Page 3 — Technical articles on Kubernetes, K3s, and Proxmox
Kubernetes high availability isn't achieved simply by adding more replicas. Using the broadcast industry's SMPTE ST 2022-7 dual-path transmission as a lens, this article unpacks what Topology Spread Constraints and multi-AZ design actually mean.
The quality-gate mindset and test automation skills QA engineers already have map directly onto Kubernetes operations aptitude. Here's a realistic six-month roadmap for making the switch, and how to clear the biggest obstacle in the way.
Generating Kubernetes manifests at AI speed doesn't make production Kubernetes operations faster. This article breaks down three real bottlenecks — CPU throttling, the HPA/VPA conflict, and database connection starvation — and how to split the work between AI and humans.
Shadow AI isn't just unauthorized SaaS tools. It's happening inside your Kubernetes clusters too. Here's the risk it creates, and how Admission Control turns detection into real governance.
An explainer on the relationship between platform engineering and Kubernetes — the design philosophy of shielding developers from K8s complexity, the three pillars of building an IDP, and managed K3s as an alternative.
Most production incidents happen because teams deploy everything at once. This article walks through how to design canary releases, automated rollback, and monitoring on Kubernetes using Argo Rollouts and GitOps — with practical steps small teams can actually sustain.
As VMware migration costs and cloud bills climb in 2026, more companies are reconsidering private cloud. This article examines the real build cost and Day 2 operational burden of self-managed OpenStack + K3s, using actual operational data and industry statistics, to clarify when in-house builds make sense versus a managed Kubernetes service.
As AI automates infrastructure, are DevOps engineers really becoming irrelevant? The reality is the opposite — demand for MLOps Kubernetes talent is surging. Here are the 5 skills you need in 2026.
CNCF's 2026 survey shows 66% of GenAI organizations run on Kubernetes. From GPU scheduling to multi-tenancy and cost optimization — here's why K8s has become the de facto AI platform, and how managed K8s can cut your build time to zero.
What is the 'stage-skipping trap' that DevOps engineers fall into? A comprehensive guide to why Managed Kubernetes is the optimal solution, explained through infrastructure evolution theory