Product
GKE Kubernetes Deployments
Google Kubernetes Engine cluster management with Autopilot mode, workload identity, and Cloud Armor for containerised Django, Node, and batch workloads.
Google Cloud Platform — The Optimal Cloud for AI, Data, and Modern Applications
We design and manage GCP infrastructure — from GKE Kubernetes clusters and Cloud Run serverless to BigQuery analytics and Vertex AI for AI/ML workloads.
20+ GCP environments managed | GKE, Cloud Run, BigQuery, Vertex AI, Terraform
- Projects delivered
- 0+
- Clients worldwide
- 0+
- Client satisfaction
- 0%
- Avg first response
- <0h
Projects delivered
Clients worldwide
Client satisfaction
Avg first response
WHY CODEFLAMME
- Production-grade architecture from day one
- TypeScript, testing, and accessibility built in
- Dedicated engineers — no freelancers or hand-offs
- NDA protected | reply within 24 hours
RESPONSE TIME
< 24h
We reply to every inquiry within one business day with a structured plan.
What We Build
What We Build With Google Cloud Platform
Production applications across product types — scoped to your users, stack, and growth stage.
6 product types — compare what we ship with Google Cloud Platform in production.
- Platform
Cloud Run Serverless
Fully managed serverless containers on Cloud Run for APIs, microservices, and event-driven workloads with automatic scaling to zero when traffic is idle.
- SaaS
BigQuery Data Warehousing
BigQuery schema design, partitioning, clustering, materialised views, and cost-aware analytics queries for product and operations reporting.
- Commerce
Vertex AI & ML Pipelines
Vertex AI training pipelines, model registry, model endpoints, and AutoML for production ML model training and serving.
- Internal
Firebase Integration
Firebase Realtime Database, Firestore, Authentication, Cloud Messaging, and Hosting for mobile-backend and real-time web applications.
- Design
GCP Data Engineering
Pub/Sub, Dataflow, Dataproc, and Cloud Composer (Airflow) for real-time and batch data processing pipelines.
WHY CODEFLAMME
Not Another Offshore Vendor
We know the hesitation. Here's exactly how we're different.
You Talk to the People Building It
No account managers relaying messages. You're in direct contact with the founder and senior engineers on your project — every sprint, every decision.
No Bench Rotation
The team that scopes your project is the team that ships it. We don't swap engineers mid-project to free them up for someone else.
NDA Before We Talk Details
Your idea and IP are protected from the first real conversation — not after contracts are signed.
Full IP, Zero Strings
Every line of code, every design file, transfers to you on delivery. No licensing, no retained rights, no surprises.
Our Capabilities
Our Google Cloud Platform Development Services
Core delivery areas for Google Cloud Platform — architecture, implementation, and production hardening.
- 01
GCP Architecture Design
VPC, subnet, and firewall design with Cloud Armor, Cloud NAT, and Private Service Connect for secure GCP deployments.
- 02
Terraform for GCP
GCP resource provisioning with Terraform — version controlled, modular, and consistent across development, staging, and production.
- 03
IAM & Org Policies
GCP IAM bindings, custom roles, Organisation Policies, and VPC Service Controls for enterprise security and compliance.
- 04
Cloud Monitoring & Logging
Cloud Monitoring dashboards, log-based metrics, uptime checks, and alerting policies for production GCP applications.
- 05
Cost Management
GCP committed use discounts, sustained use discount analysis, budget alerts, and recommender API for cost optimisation.
- 06
CI/CD with Cloud Build
Cloud Build trigger configuration, artifact registry, and deployment pipelines integrated with GitHub or GitLab.
When to Choose
When Google Cloud Platform Is the Right Choice
Decision scenarios where Google Cloud Platform is the strongest fit — and why it earns the recommendation.
SCENARIO 01
Primary use case
Your product is AI/ML-heavy
GCP's Vertex AI, TPU access, BigQuery ML, and tight integration with Google Research makes it the strongest cloud for AI/ML production workloads.
02
Scenario
You process large amounts of data
BigQuery is a strong managed warehouse for interactive analytics on very large datasets — especially when product and analytics teams share the same GCP project estate.
03
Scenario
You use Firebase
Firebase runs on GCP infrastructure — building your application backend on GCP alongside Firebase reduces cross-cloud latency and simplifies data movement.
04
Scenario
You need serverless-first architecture
Cloud Run provides a clean serverless container path — deploy a Docker image and Google manages scaling, including scale-to-zero for bursty APIs.
In Practice
How We Use Google Cloud on Real Builds
GCP patterns we ship for apps and data, when GCP is the better cloud, and how Django and containers plug in.
GCP work covers app hosting and data platforms: GKE or Cloud Run for containerised APIs, Cloud SQL for Postgres, Pub/Sub for async edges, and BigQuery or Vertex when analytics and ML are in scope. Terraform keeps projects and IAM consistent; Cloud Build or GitHub Actions handles image promotes.
GCP leads when BigQuery, Vertex AI, Firebase, or Cloud Run are central. AWS wins for the broadest enterprise catalogue; Azure when Microsoft identity dominates. We commonly run Django and Node services as containers on GKE or Cloud Run, with Docker images and DevOps practices for networking, secrets, and observability.
CodeFlamme builds often combine Cloud Run for request APIs with Pub/Sub workers for exports, plus Secret Manager and Workload Identity so app code never holds long-lived keys. Observability lands in Cloud Monitoring with the same alert ownership model we use on other clouds.
- 01
Docker / Kubernetes
GKE Autopilot or standard clusters host multi-service products; Cloud Run covers simpler container APIs that benefit from scale-to-zero.
- 02
Python / Django
Django APIs and workers are a common GCP pairing — Cloud Run or GKE for compute, Cloud SQL for Postgres, and GCS for media.
- 03
DevOps & Cloud
GCP landing projects, IaC, CI/CD, and managed operations are delivered through our DevOps and cloud practice.
Complementary Stack
The Stack We Use Alongside Google Cloud Platform
The tools we pair with Google Cloud Platform in production — organised by layer, not hype.
LAYERS
06
TOOLS
41
04
STACK_LAYER
Storage
FAQ
Frequently Asked Questions
Can't find what you need? Talk directly with our team.
Book a Discovery CallGCP for AI/ML workloads, BigQuery analytics, or Firebase-connected products. AWS for the broadest service catalogue, enterprise compliance tooling, and the largest support ecosystem.
Ready to build something powerful?
Tell us what you are building. We will respond within 24 hours with a clear, honest assessment — no pressure, no sales pitch.
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