Build Cloud-Native and AI-Enabled Applications on Google Cloud
Design, migrate and modernize applications on Google Cloud using managed compute, Kubernetes, data and AI services selected around your product and workload requirements.
Use Google Cloud as a Modern Application and Data Platform
Connect cloud-native application delivery with data and AI capabilities.
We help teams map application, data, integration and operational requirements to Google Cloud services. The architecture can combine managed application runtimes, GKE, serverless workloads, managed databases and Vertex AI without forcing every project into the same GCP pattern.
Three benefits.
Cloud-Native Architecture
Data + AI Alignment
Operational Clarity
What We Build
Cloud Applications
Modern web applications and APIs on Google Cloud.
GKE Platforms
Containerized application environments using Google Kubernetes Engine.
Serverless Applications
Event-driven and request-based workloads using managed serverless services.
Data-Driven Products
Applications connected to Google Cloud data and analytics capabilities.
AI Applications
Products using Vertex AI, Gemini and enterprise application data.
Modernized Workloads
Existing applications migrated and replatformed onto Google Cloud.
Google Cloud Application Modernization
Modernize applications so data and AI capabilities become easier to use.
Migration can be a starting point for modernization rather than a simple infrastructure move. We assess application and data dependencies, then choose where managed runtimes, containers, database modernization or AI-ready integration patterns can improve the target platform.
Assess
Migrate
Containerize
Serverless
Modernize Data
Enable AI
Core Google Cloud Capabilities
Capability
GCP Architecture
Supporting copy
Design scalable Google Cloud environments around workload, data and operational requirements.
Capability
Cloud Run
Supporting copy
Deploy containerized applications on a managed runtime with automatic scaling.
Capability
GKE
Supporting copy
Build and operate Kubernetes platforms using Google Kubernetes Engine.
Capability
Cloud Functions / serverless
Supporting copy
Implement event-driven processing and lightweight services without managing dedicated servers.
Capability
Cloud SQL
Supporting copy
Operate managed relational databases for application and transactional workloads.
Capability
Cloud Storage
Supporting copy
Store and deliver files, application assets, backups and unstructured data securely.
Capability
Pub/Sub
Supporting copy
Connect distributed applications through scalable event and messaging workflows.
Capability
API Engineering
Supporting copy
Build secure APIs and integration layers for applications and business systems.
Capability
Terraform
Supporting copy
Provision consistent Google Cloud environments through version-controlled infrastructure definitions.
Capability
CI/CD
Supporting copy
Automate testing, infrastructure provisioning and application deployment across environments.
Capability
Observability
Supporting copy
Monitor application and infrastructure behavior through metrics, logs, traces and alerts.
Capability
Vertex AI
Supporting copy
Integrate managed AI and machine-learning capabilities into applications and data workflows.
How We Deliver
Assess
Understand current applications, data, integrations and cloud requirements.
Architect
Define Google Cloud services, identity, networking, data and deployment patterns.
Build / Migrate
Develop new workloads or migrate existing applications in controlled stages.
Automate
Create repeatable infrastructure and software delivery workflows.
Validate
Test security, performance, integrations and recovery.
Operate & Evolve
Monitor production and evolve cloud, data and AI capabilities as needed.
Ready to Plan the Next Step?
Google Cloud Development Technology Stack
5.0 REVIEWS
Application
Containers
Data
Storage
Integration
Infrastructure
Observability
AI
Vertex AI Application Integration
Model Integration
Connect Vertex AI/Gemini through backend services.
Enterprise Context
Ground applications with approved business data.
RAG
Build retrieval pipelines where knowledge grounding is required.
Structured Outputs
Validate model responses for application use.
Tool Integration
Connect AI to approved APIs and workflows.
Evaluation
Test AI behavior against representative product tasks.
Integrations & Connected Systems
Identity
Google Cloud IAM | enterprise identity
Data
Google Cloud data services | external databases / warehouses
AI
Vertex AI | Gemini
Dev Tooling
GitHub | CI/CD platforms
Enterprise
ERP | CRM | operational APIs
Business APIs
Payments | messaging | document and third-party SaaS APIs
Engagement Model
Security & Governance
Carry identity, data protection and environment boundaries through the GCP architecture.
Identity & Access
Least privilege and role-aware access.
Secrets
Keep credentials out of code and unmanaged configuration.
Data Protection
Protect sensitive data according to workload requirements.
Environment Boundaries
Separate development, staging and production appropriately.
Auditability
Keep useful deployment and operational history.
Recovery
Plan backup, rollback and incident paths according to business impact.
We design cloud access, service identities, secrets, data protection and application authorization according to workload risk. AI-enabled applications also need explicit controls around which data can reach models and which actions AI components are allowed to initiate.
Why Choose Virtual Coders for Google Cloud Development?
"Game-Changing Custom SaaS Solutions – Highly Recommended! Working with Virtual Coders to develop our custom SaaS platform was transformative. Their team grasped our unique needs and delivered a robust solution, greatly enhancing our operations. Their attention to detail and proactive communication made the process smooth and enjoyable. Highly recommended for Australian companies seeking to enhance their software solutions!"
Rick Giesel
Owner, ICT
Why Choose Virtual Coders for Google Cloud Development?
✓Full-stack application + platform engineering perspective.
✓Architecture choices connected to real product and operational requirements.
✓Cloud, DevOps, API, data and integration capability in one delivery team.
✓Incremental modernization rather than unnecessary rewrites.
✓No unsupported certification, compliance or performance claims.
Frequently Asked Questions
Evaluating Google Cloud for Your Application?
We support GCP architecture, application development, migration, GKE/cloud-native engineering, infrastructure automation and Vertex AI integration.
Yes. We assess application and data dependencies before selecting rehosting, replatforming or modernization approaches.
Yes. GKE can be used for workloads that benefit from Kubernetes orchestration, portability and cloud-native operational patterns.
Yes. Cloud Run can be suitable for containerized web, API and event-driven workloads that benefit from a managed serverless runtime.
Yes. We can integrate model capabilities with applications, enterprise data, RAG, APIs and workflow controls.
Yes. Infrastructure as Code can be used to create repeatable Google Cloud environments and deployment workflows.
Yes. Application modernization often requires changes to databases, storage, data integration and analytics pathways, which should be planned together.
We consider workload architecture, operational requirements, scaling, portability, team skills and the level of orchestration actually required.
SEND US A MESSAGE.
READY TO ACCELERATE YOUR TECH JOURNEY?
Partner with our expert engineers to transform your ideas into scalable, high-performance solutions tailored to your business needs.
OUR OFFICES
India
E-414 to 416, Ganesh Glory 11, Jagatpur Road, Nr. BSNL Office, off. S.G. Highway, Jagatpur, Ahmedabad, Gujarat - 382470
Australia
18, Giancarlo Crescent, Doolandella-4077, QLD, Australia
Canada
20 Meadowglen Pl, Toronto, ON M1H 2Y5