Cloud technologies at Neoteric

How we design and run cloud-native systems that are secure, scalable and optimised for cost and performance on AWS, Azure and GCP.

M
MaheshDeveloper
5 min read

Cloud is an operating model, not a data centre

Lifting servers into a cloud account rarely saves money or improves reliability. The benefit arrives when the platform is designed around elasticity, automation and managed services. We design for the cloud from the architecture up: stateless services, managed databases, event-driven integration and infrastructure that is created from code, never by hand.

Everything as code

Every environment we run is described in Terraform and versioned alongside the application. Pull requests to infrastructure are reviewed like application code, and environments are created and destroyed on demand for testing. GitOps with Argo CD keeps Kubernetes clusters in sync with the repository so drift is visible and reversible.

If it is not in the repository, it does not exist. That rule has saved more weekends than any monitoring tool.

Kubernetes where it earns its place

Containers give us consistent builds and predictable deployments. We run Spring Boot services on managed Kubernetes (EKS, AKS, GKE) with horizontal pod autoscaling tied to real signals such as queue depth and p95 latency, not just CPU. For smaller workloads we deliberately avoid Kubernetes and use serverless containers or functions where the operational overhead is not justified.

Security and compliance from day one

Least-privilege IAM, private networking, encrypted storage and secrets in a managed vault are defaults, not add-ons. Pipelines scan images and dependencies on every build. For clients in finance and healthcare we map controls to their audit requirements early so compliance evidence is generated automatically rather than assembled in a panic before an audit.

Cost as a first-class metric

We tag every resource, set budgets per environment and review spend with the client monthly. Rightsizing, spot capacity for stateless workloads, scheduled scale-to-zero for non-production and storage lifecycle policies routinely cut bills by 30–50% without touching the application. Observability (OpenTelemetry traces, structured logs, SLO dashboards) tells us where to optimise next.

Key takeaways
  • Design for elasticity and managed services rather than lift-and-shift.
  • Terraform and GitOps make every environment reproducible.
  • Autoscale on business signals, not just CPU.
  • Security controls and cost budgets are built in, reviewed monthly.
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