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
Build on infrastructure that scales. Code Huddle designs cloud-native architectures that start lean and grow with your business — without costly refactors down the road.
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