Trusted Digital Transformation Partner
ROSTAN partners with Google Cloud to deliver world-class data engineering, AI/ML workloads, and cloud-native applications. Leveraging GCP's global fiber network (spanning 200+ countries), BigQuery's serverless analytics, and Vertex AI for MLOps, we architect solutions that turn data into competitive advantage — from petabyte-scale analytics pipelines to real-time ML prediction endpoints in production.
Multi-Region GCP Architecture — Mumbai & Iowa
ROSTAN is a Google Cloud Partner delivering six distinct GCP service lines from one team: Cost Optimization (FinOps — Committed Use Discounts, right-sizing, no migration required), Managed Services (SRE-style 24×7 operations on infrastructure that already runs), DevOps (Cloud Build CI/CD and infrastructure-as-code), Infra Sizing (Cloud Maturity Assessment and capacity planning), Development (building on Cloud Run, App Engine and Cloud Functions), and Management (multi-project governance, IAM and VPC Service Controls). Each is a separate engagement with its own scope.
Each is a distinct capability with its own scope. Engage one, or several — they are not bundled.
A standalone engagement — we do not need to have built your infrastructure to reduce what you pay for it. We audit your project against Committed Use Discounts, Preemptible/Spot VM opportunities, GKE Autopilot per-Pod billing, and BigQuery slot commitment versus on-demand spend. Most customers see a 25–40% cost reduction within 90 days.
Day-to-day operations on infrastructure that already runs — you do not need to migrate anything to bring us in. SRE-style operations with defined SLO/SLA targets, proactive monitoring, and incident response, so your own engineers stay off the pager.
Where Managed Services keeps existing infrastructure running, DevOps changes how new releases get to it. Cloud Build and Cloud Deploy pipelines integrated with GKE and Cloud Run, so a release is a pipeline run with a rollback plan, not a maintenance window.
Distinct from Cost Optimization: this is about whether your infrastructure fits your workload, not just what it costs. Cloud Maturity Assessment, GKE node pool and BigQuery slot capacity planning against expected peak load, and autoscaling thresholds set before a launch, not after an outage teaches you where the ceiling was.
We also build on GCP, not only operate it — distinct from the BigQuery and Vertex AI work below, which is data and ML platform engineering specifically. General-purpose cloud-native application development on Cloud Run, App Engine and Cloud Functions; API design and integration; and modernising a monolith into services that use GCP primitives.
The governance layer above day-to-day operations: how your GCP projects, access and policy are structured, not how any one workload runs. Multi-project resource hierarchies, IAM and VPC Service Controls perimeters, and Organization Policy guardrails that stop a misconfiguration from becoming an incident — set up once, then audited on a schedule.
The six service lines above are delivered using deep GCP expertise across data, AI/ML, Kubernetes, and cloud-native platforms.
Cloud Maturity Assessment and phased migration to Google Cloud — from initial TCO analysis and workload discovery to production cut-over using Google's proven Migrate for Compute Engine tooling.
Kubernetes — as pioneered by Google — delivered as a fully managed service with Autopilot mode for hands-free node management, Anthos for multi-cluster federation, and zero-trust workload identity.
Serverless, petabyte-scale analytics that delivers sub-second query performance with no infrastructure management. We design end-to-end data pipelines from ingestion through transformation to BI dashboards.
End-to-end MLOps on Google's unified AI platform — from feature engineering and model training to versioned Model Registry, Prediction endpoints, and continuous evaluation pipelines in production.
Zero-trust GCP security architecture using BeyondCorp, VPC Service Controls perimeters, Cloud Armor WAF, and Chronicle SIEM — designed for PCI-DSS, ISO 27001, and PDPB compliance.
SRE-style cloud operations that keep your GCP environment healthy, cost-efficient, and compliant — with defined SLOs, automated scaling runbooks, and proactive FinOps cost governance.
Where Google Cloud leads the industry — across the capabilities that matter most for data-driven enterprises.
The technical capabilities that make GCP the platform of choice for data-intensive and AI-first organisations.
| Feature | ✓ GKE Autopilot | GKE Standard |
|---|---|---|
| Node management | Fully managed by Google | Customer manages nodes |
| Billing model | Per Pod (CPU/memory) | Per Node (VM) |
| Security hardening | Hardened by default | Manual configuration |
| Best for | Hands-off operations | Custom node pools, GPUs |
| Cluster autoscaling | Automatic, transparent | Cluster Autoscaler (manual) |
Pay per TB of data processed by queries. Ideal for ad-hoc analytics and exploratory workloads with unpredictable query volumes.
Reserve dedicated BigQuery slots (CPU) at a fixed monthly cost. Predictable billing for high-volume, production analytics pipelines.
In-memory analysis acceleration for sub-second Looker Studio and Looker dashboard queries. Reserved per-project, per-region.
How ROSTAN architects end-to-end ML delivery on Vertex AI.
Tell us what's actually going on — a rising BigQuery bill, a Vertex AI model stuck in a notebook, or infrastructure you're not sure fits the workload. You'll get a practical next step, not a sales deck.
Talk to a ROSTAN GCP architect and discover how BigQuery, GKE, and Vertex AI can accelerate your data and AI roadmap. Free assessment, no commitment.
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