Google Cloud Consulting Services
InterCode architects, migrates, and manages cloud-native infrastructure on Google Cloud Platform. From GKE-based microservices to BigQuery analytics pipelines and serverless backends on Cloud Run, we help startups and SaaS companies leverage the full power of GCP — including Google's world-class ML ecosystem.
Why Google Cloud for Modern SaaS and Data
Google Cloud Platform is the infrastructure of choice for teams that want cloud-native architecture, world-class data tooling, and access to Google's machine learning ecosystem. GKE provides managed Kubernetes with autopilot mode that eliminates node management overhead, while Cloud Run lets teams deploy containerized services that scale to zero and cost nothing when idle. At InterCode, GCP is our cloud of choice for data-intensive and AI-driven applications. BigQuery is Google's crown jewel for analytics — a serverless data warehouse that queries terabytes in seconds without any infrastructure to manage. We build end-to-end data pipelines that land raw events from Pub/Sub, transform them with Dataflow or dbt, and surface insights in Looker or custom dashboards. Vertex AI brings AutoML, custom model training, and model serving into a single managed platform, making production AI deployments faster and more reliable. InterCode helps startups move fast on GCP with its transparent pricing, generous free tiers, and startup credits program. We design architectures that take advantage of GCP's global network, multi-region storage, and Firebase for real-time mobile backends. Whether you are migrating from on-premises or launching greenfield, we ensure your GCP foundation is secure, observable, and cost-optimized from day one.
What We Build on Google Cloud
We architect SaaS platforms on GKE with autoscaling workloads and zero-downtime deployments, build BigQuery analytics pipelines that process millions of events per day, and deploy serverless backends with Cloud Run that cut infrastructure costs by 60%. Our team has migrated on-premises data centers to GCP with zero business disruption, integrated Firebase for real-time mobile backends, and deployed Vertex AI pipelines for production ML models. GCP's Pub/Sub and Dataflow combination is our go-to for event-driven architectures that need guaranteed message delivery and scalable stream processing.
Related Services
Cloud deployment &
Set up scalable, secure, and cost-optimised cloud infrastructure for your application. InterCode provides cloud deployment services, devops services, and managed cloud services — so your engineering team can focus on product features, not infrastructure problems.
Learn moreCloud Migration With Zero Downtime
Move to the cloud without disrupting your business. InterCode plans and executes cloud migrations to AWS, Azure, and GCP that reduce costs, improve scalability, and modernize your infrastructure while keeping your systems running throughout the transition.
Learn moreDevOps Services That Accelerate Delivery
Ship faster, fail less, and recover instantly. InterCode builds DevOps cultures and toolchains that turn manual, error-prone releases into automated, repeatable pipelines delivering value to production multiple times per day.
Learn moreData Engineering for Smarter Decisions
Your data is only as valuable as the infrastructure that moves and transforms it. InterCode builds reliable data pipelines, warehouses, and streaming architectures that turn raw data into the insights your business depends on.
Learn moreFrequently Asked Questions
GCP is strongest for data analytics (BigQuery), Kubernetes (GKE autopilot), and ML workloads (Vertex AI). AWS has the widest service breadth. Azure is best for enterprises already using Microsoft 365 and Active Directory. For startups and SaaS with data or ML requirements, GCP often wins on price and developer experience.
BigQuery is serverless — you pay per query with no cluster to manage. Redshift requires provisioned clusters or serverless capacity, which adds operational overhead. BigQuery's on-demand pricing is excellent for variable workloads, while Redshift can be more cost-effective for consistent high-volume throughput. We evaluate both based on your query patterns and team expertise.
GCP is generally competitive with AWS and often cheaper for compute (sustained use discounts are automatic) and egress within the same region. BigQuery and Cloud Run can be significantly cheaper than AWS equivalents for the right workloads. We run cost modeling before recommending a cloud provider.
Google Kubernetes Engine is a fully managed Kubernetes service backed by Google's own engineers who built Kubernetes. GKE Autopilot mode manages nodes, scaling, and upgrades for you. It offers the most mature managed Kubernetes experience on any cloud, with built-in security policies, workload identity, and binary authorization.
Firebase can replace a backend for apps that need real-time data sync, authentication, push notifications, and simple cloud functions. For complex business logic, custom APIs, or SQL data models, Firebase is better used alongside a dedicated backend. We design Firebase architectures that maximize simplicity while keeping migration paths open.
Start Your GCP Project
Talk to our Google Cloud engineers about your architecture, migration, or data platform. We will scope your requirements and design a GCP solution built for scale.
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