Container/Kubernetes Management
Your Model Works in the Notebook and Breaks in the Cluster
A model working in a notebook gives you a particular kind of confidence. The metrics look good, the code runs top to bottom, the researcher demos it, leadership nods, and everyone agrees ...
Self-Healing Kubernetes Gets Real—and Risky: Running AI Agents on Amazon EKS
For years, “self-healing Kubernetes” meant a liveness probe restarting a crashed pod. In 2026 it means something far more literal: an autonomous agent that reads your cluster’s logs and metrics, forms a ...
Cloud-Native’s Interest Payment Just Came Due
We spent a decade telling each other that cloud-native was how you move fast. Break the monolith into services. Put everything in containers. Declare your infrastructure. Add a service mesh, a GitOps ...
Tigera Introduces Lynx, a Unified Control Plane for Kubernetes‑Native AI Agents
The first Kubernetes AI agent control plane is here. Tigera, best known for backing the open-source Calico networking and security stack for Kubernetes, is pushing beyond traditional container security with the launch ...
Why Kubernetes Cost Allocation and Cloud Bills Don’t Match
A few months ago, I found myself looking at a Kubernetes cost report and a cloud invoice side by side. The numbers didn’t match. Not because of a bug or a calculation ...
When Your Cluster Won’t Sit Still: The Hidden Cost of Kubernetes Autonomy During Incidents
I’ve spent the better part of the last few years on the receiving end of Kubernetes pages, both as an operator and as someone building tooling for platform teams. The pattern I’ve ...
Pod Disruption Budgets: A Field Guide to What Actually Works
In Kubernetes, PodDisruptionBudgets are simple to write, easy to misuse, and cause more “why won’t this node drain?” confusions than any other Kubernetes primitive. After tracing too many node lifecycle automation problems ...
DevZero Launches Automation Platform to Dynamically Rightsize Kubernetes Clusters
DevZero today launched an autonomous infrastructure optimization platform for Kubernetes clusters based on a profiler that continuously monitors clusters, nodes, and individual workloads to build statistical models of demand for resources. Company ...
Stop Wasting GPU Budget: Autoscaling AI Inference on Kubernetes with KEDA
The rush to deploy Large Language Models (LLMs) and generative AI has created a massive infrastructure bottleneck. Platform engineering teams are spinning up expensive GPU node pools on Kubernetes, but they are ...
Ten Years of the Operator Pattern: What We Got Right, What We’d Change
CoreOS introduced the operator pattern in November 2016, and nearly a decade later operators are everywhere. Almost every CNCF graduated project ships one, every database vendor offers one, and every platform team ...
