Google Cloud architecture advisory for data and AI workloads, partner-delivered build.
Lightbridge Cloud provides Google Cloud architecture advisory and platform selection for organizations that treat data as a strategic asset: BigQuery analytics design, Vertex AI fit assessment, and GKE reference architecture. Selection and architecture run in-house; the hands-on build runs through Lightbridge Cloud's vetted partner network, under Lightbridge Cloud's own project management and technical leadership.
Lightbridge Cloud Google Cloud advisory capabilities.
BigQuery Analytics Architecture
Serverless data warehouse architecture, BigQuery ML integration planning, and real-time streaming ingestion design, sized in-house for petabyte-scale analytics before a delivery partner builds it.
Vertex AI Fit Assessment
Model deployment approach for custom models, AutoML, and foundation model fine-tuning, assessed and architected in-house; production training and deployment run through a vetted delivery partner.
GKE and Container Architecture
Google Kubernetes Engine cluster design, multi-cluster strategy, and Anthos service mesh planning, specified in-house for a delivery partner to build and operate at cutover.
Data Engineering Architecture
Dataflow, Dataproc, Pub/Sub, and Cloud Composer pipeline design for ETL, streaming, and orchestration, architected in-house to scale with data volume and complexity.
Cloud-Native Application Architecture
Reference architecture for Cloud Run, App Engine, Cloud Functions, and Firebase, designed for workloads that scale to zero and burst to millions, built through our delivery partner network.
Security and Networking Architecture
VPC Service Controls, Cloud Armor, Identity-Aware Proxy, and organization policy design for regulated workloads, specified in-house for a vetted delivery partner to implement.
Lightbridge Cloud: Google Cloud architecture for organizations that compete on data.
Google Cloud processes over 100 billion rows per second through BigQuery globally. Organizations that adopt Google Cloud for analytics and AI workloads gain access to the same data infrastructure that powers Google Search, YouTube, and Waymo. Lightbridge Cloud designs the architecture that brings that capability to mid-market enterprises, in-house, before routing the build to a vetted delivery partner. For private application access to managed PostgreSQL, MySQL, and SQL Server instances, see the Cloud SQL Auth Proxy guide.
Lightbridge Cloud's Google Cloud advisory works alongside Lightbridge.ai for AI strategy and Lightbridge Automation for AI governance. When BigQuery analytics surface an opportunity for a predictive model, Lightbridge Cloud designs the Vertex AI architecture with responsible AI frameworks built in, then routes production training and deployment to our delivery partner network.
Petabyte
scale analytics architecture on BigQuery
Vertex AI
fit assessment and architecture for production ML
GKE
container architecture at enterprise scale
Frequently asked questions.
What does Lightbridge Cloud actually do on Google Cloud engagements?
Lightbridge Cloud runs Google Cloud architecture advisory and platform selection in-house: BigQuery analytics architecture, Vertex AI fit assessment, and GKE reference architecture. Lightbridge Cloud does not build or operate Google Cloud infrastructure directly. The hands-on build runs through Lightbridge Cloud's vetted partner network, under Lightbridge Cloud's own project management and technical leadership.
When should an organization choose Google Cloud over AWS or Azure?
Google Cloud is the strongest platform for data analytics, machine learning, and AI workloads: BigQuery, Vertex AI, and the data engineering stack (Dataflow, Pub/Sub, Dataproc) lead the category. Organizations that treat data as a strategic asset and plan production AI workloads benefit most from Google Cloud. Lightbridge Cloud recommends the platform that fits each workload, including AWS or Azure when either is the better fit.
Does Lightbridge Cloud design Vertex AI architecture for production ML workloads?
Yes. Lightbridge Cloud assesses and architects production ML approaches on Vertex AI in-house, including model strategy, AutoML fit, versioning, and A/B serving design. Lightbridge Cloud also works with Lightbridge.ai for AI strategy and with Lightbridge Automation for AI governance when ML workloads require responsible AI frameworks. Production training and deployment are carried out by a vetted delivery partner under Lightbridge Cloud's technical leadership.
How does Lightbridge Cloud approach BigQuery architecture?
Lightbridge Cloud designs BigQuery architecture in-house: dataset organization, partitioning and clustering strategy, materialized views, authorized views for access control, and cost governance through slot reservation and on-demand pricing analysis. The resulting architecture is built and operated by our delivery partner network.
Can Lightbridge Cloud advise on multi-cloud environments that include Google Cloud?
Yes. Lightbridge Cloud advises across Google Cloud, AWS, and Azure, including Anthos-based multi-cluster Kubernetes strategy and the integration architecture connecting Google Cloud services with Salesforce, ERP systems, and other business platforms. Delivery for each platform routes to the practice or vetted partner built for it.
Who builds and operates the Google Cloud environment Lightbridge Cloud designs?
A rigorously vetted delivery partner builds the GKE, BigQuery, and Vertex AI architecture, under Lightbridge Cloud's project management and technical leadership throughout. Lightbridge Cloud does not maintain an in-house Google Cloud build team and does not operate infrastructure on an ongoing basis after handoff. Day-two operations run with your team or the operations partner you choose.
How does Lightbridge Cloud connect Google Cloud to Salesforce and ERP?
Lightbridge Cloud designs the integration architecture connecting Google Cloud data platforms and compute services to Salesforce, NetSuite, and other business systems, then delivers that integration layer in-house through our MuleSoft and Boomi practice. BigQuery analytics can feed Salesforce dashboards, and Vertex AI predictions can trigger CRM workflows, planned as part of the architecture, not added afterward.
Get a Google Cloud fit assessment.
Lightbridge Cloud assesses your data and AI readiness, evaluates Google Cloud fit, and delivers an architecture and selection roadmap for our delivery partner network to build.