Cloud Architecture Design
AWS, Azure, or GCP architecture designed for your workload. We prioritize managed services, auto-scaling, multi-AZ reliability, and cost optimization from the start.
Specialized service
Cloud-Native Development & Infrastructure
Code Huddle designs and runs cloud infrastructure on AWS, Azure and GCP: Terraform, Docker and Kubernetes, CI/CD pipelines, monitoring and cost optimization. We run the platforms we build, including multi-tenant SaaS such as ParkingHub and AWS-native data platforms such as Ensemble – Flux Foundry.
AWSAzureGCPDockerKubernetesTerraformServerless
Capability map
What we design, build, and improve
Code Huddle's cloud and DevOps engineers design infrastructure that is scalable, cost-efficient, and maintainable. We specialize in cloud-native architectures using AWS (preferred), Azure, and GCP — with Infrastructure as Code via Terraform, container orchestration with Kubernetes, and automated CI/CD pipelines for zero-downtime deployments.
Docker & Kubernetes
Containerize your applications with Docker and orchestrate at scale with Kubernetes (EKS, AKS, GKE). Helm charts, horizontal pod autoscaling, and rolling deployments.
Infrastructure as Code (Terraform)
Define your entire cloud infrastructure in Terraform. Version-controlled, repeatable, and auditable infrastructure with Terragrunt for multi-environment management.
Serverless Computing
Cost-efficient event-driven architectures using AWS Lambda, Azure Functions, or Google Cloud Functions. Pay only for what you use — ideal for APIs, background jobs, and webhooks.
Microservices Architecture
Decompose monoliths into independently deployable services. API Gateway, service mesh (Istio), inter-service communication, and distributed tracing with Jaeger.
DevOps Automation & Monitoring
CI/CD pipelines, GitOps workflows with ArgoCD, infrastructure monitoring with Prometheus/Grafana, log aggregation with ELK stack, and 24/7 alerting.
Delivery model
A visible path from uncertainty to production
- 01
Frame the decision
Clarify the user outcome, commercial goal, constraints, inherited systems, and unknowns worth testing first.
- 02
Design the system
Shape the experience, architecture, integrations, release boundary, acceptance criteria, and operating model.
- 03
Ship with evidence
Deliver reviewable increments with testing, demonstrations, production telemetry, documentation, and handover.
Commercial model
Scope and cost follow uncertainty
Defined outcomes can use milestones. Evolving products are usually better served by transparent team capacity. Estimates follow discovery of workflows, integrations, constraints, and acceptance criteria.
Engineering judgment
Tradeoffs stay explicit
Build versus buy, delivery speed, operating cost, security, maintainability, migration, and technical ambition are discussed as product decisions—not hidden implementation details.
Where this fits
Common product situations
- 01Cloud migration from on-premises
- 02Setting up cloud infrastructure for new product
- 03Kubernetes migration from bare-metal
- 04DevOps pipeline for existing engineering team
- 05Cost reduction audit for existing cloud setup
- 06Compliance-ready infrastructure (SOC 2, HIPAA)
Technology choices
Selected for the system—not the trend
The final stack follows product constraints, team capability, integration boundaries, security, scale, and long-term ownership.
AWSAzureGCPDockerKubernetesTerraformTerragruntHelmGitHub ActionsArgoCDPrometheusGrafanaELK StackIstioAWS LambdaCloudflare
Evidence related to Cloud & DevOps
Explore product stories with related architecture, workflows, and delivery decisions.
Questions before starting
The details buyers usually need
We recommend AWS for most new projects due to its breadth of managed services, global reach, and mature ecosystem. Azure is preferred for Microsoft-heavy enterprises, and GCP for AI/ML-intensive workloads (TPUs, Vertex AI). We are cloud-agnostic and can work with any provider.
Yes — cloud cost optimization is a common engagement. We audit your AWS, Azure or GCP spending, identify waste (idle instances, over-provisioned databases, inefficient data transfer), and implement rightsizing, reserved capacity or savings plans, and autoscaling. You get a report of each change and its measured effect on the monthly bill.
Plan your project
Practical questions and scope decisions before you commission a build.
Slow Web App? A Performance Checklist Before Upgrading HostingDiagnose a slow web app before upgrading hosting: measure user journeys, database queries, connection pools, payloads, background jobs, and caching.Software project handover: a checklist for changing development teamsPlan a software handover: repository access, deployments, data ownership, integration accounts, tests, operating costs, and release responsibilities.How to Choose a Tech Stack for Your Web App and the Mistakes to AvoidLearn how to choose the right tech stack for your web app. Compare frontend, backend and database options, and avoid costly mistakes.How to Deploy a NestJS App to AWS EC2 with GitHub Actions (Without Building on the Server)Build NestJS in GitHub Actions, ship a ready-to-run archive to EC2, reload with PM2, and roll back automatically if a health check fails.The AI-Powered Developer Workflow: From Planning to Code Review and DeploymentUse AI across your whole development process without shipping wrong code. A 6-stage workflow for planning, coding, testing, code review and deployment.Your App Works Locally. What Changes When You Take It to Production?A practical checklist for moving from “works on my machine” to production: environments, databases, integrations, networks, failure handling, security, and launch readiness.