AI/ML SaaS Startup AI/ML platform engineering

AI Startup GPU Kubernetes Platform

Industry
AI/ML
Solutions
1 Services
Technologies
10+ Tools

The Challenge

AI startup needed production Kubernetes infrastructure on Vultr with managed GPU nodes for machine learning workloads. Existing PHP application needed containerization and modern CI/CD. No security scanning or image signing in place. Required fast iteration for AI model training and deployment.

What We Built

Provisioned Kubernetes cluster on Vultr with GPU node pools using Terraform
Containerized legacy PHP application and built Docker images
Implemented GitHub Actions pipelines: build, test, scan, deploy
Integrated Trivy for vulnerability scanning in build and runtime
Set up image signing and verification with Sigstore
Deployed Prometheus + Grafana for GPU utilization monitoring
Configured autoscaling for GPU workloads based on demand
Created CI/CD workflow for ML model deployments

Technology Stack

Kubernetes Vultr GPU Nodes Terraform GitHub Actions PHP Docker Trivy Sigstore Prometheus Grafana

Security & Compliance

  • Container images scanned for vulnerabilities before deployment
  • All images cryptographically signed with Sigstore
  • Secrets stored in external secrets operator (AWS Secrets Manager)
  • GPU workloads isolated with Kubernetes namespaces and RBAC
  • Runtime security monitoring for anomalous GPU usage

The Results

Production Kubernetes platform with GPU support live in 5 weeks

PHP application modernized and containerized

CI/CD pipelines reduced deployment time from hours to minutes

100% of container images signed and verified

Cost-optimized GPU autoscaling saved 40% on infrastructure spend

Why catdev?

AI startups need specialized infrastructure expertise—GPU orchestration, cost optimization, and fast iteration cycles. catdev delivered a platform that handled GPU workloads efficiently while maintaining security standards that would scale with the company's growth and eventual SOC2 certification.

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