Kubernetes & AI Infrastructure,
Built from real-world production experience.
Deep-dive content on Kubernetes at scale, GPU clusters, distributed training, and the real engineering behind production AI systems. No fluff. No slides-only talks.
Blog
Latest Articles.
Why Kubeflow Trainer Exists: The Journey from Single GPU Training to Distributed AI on Kubernetes
Understand the evolution from single GPU training to PyTorch DDP and discover why Kubernetes needs Kubeflow Trainer to orchestrate distributed AI workloads.
How One Expired Certificate Quietly Stopped an Entire Kubernetes Control Plane
A real production incident that explains how one expired API server certificate silently stopped Kubernetes reconciliation and brought an entire control plane to a halt.
Scaling LLM Inference on Kubernetes: Why Your Pods Take 30 Minutes to Start (And How to Fix It)
# Scaling LLM Inference on Kubernetes: Why Your Pods Take 30 Minutes to Start (And How to Fix It)
Understanding How Kubernetes Supports GPUs
Learn how Kubernetes discovers, schedules and exposes GPUs to containers, and why components like the Device Plugin and GPU Operator are essential for running AI workloads.
GPU Architecture Explained: How Modern GPUs Execute AI Workloads
A practical guide to modern GPU architecture, explaining how Streaming Multiprocessors, CUDA Cores and Tensor Cores work together to execute AI workloads.
Understanding the GPU Memory Hierarchy
Explore the GPU memory hierarchy, from registers to HBM, and learn how each level of memory impacts GPU performance.
Latest videos
Watch & Learn.
Everything That Happens to Secure an App Before It Reaches Kubernetes
In this video, I walk through how a senior DevOps/Platform engineer would secure an application from a developer machine all the way to a Kubernetes cluster. We cover: ✅ Developer workstation security ✅ Git and source control security ✅ CI/CD pipeline security ✅ Container image scanning ✅ Registry security ✅ Kubernetes RBAC ✅ Secrets management ✅ Network policies This is a common senior DevOps and platform engineering interview question and a real-world approach used in modern cloud-native environments. #DevOps #Kubernetes #DevSecOps #PlatformEngineering #CloudSecurity #Docker #AWS
Jun 16, 2026
Linux Process Isolation Explained | cgroups, Namespaces & Docker
In this video, you’ll learn what process isolation is in Linux and how it’s achieved using cgroups and namespaces. We’ll also explore how Docker uses these Linux features under the hood to run containers. We’ll start by examining how processes look when there’s no isolation and everything runs on the same host. Then, we’ll compare that to running each application on its own server, and finally, how multiple apps can run on the same host but remain isolated from each other. At the end of the video, we’ll do some hands-on experiments to see what gets created when a Docker container spins up giving you a clear picture of how containerisation really works.
Sep 15, 2025
How to Build a Kubernetes Cluster with kubeadm and Cilium CNI (Beginner-Friendly Tutorial)
Learn how to create a Kubernetes cluster from scratch using kubeadm and install Cilium as your Container Network Interface (CNI), replacing kube-proxy and unlocking powerful eBPF-based networking. This step-by-step tutorial walks you through provisioning AWS infrastructure, installing Kubernetes components, configuring Cilium, and deploying a sample application to verify the setup. What You’ll Learn in This Tutorial - How to create a VPC in AWS to build an isolated Kubernetes environment - Setting up Security Groups for master and worker nodes - Provisioning 3 EC2 instances (1 Control Plane + 2 Worker Nodes) - Installing kubeadm, kubelet, kubectl, and required components on each node - Initializing the Kubernetes control plane using kubeadm - Joining all worker nodes to the cluster - Installing Cilium CNI as the networking layer (and kube-proxy replacement) - Deploying a test application to confirm everything is working correctly. Links: - kubernetes docs for kubeadm installation: https://kubernetes.io/docs/setup/production-environment/tools/kubeadm/install-kubeadm/ - kubernetes docs for creating the cluster: https://kubernetes.io/docs/setup/production-environment/tools/kubeadm/create-cluster-kubeadm/ - Containerd Installation guide: https://docs.docker.com/engine/install/ubuntu/ - Cillium docs and installation: https://docs.cilium.io/en/stable/gettingstarted/k8s-install-default/ Follow me on other social media: TikTok: https://www.tiktok.com/@barilonofficial Instagram: https://www.instagram.com/barilonofficial/ LinkedIn: https://www.linkedin.com/in/isrealurephu/
Dec 8, 2025
The person behind it
About
I'm a Senior Platform Engineer with over 5 years of experience designing and operating large-scale Kubernetes platforms in production. I currently manage a bare-metal Kubernetes cluster hosting more than 500 microservices across 30+ engineering teams and operate GPU infrastructure for vLLM inference and distributed AI training workloads.
Over the years, I've worked closely with AI and machine learning engineers to understand the challenges of building, deploying, and operating AI infrastructure at scale. That experience has deepened my expertise in GPU infrastructure, Kubernetes, and the systems that power modern AI workloads.
I'm also an AWS Community Builder and hold all five CNCF Kubestronaut certifications.
Barilon is where I document what I'm building, operating, and learning—no slides-only content or theory disconnected from practice. Most of what I share comes from real production systems I work on, while the rest is based on hands-on experiments, home lab projects, and deep dives into technologies I'm actively exploring.