Cloud · GCP · Strategy
The right GCP architecture depends on decisions — resource hierarchy, project structure, service selection — that are hard to unwind once made. We bring deep GCP expertise to get those decisions right from the start, especially where data and AI workloads are involved.
GCP architecture decisions matter most where they touch the platform's genuine differentiators — data analytics, machine learning infrastructure, and Kubernetes-native design. Getting the architecture right means structuring your environment to take real advantage of those strengths, not just deploying a generic cloud template that happens to run on Google's infrastructure.
Whether you're designing a landing zone for a new GCP environment or reviewing years of organic growth, our consulting engagements give you a clear, documented path forward.
Assessment against Google Cloud's best-practice framework, covering security, reliability, cost, and performance
Organization, folder, and project structure design and governance
Matching GCP's catalog to your workload, especially data and AI use cases
VPC design and IAM structure planning
A phased plan for GCP adoption, expansion, or remediation
Typically 2–4 weeks depending on environment size and complexity, though larger multi-project environments may take longer.
Both — many engagements start with an existing environment that's grown without a clear strategy, and the review identifies what to fix versus what's already solid.
No — consulting is an assessment and design phase; any changes to production are planned and executed separately, with your sign-off.