Google Cloud Platform
GCP delivery covering GKE, BigQuery data-platform design, and portable app stacks built on open standards. Migration and managed operations with IaC reproducibility. If the merit is there, we recommend it — not because of a partnership checkbox.
Overview
Google Cloud Platform excels where Kubernetes, data analytics, and open standards are the priority. It is the home of GKE — the most mature managed Kubernetes service — and BigQuery, a genuinely serverless data warehouse that changes how teams think about analytics. Many teams choose GCP for its developer experience and data capabilities but struggle with cost governance and operational maturity. We build container platforms, data pipelines, and modern application stacks the portable way, so you get GCP strengths without the lock-in.
Clevertek scopes every engagement to your environment — capacity, sites, compliance and support model — so you get a tailored plan rather than a fixed SKU. Pricing is quote-only, and our solutions architects will work through your requirements before any proposal.
Our approach
We design and operate Google Cloud environments that leverage GCP strengths while keeping costs governed and architecture portable. For container platforms, we build GKE clusters with production-grade networking, security policies, and cost controls — not a quick-start cluster that breaks under load. For data, we design BigQuery warehouses with modelled schemas, cost controls, and pipeline orchestration that analysts can actually use. Across all workloads, we favour open standards — Kubernetes, Terraform, open-source tooling — so your architecture is not dependent on a single vendor strategy. We also offer managed GCP operations, including FinOps, monitoring, and incident response, for teams that want Google Cloud expertise without hiring a dedicated GCP engineer.
Why work with us
GKE expertise without the lock-in
We build production GKE clusters with proper networking, security, and cost controls — using standard Kubernetes so your workloads can run elsewhere if your cloud strategy changes.
BigQuery done cost-effectively
BigQuery cost surprises are common. We design schemas, partitioning, and query patterns that control costs while giving analysts fast, self-serve access to data.
Open-source first architecture
We use Terraform, Kubernetes, and open-source tooling wherever possible. Your GCP environment is reproducible on another cloud, not trapped in Google-specific tooling.
GCP cost governance that works
Budgets, quotas, committed-use discounts, and per-project cost tracking are configured from day one. You see what each project spends before the bill arrives.
Portable by design
We favour open standards so a GCP workload can move if your cloud strategy changes. No gratuitous lock-in, and the deliberate commitments are flagged and justified.
Managed operations available
We offer ongoing GCP operations — monitoring, FinOps, patching, incident response — for teams that want GCP expertise without a dedicated cloud engineer.
Key benefits
What this solution delivers for your business.
Production-grade Kubernetes on GKE
GKE clusters with proper networking, security policies, workload identity, and cost controls — not a development cluster that needs re-architecture for production.
Cost-effective BigQuery analytics
Properly designed schemas, partitioned tables, and query governance prevent the cost surprises that catch most new BigQuery users.
Portable, vendor-independent architecture
Open-source tooling and standard Kubernetes mean your workloads are not locked to GCP. You get GCP benefits without GCP dependency.
Predictable GCP costs
Budgets, quotas, committed-use discounts, and per-project cost dashboards give you control over GCP spend from month one.
Developer-friendly platform
CI/CD pipelines, Artifact Registry, Cloud Build, and deployment workflows that make your team productive on GCP without learning proprietary deployment tooling.
Integrated analytics pipeline
From ingestion through BigQuery to Looker dashboards — a complete analytics pipeline that turns operational data into business decisions.
What's included
Part of this managed service.
Kubernetes with GKE
Production-grade GKE clusters with autopilot or standard mode, network policies, workload identity, and cost monitoring.
- GKE cluster design and deployment
- Network policy and security controls
- Workload identity and IAM integration
- Cost monitoring per namespace
Data platform with BigQuery
Serverless data warehouse design with modelled schemas, partitioning, clustering, and cost controls for self-serve analytics.
- BigQuery warehouse design
- Data pipeline orchestration with Cloud Composer
- Cost governance and query monitoring
- Looker Studio dashboard integration
Modern application deployment
CI/CD pipelines, Cloud Run, and compute-optimised architectures for modern application stacks on GCP.
- Cloud Run serverless deployment
- Cloud Build CI/CD pipelines
- Compute Engine rightsizing
- Artifact Registry and container management
GCP cost governance
Budgets, committed-use discounts, per-project cost allocation, and monthly cost reviews to keep GCP spend under control.
- Budget and alert configuration
- Committed-use discount planning
- Per-project cost allocation tags
- Monthly FinOps review
Where it helps
Real-world scenarios where this solution delivers measurable outcomes.
A Kubernetes platform done right
Stand up GKE with the policies, security, and cost controls a platform team needs — not a weekend cluster that breaks in production.
Analytics on open standards
Build a BigQuery data platform your team can run and your consultants can exit, without proprietary lock-in or surprise query costs.
Multi-cloud data pipeline
Use GCP as your analytics layer while running compute on another cloud — taking advantage of BigQuery and Looker without committing your entire estate to one provider.
Questions buyers actually ask
Should we be on GCP or AWS?
It depends on the workload and your team. GCP is strongest on Kubernetes, data analytics, and developer experience. We tell you straight which fits, including both for different things.
Are we locked into Google?
We design portably where it is free, and flag the deliberate commitments. You should know exactly where you are tied and why.
Do you run it after build?
Yes — managed GCP operations is available, or we hand the platform to your team with runbooks and a cost review rhythm.
How do you control BigQuery costs?
Schema design, partitioning, clustering, and query governance from day one. We also set custom quotas and budgets per project, with alerts before costs exceed thresholds.
Can you help us migrate from another cloud to GCP?
Yes — including workload migration, data transfer, and identity federation. We provide a TCO comparison and migration plan before any work starts.
Ready to scope a solution?
Talk to a Clevertek solutions architect about your requirements — no obligation.