Technology
Google Cloud Development & Consulting Services
GCP architecture, GKE, Cloud Run, BigQuery, and Vertex AI — production engineering for organizations leveraging Google’s data and AI strengths.
What we build with Google Cloud
- GCP landing zones with Folders, Org Policies, and resource hierarchy
- GKE Autopilot and Standard clusters with Workload Identity
- Cloud Run and Cloud Functions for serverless workloads
- BigQuery for analytics and warehousing at scale
- Vertex AI for ML and generative AI workloads
- Terraform or Config Connector for IaC
Why DiveScale
Built by engineers who ship Google Cloud in production
GCP shines when your workload is data-heavy (BigQuery), AI-heavy (Vertex AI, Gemini), or container-native (GKE, Cloud Run). DiveScale ships GCP environments with proper governance — Folders, Org Policies, Workload Identity — built in from day one.
We default to GKE Autopilot for teams that want Kubernetes without node management; Cloud Run for stateless containers without K8s; Cloud Functions where event-driven serverless wins. The choice is per workload, not cluster-wide.
On the data side, BigQuery is genuinely best-in-class for serverless analytics. We pair it with Dataflow or BigQuery scheduled queries for pipelines, and Looker or Looker Studio for visualization.
Google Cloud use cases we deliver
How we deliver
Our Google Cloud delivery process
- 01
Landing zone
Resource hierarchy, Org Policies, baseline IAM, and centralized logging designed before workloads move.
- 02
IaC & pipelines
Terraform or Config Connector with Cloud Build or GitHub Actions pipelines.
- 03
Migrate or build
Workloads moved or built incrementally — GKE, Cloud Run, BigQuery, or Vertex AI based on fit.
- 04
Operate & optimize
Cost reviews, Security Command Center baselines, and ongoing architecture checks.
Related technologies
AWS
AWS architecture, migration, and platform engineering — multi-account governance, well-architected workloads, Terraform IaC, and the operational discipline production demands.
Learn moreMicrosoft Azure
Azure architecture, App Service, AKS, Functions, and Azure OpenAI — enterprise-grade builds for Microsoft-aligned organizations.
Learn moreKubernetes
Production Kubernetes engineering — cluster design, GitOps, observability, CIS hardening, multi-tenancy, internal developer platforms, and the day-2 operations the demos skip.
Learn moreTerraform
Terraform engineering — module design, state strategy, multi-account governance, policy-as-code, drift detection, and CI-driven plan / apply for multi-cloud estates.
Learn moreGoogle Cloud — Frequently Asked Questions
GCP wins on data analytics (BigQuery), Kubernetes ergonomics (GKE), and AI (Vertex, Gemini). AWS wins on breadth. Azure wins on Microsoft alignment. We help teams pick honestly per workload.
