GCP DevelopmentGCP Development Company
Google Cloud Platform — leader in Kubernetes, data analytics, and AI/ML with Google's global network backbone.
Matlab Infotech architects Google Cloud Platform solutions leveraging GCP's leading data analytics (BigQuery), containerisation (GKE — Kubernetes' birthplace), and AI/ML services (Vertex AI). For data-intensive products and AI-first companies, GCP is often the optimal cloud choice.
25+
GCP Projects
Google Cloud Platform architectures delivered across analytics, AI/ML, and SaaS companies
10x
BigQuery Performance
Average query speed improvement vs. traditional data warehouses like Redshift or Snowflake
99.99%
GKE Uptime
Kubernetes service availability on GKE Autopilot across client production workloads
1PB+
Data Processed
Cumulative data processed through Matlab Infotech-architected GCP data pipelines
Why GCP
Why GCP Leads in Data, AI, and Kubernetes
BigQuery Data Warehouse
BigQuery is the world's leading serverless data warehouse — petabyte-scale SQL analytics in seconds with zero infrastructure management.
Kubernetes Origin
Google invented Kubernetes and GKE is the most mature managed Kubernetes service — features land in GKE first before AWS EKS or AKS.
Vertex AI Platform
Vertex AI provides managed pipelines, model registry, and AutoML — the most integrated MLOps platform of any major cloud.
Google's Network Backbone
GCP runs on Google's private global fibre network — lower latency and higher bandwidth than other clouds for international traffic.
Firebase Integration
Firebase is GCP-native — Firestore, Authentication, and Cloud Functions integrate seamlessly with BigQuery export and Cloud Run.
Sustainability Leader
GCP matches 100% of its energy use with renewable energy — the most carbon-neutral major cloud platform.
What We Offer
Our GCP Development Services
GCP Architecture Design
Google Cloud architecture designed around reliability, data strategy, and AI/ML capabilities using Well-Architected principles.
GKE Kubernetes Deployment
Google Kubernetes Engine clusters with Autopilot mode, Workload Identity, Binary Authorization, and Anthos Service Mesh.
BigQuery Data Warehousing
BigQuery schema design, partitioning, clustering, dbt data models, and Looker Studio dashboards for analytics at scale.
Vertex AI & MLOps
Vertex AI Pipelines, Model Registry, Feature Store, and managed training jobs for production ML model lifecycle management.
Cloud Run Serverless
Containerised serverless workloads on Cloud Run — event-driven, auto-scaling, and priced per request for cost-efficient APIs.
Cloud SQL & Spanner
Managed PostgreSQL/MySQL on Cloud SQL and globally consistent Cloud Spanner for high-write distributed applications.
Pub/Sub Event Streaming
Google Cloud Pub/Sub event pipelines for real-time data ingestion, microservices decoupling, and audit log streaming.
GCP Cost Optimisation
Committed Use Discounts, Spot VM strategies, BigQuery slot reservations, and Cloud Billing budget alerts to control GCP spend.
What We Build
Business Solutions We Deliver with GCP
Data Platform & Analytics
End-to-end GCP data platforms: Dataflow ingestion → BigQuery warehouse → Looker Studio dashboards for analytics-first companies.
AI/ML Products
Vertex AI-powered product features — recommendation engines, NLP classification, fraud detection, and generative AI APIs.
High-Traffic APIs on GKE
Global GKE clusters serving millions of API requests with horizontal pod autoscaling and multi-regional failover.
Firebase + GCP Hybrid
Firebase for client-facing real-time features + BigQuery export + Cloud Run backend for a complete GCP-native stack.
Streaming Data Pipelines
Pub/Sub + Dataflow streaming pipelines processing millions of events per hour for IoT, analytics, and fraud detection.
Document AI Processing
Automated document extraction and classification using Google Document AI for insurance, legal, and financial workflows.
Media & Content Processing
Cloud Storage + Transcoder API + Cloud CDN for video processing, adaptive bitrate streaming, and global content delivery.
Multi-Cloud with GCP
Anthos-managed multi-cloud architectures running workloads across GCP, AWS, and on-premises from a single control plane.
Technology Stack
Tools & Technologies We Pair with GCP
Compute
Data & Analytics
AI/ML
Databases
DevOps
How We Work
Our GCP Development Process
Discovery & Planning
We align on goals, architecture choices, and technical constraints before writing a single line of code.
UI/UX Design
Research-led wireframes and interactive prototypes validated with stakeholders before development begins.
Agile Development
Two-week sprints with working demos, automated testing, and a shared staging environment.
QA & Testing
Manual, automated, performance, and security testing baked into every sprint — not bolted on at the end.
Launch & Support
Zero-downtime deployments, monitoring setup, and a 90-day support window to ensure a smooth go-live.
Why Matlab Infotech
Why Choose Us for GCP Development
Dedicated Team
A focused team exclusively on your project — no context switching, no shared resources.
Agile Delivery
Two-week sprints with working demos so you always see progress and can course-correct early.
Flexible Engagement
Fixed-scope, dedicated, or hourly — choose the model that matches your budget and timeline.
NDA & IP Protection
Full IP ownership, signed NDA before work starts, and secure development environments throughout.
Transparent Communication
Slack-first async updates with daily standups and a dedicated PM keeping you in the loop.
90-Day Support
Post-launch warranty and optional retainer plans to keep your product healthy and evolving.
Industry Solutions
GCP Solutions Across Industries
Engagement Models
Flexible Hiring Models for GCP Development
Dedicated Team
From $25/hr
Full-time developers assigned exclusively to your project — no shared resources, no context switching.
- Dedicated developers
- Daily standups
- Scale monthly
- Full IP ownership
Hourly / Part-Time
From $20/hr
Pay only for the hours you use. Ideal for ongoing maintenance, reviews, and iterative improvements.
- Flexible hours
- No minimum commitment
- Weekly billing
- Pause anytime
Fixed Scope
Project-based
Agree on deliverables and price upfront. Best for well-defined projects with clear requirements.
- Fixed price
- Milestone delivery
- No surprises
- Money-back guarantee
Technology Comparison
GCP vs Other Technologies
| Feature | GCP (Matlab Infotech) | AWS for Data Workloads |
|---|---|---|
| Data warehouse | BigQuery — serverless, petabyte-scale, fast | Redshift — provisioned, requires cluster management |
| Kubernetes maturity | GKE — most feature-complete managed K8s | EKS — catching up but GKE innovates first |
| MLOps platform | Vertex AI — most integrated end-to-end | SageMaker — capable but more complex |
| Network performance | Google private backbone — lowest global latency | AWS backbone — excellent but smaller |
| Firebase integration | Native — Firestore, Auth, BigQuery export | No Firebase equivalent — separate tools |
| Pricing model (analytics) | BigQuery on-demand — pay per query byte | Redshift — provisioned capacity always running |
Client Stories
What Our Clients Say
"Matlab Infotech migrated our data warehouse to BigQuery. Queries that took 8 hours in Redshift run in 40 seconds. The cost dropped 55% too."
Maria Gonzalez
Head of Data · AnalyticsCo
"Matlab Infotech built our Vertex AI ML pipeline. We went from 3-week manual model deployments to 2-hour automated pipelines. Transformational."
Hiroshi Tanaka
ML Engineering Lead · AIFirst
"Our GKE platform handles 50M API requests per day. Matlab Infotech designed it with Autopilot — zero node management, and our infra bill actually decreased."
Rachel Thomas
Platform Lead · ScaleUp
FAQ
Frequently Asked Questions about GCP
When should I choose GCP over AWS or Azure?
Choose GCP when: (1) BigQuery is your data warehouse — GCP's analytics ecosystem is unmatched, (2) you're building ML/AI-heavy products and want Vertex AI, (3) you already use Firebase and want the native GCP integration, (4) your workload is Kubernetes-heavy (GKE is the most mature), or (5) you need Google's superior global network for low-latency international traffic.
What makes BigQuery different from other data warehouses?
BigQuery is serverless — no cluster provisioning, patching, or vacuuming. You query petabytes of data in seconds, pay per TB scanned (or flat-rate slots), and auto-scale to any workload. Compared to Redshift, BigQuery requires zero maintenance and typically costs less for query-heavy workloads with variable patterns.
What is Vertex AI?
Vertex AI is Google's unified ML platform covering data labelling, training pipelines (with Kubeflow), model registry, feature store, and serving endpoints. It supports custom models (TensorFlow, PyTorch, scikit-learn), AutoML for low-code training, and integrates Gemini API for foundation model use cases.
Is GKE better than EKS or AKS?
GKE consistently introduces Kubernetes features first (it's Google's own project), has the most mature autopilot mode for zero-node-management operation, and has the best bin packing efficiency. For most teams, the choice depends on broader cloud strategy rather than raw Kubernetes capability.
How does Firebase integrate with GCP?
Firebase is a GCP product. Firestore data auto-exports to BigQuery for analytics. Cloud Functions run on GCP infrastructure. Firebase Auth integrates with Google Identity Platform. Cloud Run hosts backend APIs consumed by Firebase apps. The integration is seamless and we frequently build full products on this combined stack.
Can you help with GCP cost management?
Yes. We configure Committed Use Discounts for predictable GKE and Cloud SQL workloads (up to 57% savings), implement BigQuery slot reservations for consistent analytics workloads, use Spot VMs for batch jobs, set Cloud Billing budgets with alerts, and use recommender API to identify underutilised resources.
Related Technologies
Explore technologies we commonly pair with GCP.
Unlock the Power of Google Cloud Platform
Matlab Infotech builds GCP architectures for data-intensive and AI-first products — BigQuery analytics, Vertex AI pipelines, and GKE at scale.
Let's Collaborate
Tell us about your project and we'll come back with a plan, a timeline, and a quote.