Google Cloud
Google Cloud Platform (GCP) Services
We design, migrate, build and operate data, analytics, AI and infrastructure workloads on Google Cloud, with engineering discipline from the first assessment to a monitored production platform.
Get More from Google Cloud, Faster
Google Cloud brings together a serverless data warehouse in BigQuery, a governed semantic layer in Looker, Gemini models and agent tooling through Gemini Enterprise Agent Platform (formerly Vertex AI), and mature infrastructure services for compute, storage and networking. The opportunity is large, but so is the surface area: hundreds of services, several pricing models and many ways to assemble them. Most organizations need help choosing the right building blocks and wiring them together properly.
Hanoi Technology works with Google Cloud across the full lifecycle. We move legacy warehouses and virtual machines onto the platform, build analytics and customer data products on top of BigQuery, put cost and governance controls in place, and run what we build under clear service levels. Our delivery hub in Hanoi supports clients in North America, Europe and Asia-Pacific with weekly written progress updates and sprint demos.
The Challenge
What Slows Down Google Cloud Programs
These are the issues we most often find when a client asks us to review an existing Google Cloud estate.
Lift-and-Shift Without Redesign
Workloads moved as-is keep their on-premises sizing, batch windows and licensing assumptions. They work, but they cost more than they should and miss serverless options such as BigQuery, Cloud Run or managed databases.
Fragmented Data and Duplicate Metrics
Teams load the same sources into separate datasets and define revenue or churn differently in each dashboard. Without a shared model, executives stop trusting the numbers and analysts spend their time reconciling.
Spend That Nobody Owns
On-demand BigQuery queries, oversized instances, idle disks and forgotten projects accumulate quietly. When labels, budgets and commitments are missing, finance sees the invoice long before engineering sees the cause.
Governance Added Too Late
IAM roles granted broadly during a pilot, unclassified personal data and missing audit trails become blockers when a security review finally arrives. Retrofitting controls is slower than designing them in.
Business Value
Why Build on Google Cloud
Serverless Analytics at Any Scale
BigQuery separates storage and compute and scales without cluster management. Teams query terabytes with standard SQL and pay for what they use or reserve capacity through editions.
One Semantic Layer for BI and AI
Looker’s LookML model defines metrics once and serves them to dashboards, embedded analytics and conversational agents, so humans and AI see the same numbers.
Built-In AI Close to Your Data
Gemini models, BigQuery ML and agent tooling run next to your governed data, which shortens the path from a use case to a production feature.
Open Formats and Multicloud Reach
BigLake and Apache Iceberg support, plus cross-cloud connectivity, let you query data where it lives instead of copying everything first.
Native Cost Intelligence
Cloud Billing reports, FinOps hub, anomaly detection and recommenders expose waste and savings opportunities without extra tooling.
Security by Default
Encryption at rest and in transit, organization policies, VPC Service Controls and Knowledge Catalog governance give you a strong baseline to build on.
Google Cloud Is a Platform, Not a Product
The value comes from combining services well: BigQuery with Looker, Knowledge Catalog with IAM, Backup and DR with a tested runbook. We focus on that integration work, because that is where most programs either succeed or quietly stall.
Our Services
Hanoi Technology’s End-to-End Google Cloud Services
Our Google Cloud practice covers modernization, analytics, AI, cost and resilience.
Data Warehouse Modernization
We migrate Teradata, Oracle, Netezza, SQL Server and Hadoop warehouses to BigQuery using BigQuery Migration Service for assessment and SQL translation, then redesign models for partitioning, clustering and cost.
- Migration assessment and wave plan
- Translated and validated SQL
- Optimized BigQuery data model
Analytics and Business Intelligence
We build Looker semantic models, governed dashboards and embedded analytics, and enable conversational analytics on top of trusted LookML definitions.
- LookML model and style guide
- Executive and operational dashboards
- Embedded analytics integration
Customer Data and AI
We assemble customer data platforms in BigQuery that unify web, app, CRM and advertising data, then apply segmentation, propensity models and Gemini-powered features.
- Unified customer profile
- Audience and activation pipelines
- Propensity and churn models
Infrastructure Migration
We move VMware, AWS and Azure virtual machines to Compute Engine with Migrate to Virtual Machines, using test clones and wave-based cutovers to keep downtime short.
- Discovery and sizing report
- Landing zone and network design
- Tested cutover runbooks
FinOps and Cost Optimization
We set up billing export, labeling, budgets and dashboards, right-size resources and plan committed use discounts so savings are sustained, not one-off.
- Cost allocation model
- Savings backlog with estimates
- Monthly optimization review
Backup, DR and Managed Operations
We design protection with Backup and DR Service and backup vaults, document recovery objectives and run the platform as a managed service.
- Backup plans and policies
- DR runbook and test results
- Managed service with SLAs
Explore
Explore Our Google Cloud Services
- Looker AnalyticsGoverned semantic models, dashboards, embedded and conversational analytics on Looker.Learn more
- Teradata to BigQuery MigrationAssessment, SQL translation, data transfer and validation from Teradata to BigQuery.Learn more
- Customer Data Platform on Google CloudUnified customer profiles, segmentation and activation built on BigQuery.Learn more
- FinOps on GCPCost visibility, allocation, accountability and forecasting for Google Cloud spend.Learn more
- DWH Modernization with BigQueryRe-architect legacy warehouses as a modern, governed BigQuery platform.Learn more
- GCP Smart AnalyticsStreaming, batch and AI-assisted analytics across BigQuery, Dataflow and Looker.Learn more
- GCP Cost OptimizationRight-sizing, commitments, BigQuery tuning and storage cleanup with measured savings.Learn more
- Google Cloud Backup and DRImmutable backups, recovery plans and tested failover with Backup and DR Service.Learn more
- VM Migration to GCPMove VMware, AWS and Azure VMs to Compute Engine with Migrate to Virtual Machines.Learn more
Our Approach
How We Deliver on Google Cloud
Every engagement follows the same five stages, scaled to its size.
- 01
Assess
We inventory workloads, data sources, costs and constraints using Migration Center, billing data and stakeholder interviews, and agree on measurable goals.
Deliverables: Current-state assessment · Business case and priorities
- 02
Design the Foundation
We define the resource hierarchy, IAM model, networking, organization policies and logging so later workloads land in a secure, consistent environment.
Deliverables: Landing zone design · Security and governance baseline
- 03
Migrate and Build
We deliver in two-week sprints with demos, moving or building workloads in waves and automating infrastructure with Terraform.
Deliverables: Infrastructure as code · Migrated or new workloads
- 04
Validate and Optimize
We compare results against source systems, test performance and recovery, and tune cost before each wave is signed off.
Deliverables: Validation reports · Performance and cost tuning log
- 05
Operate and Improve
We hand over with documentation and training, or run the platform as a managed service with monitoring, patching and monthly cost reviews.
Deliverables: Runbooks and training · Managed service reporting
Use Cases
Google Cloud Use Cases We Deliver
Typical outcomes clients ask us for on Google Cloud.
Retire an Aging On-Premises Warehouse
A retailer moves a Teradata system nearing contract renewal to BigQuery, translating thousands of SQL scripts and running both platforms in parallel until reports reconcile.
Single Version of KPIs
A subscription business replaces dozens of spreadsheet reports with a Looker model where revenue, churn and retention are defined once and reused everywhere.
Data Center Exit
A services company migrates several hundred VMware virtual machines to Compute Engine in planned waves, with test clones validated before each cutover weekend.
Personalization from First-Party Data
An e-commerce brand unifies GA4, CRM and order data in BigQuery to build audiences and recommendation features for its site and campaigns.
Cutting Cloud Spend Without Slowing Teams
A SaaS provider introduces labels, budgets and BigQuery reservations, then commits to steady-state compute once usage patterns are clear.
Ransomware-Resilient Backups
A financial services firm protects Compute Engine, Cloud SQL and SAP HANA workloads in immutable backup vaults and rehearses restores quarterly.
Technology
Google Cloud Technologies We Work With
We choose services based on workload fit, cost and the skills of the team that will run them.
- BigQuery
- Looker
- Gemini Enterprise Agent Platform
- BigQuery Migration Service
- Dataflow
- Pub/Sub
- Dataproc
- Cloud Composer
- Dataform
- Knowledge Catalog
- Compute Engine
- Google Kubernetes Engine
- Cloud Run
- Migrate to Virtual Machines
- Backup and DR Service
- Terraform
Platforms
Deliver Google Cloud on Your Preferred Platform
Why Hanoi Technology
Why Organizations Choose Hanoi Technology
Senior, Cross-Functional Teams
Strategy, data, AI, cloud and engineering specialists work as one team, so nothing is lost between hand-offs.
Proven Delivery
More than 50 projects delivered for clients in North America, Europe and Asia-Pacific.
Radical Transparency
A written update every week and a demo of working software every sprint, so you always know where things stand.
Cost-Effective Global Delivery
Experienced engineers from our Hanoi delivery hub, with working-hour overlap for every major time zone.
Success Story · E-commerce and retail
Personalized shopping experience for a US fashion retailer
A fast-growing US fashion and lifestyle retailer had plenty of traffic but a 2.1% conversion rate. We combined a recommendation engine with a simpler path from discovery to checkout.
Read the Full StoryMore Success Stories
Logistics
−25%operational costsRoute optimization and fleet visibility for a regional logistics company
A regional delivery company handling thousands of shipments a day was planning routes and dispatching by hand. We built dynamic route optimization, a fleet dashboard and a driver app.
Fintech
+162%monthly active usersAll-in-one digital banking app for a traditional bank
A traditional financial institution wanted to compete with neobanks for mobile-first customers. We replaced a set of separate banking, investing and payment apps with one product that people use every day.
Resources
Featured Resources
Industry trends and practical guidance to help you get more value from data, AI and technology.
FSMA 204 After the Delay: Using Shipment Monitoring to Get Traceability-Ready by 2028
The FDA Food Traceability Rule deadline moved to July 2028, but the data work is large. Here is how to use shipment monitoring and event data to get ready without wasting the extra time.
CSRD After the Omnibus: What the Revised ESRS Mean for Reporting From 2027
The Omnibus and the simplified ESRS reshaped EU sustainability reporting in 2026. Here is who is in scope, what changed in the standards and how to adapt your data and process.
OpenTelemetry in 2026: Building a Vendor-Neutral Observability Strategy
OpenTelemetry has become the default way to collect telemetry. Here is what changed in 2026 and a practical roadmap for a vendor-neutral observability stack.
Plan Your Next Step on Google Cloud
Tell us what you are running today and where you want to be. Book a free consultation and we will reply within 24 hours with suggested next steps.
Google Cloud FAQ
Are you an official Google Cloud partner?
We do not claim any official partner tier. We work with Google Cloud as an engineering and delivery team, using Google’s documented tools such as BigQuery Migration Service, Migrate to Virtual Machines and Backup and DR Service. If your procurement process requires a Google partner of record for licensing or credits, we are happy to work alongside one while we handle architecture, migration and engineering.
Which Google Cloud services do you cover?
Our focus is data and analytics (BigQuery, Looker, Dataflow, Pub/Sub, Dataproc, Knowledge Catalog), AI with Gemini models and Gemini Enterprise Agent Platform, infrastructure migration to Compute Engine and GKE, FinOps and cost optimization, and backup and disaster recovery. For niche services we start with a short technical spike before committing to estimates, so you are not paying for us to learn on the job.
How long does a typical Google Cloud project take?
A focused assessment usually takes two to four weeks. A Looker implementation or cost optimization program typically runs six to twelve weeks. Warehouse and data center migrations are planned in waves and can take several months depending on the number of workloads, SQL complexity and how long parallel running must last. We provide a wave plan with dates after the assessment rather than guessing upfront.
What drives the cost of an engagement?
The main drivers are the number of workloads or data sources, the volume and complexity of code to translate, integration and security requirements, the validation effort required by your business, and whether you want us to operate the platform afterward. We price assessments as fixed-scope projects and larger programs as sprints or dedicated teams, with a clear estimate before each phase begins.
How do you handle security and compliance?
We design least-privilege IAM, organization policies, VPC Service Controls where appropriate, customer-managed encryption keys when required, and centralized audit logging. Sensitive data is classified and governed through Knowledge Catalog and BigQuery policy tags. We work within your access policies, use your accounts rather than ours, and document every control so your security team can review it.
Can you work with our existing team and tools?
Yes. Many clients engage us as a dedicated team that works inside their repositories, ticketing and CI/CD pipelines. We overlap working hours with your time zone, share weekly written progress updates and demo every sprint. Knowledge transfer is planned from the start so your engineers can own the platform, or we continue as a managed service if you prefer.