
Typical cost (50 workloads)$100K+ (hidden labor)$80-130K$25-55K (+ ongoing savings)

Ready to get started?

Get a Free GCP Assessment

What You Get

GCP migration readiness assessment with workload classification and TCO
Landing zone architecture with VPC, IAM, and Organization policy baseline
Detailed migration runbook per workload with rollback procedures
Migrate for Compute Engine execution with validation testing
Database migration with schema conversion and data validation report
Post-migration performance benchmark and optimization report
30-day hypercare support with Cloud Monitoring and alerting
GCP cost optimization review 60 days post-migration with CUD recommendations
BigQuery optimization report for migrated data warehouse workloads
Knowledge transfer documentation and operational handover package

Pricing & Investment Tiers

Transparent pricing. No hidden fees. Scope-based quotes.

Migration Assessment

$5,000–$12,000

Discovery + GCP planning

Most Popular

Standard Migration

$25,000–$55,000

10-50 workloads

Enterprise Migration

$55,000–$100,000+

50+ workloads with BigQuery

Transparent pricing. No hidden fees. Scope-based quotes.

Questions about pricing? Let's discuss your specific requirements.

Get a Custom Quote

Why Choose Opsio for Cloud Services

Data platform expertise

BigQuery, Dataflow, Pub/Sub — we optimize your complete data stack for GCP.

Container specialists

GKE migration and operations at scale with Autopilot and workload identity.

AI/ML infrastructure

Vertex AI migration, GPU optimization, and MLOps pipeline automation.

Multi-cloud experience

We migrate from AWS, Azure, and on-premises to GCP seamlessly.

Terraform-native

All infrastructure defined in Terraform for reproducibility and drift prevention.

Cost optimization

GCP-specific pricing with CUDs, sustained use, and spot VM strategies.

Not sure yet? Start with a pilot.

Begin with a focused 2-week assessment. See real results before committing to a full engagement. If you proceed, the pilot cost is credited toward your project.

Our 4-Phase Delivery Process

01

Assessment

Workload analysis, GCP service mapping, cost-benefit analysis, and TCO comparison against current platform with migration roadmap. Timeline: 2-3 weeks.

02

Planning

Target architecture design, landing zone deployment with Terraform, migration strategy per workload, and project timeline with dependencies. Timeline: 2-4 weeks.

03

Migration

Server, database, data warehouse, and container migration execution with zero-downtime cutover, validation, and tested rollback. Timeline: 4-12 weeks.

04

Optimization

Performance tuning, CUD recommendations, right-sizing, security hardening with SCC, and operational handover with monitoring. Timeline: 2-4 weeks.

Key Takeaways

  • GCP Migration Assessment
  • Compute Migration
  • Database Migration
  • Data Warehouse Migration
  • Container Migration to GKE

Industries Served by Opsio

Data & Analytics

BigQuery migration from legacy data warehouses for modern analytics platforms.

AI/ML Organizations

Vertex AI migration for ML training, serving, and production operations.

SaaS & Technology

GKE-based container workloads with Autopilot for operational simplicity.

Media & Entertainment

High-throughput content processing and delivery with Cloud CDN and GKE.

GCP Migration Services — Built for Data & AI Workloads — FAQ

Why choose GCP over AWS or Azure?

GCP excels at data analytics with BigQuery's serverless architecture, machine learning with Vertex AI's integrated platform, and Kubernetes with GKE's Autopilot mode. If your workloads are data-intensive, AI-driven, or container-native, GCP often offers better price-performance. We help you evaluate objectively based on your specific workload characteristics, not platform preferences. Organizations with heavy data warehouse workloads frequently see 30-50% cost reductions moving to BigQuery, while those running large Kubernetes deployments benefit from GKE Autopilot's reduced operational overhead.

Can you migrate from AWS to GCP?

Yes. We migrate workloads from AWS, Azure, and on-premises to Google Cloud using Migrate for Compute Engine for servers, Database Migration Service for databases, and BigQuery Transfer Service for data warehouse migration. Our GCP migration methodology handles networking differences, IAM reconfiguration, and application testing throughout the cross-cloud transition. Cross-cloud migrations require careful planning for service equivalency mapping, as GCP networking and IAM models differ significantly from AWS and Azure, and our experience prevents the configuration mistakes that cause post-migration issues.

How much does GCP migration cost?

Assessment: $5,000-$12,000. Standard compute migration of 10-50 workloads: $25,000-$55,000. Data warehouse migration to BigQuery: $30,000-$100,000+ depending on data volume and ETL complexity. Enterprise migration of 50+ workloads: $55,000-$100,000+. We provide fixed-price quotes after assessment with detailed scope and timeline. GCP's competitive pricing with Committed Use Discounts and sustained use savings frequently delivers ongoing cost reductions that offset the migration investment within the first year of operations. All pricing is transparent with no hidden charges, and we include post-migration optimization in every engagement.

How long does GCP migration take?

Simple compute migration of 10-20 servers takes 4-8 weeks. Data warehouse migrations to BigQuery take 6-12 weeks including ETL pipeline migration and validation. Full datacenter migrations with database modernization and containerization typically span 3-6 months depending on workload complexity and team availability. We provide detailed milestone timelines after assessment and execute migrations in planned waves, so your business operations continue normally while workloads move to GCP incrementally with validation at each stage.

Do you support hybrid GCP environments?

Yes. Opsio designs hybrid architectures using Google Anthos for multi-cloud Kubernetes management, Cloud Interconnect for private high-bandwidth connectivity, and GCP-native tools for workloads that cannot fully migrate. Our migration approach supports phased transitions at your pace with hybrid connectivity maintained throughout. Anthos provides consistent Kubernetes management across on-premises and GCP, meaning container workloads can move between environments seamlessly while your team uses the same operational tools and procedures regardless of where the workload runs.

Can you migrate our data warehouse to BigQuery?

Yes — data warehouse migration to BigQuery is a core specialty. We migrate from Teradata, Netezza, Oracle, Amazon Redshift, Azure Synapse, and on-premises SQL-based warehouses. Migration includes schema translation, ETL pipeline conversion to Dataflow or Cloud Composer, data validation, and query performance optimization for BigQuery's columnar architecture. BigQuery's serverless model eliminates cluster management entirely, and our optimization ensures your existing queries perform as well or better on BigQuery while taking advantage of its unique capabilities like nested fields and streaming inserts.

What is GKE Autopilot and should I use it?

GKE Autopilot is Google's fully managed Kubernetes mode where Google manages the nodes, scaling, and infrastructure — you only manage workloads. It reduces operational overhead significantly compared to standard GKE. We recommend Autopilot for most workloads unless you need specific node configurations, GPU node pools, or advanced networking that requires standard mode. Autopilot also optimizes costs automatically by right-sizing pod resources and bin-packing workloads efficiently, often delivering 20-30% lower compute costs compared to manually managed standard GKE clusters.

How do you handle GCP networking during migration?

GCP networking differs from AWS and Azure VPC models. We configure Shared VPC for centralized network management, set up Cloud NAT for outbound connectivity, deploy Cloud Load Balancing for traffic distribution, and establish Cloud Interconnect or VPN for hybrid connectivity. Network design happens during the planning phase before any workload migration begins. Understanding GCP's global VPC model, which differs fundamentally from the regional VPC approach in AWS and Azure, is critical for correct network architecture and avoiding the connectivity issues that catch teams unfamiliar with Google Cloud.

What about GCP licensing and costs?

GCP uses Committed Use Discounts (CUDs) instead of Reserved Instances, sustained use discounts that apply automatically, and competitive per-second billing. For database migrations, moving from Oracle to AlloyDB (PostgreSQL-compatible) eliminates Oracle licensing entirely. We model TCO during assessment so you understand the full cost picture before committing. Organizations migrating from Oracle databases frequently save $50,000-$500,000 annually in licensing costs alone by moving to AlloyDB, making the migration investment pay for itself rapidly through eliminated proprietary database fees.

Do you provide post-migration GCP management?

Yes. Every migration includes 30 days of hypercare with monitoring and incident response. After hypercare, we offer ongoing GCP managed services — 24/7 monitoring, GKE operations, BigQuery optimization, security management, and cost governance. The same team that migrated your workloads manages them, providing continuity and deep environment knowledge. During hypercare, we proactively tune monitoring thresholds, optimize resource configurations based on actual production traffic, and address any post-migration issues to ensure your GCP environment is fully stable.

Still have questions? Our team is ready to help.

Get a Free GCP Assessment
Editorial standards: Written by certified cloud practitioners and reviewed by our engineering team.
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GCP Migration Services — Built for Data & AI Workloads

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