Complete AI Platform Tech Stack Explained Kubernetes, CI CD, Observability & GPU Infrastructure

Description

“Want to understand how modern AI platforms are built in production? In this video, we break down a complete technology stack used for building scalable, secure, and observable AI systems on Kubernetes. From containerization and GitOps to GPU inference, observability, and CI/CD pipelines — this is a real-world architecture used in cloud-native environments. What you’ll learn: Container Runtime (Docker, containerd, BuildKit) Kubernetes (EKS, AKS, GKE) GitOps with ArgoCD & Argo Rollouts Event-driven scaling using KEDA GPU support and inference servers (vLLM, Triton, TGI) Observability stack (Prometheus, Grafana, Jaeger, OTEL) CI/CD pipeline with GitHub Actions Security, networking, and storage layers This video is perfect for: DevOps Engineers Cloud Engineers AI/ML Engineers Kubernetes beginners & professionals If you found this helpful, don’t forget to like, share, and subscribe for more deep dives into cloud-native and AI infrastructure.