Services

Cloud & Kubernetes Architecture

AI-ready infrastructure. GPU orchestration. Zero-Trust by default.

KubernetesAPISIXKeycloakAKSGCPHetznerOpenWhiskvLLMVeleroGrafana

Capabilities

What we build

GPU Orchestration

Kubernetes cluster with custom runtime for AI workloads on AKS, GCP, and Hetzner bare-metal. Sizing optimized for LLM inference.

API Gateway APISIX

JWT plugins, rate-limiting for LLM calls, multi-tenant routing, CORS managed at gateway level. Security layer before code.

Serverless AI

Apache OpenWhisk on Kubernetes for intermittent AI workloads: scale-to-zero, GPU tasks, image processing, batch inference.

Full Stack Deploy

Redis, RabbitMQ, MinIO, Grafana, Velero, Airflow, n8n — complete stack orchestrated with multi-environment CI/CD.

Zero-Trust Security

Keycloak + APISIX as integrated security layer. No service exposed without authentication. Suitable for healthcare and financial data.

Disaster Recovery

Velero for automatic Kubernetes backup. Multi-region strategies on EU cloud for business continuity.

FAQ

Frequently asked questions

How do you securely deploy an LLM on Kubernetes?

Secure LLM deployment on Kubernetes requires: isolated namespaces, network policies, OIDC authentication via Keycloak, rate-limiting at APISIX level, and a dedicated GPU node pool. Nexus MDS Core implements this stack in a single-command configuration.

What is the difference between AKS, GCP GKE, and Hetzner for AI workloads?

AKS and GKE offer native integration with cloud services (storage, IAM, monitoring) but at high GPU costs. Hetzner bare-metal offers H100/A100 GPUs at 3-5x lower costs but requires infrastructure management. The choice depends on budget, compliance (EU data residency), and team operational capacity.