资讯与观察· Kubernetes
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The next 10 years of KubeVirt
KubeVirt was founded by Red Hat in 2016 around the idea that Kubernetes could run virtual machines alongside containers. We
Isolation. Security. Scale.
Without these three things, Agents cannot be properly implemented in a controlled environment, they will not have policy enforcement to ensure they do what they’re supposed to do, and there’s zero way of ensuring that t…
19 分钟 · CNCF Blog
Is Kubernetes ready for AI agents?
Kubernetes was built around a fairly simple assumption. It’s that software does what its developers told it to do. AI
15 分钟 · The New StackLATEST STORIES
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Why Kubernetes autoscalers keep fighting each other (and why the solution must be autonomous)精选导读
Ask an SRE a deceptively simple question: What is the right size for checkout-api, and how many replicas should it
Before you expand your GPU pool, measure the outcome精选导读
For teams running AI workloads on Kubernetes, a fully allocated GPU pool and a growing batch-job queue might make expanding
AI jobs are waiting while GPUs sit idle. Kubernetes has a new plan.精选导读
Welcome to another edition of Road to KubeCon! We’re tracking movements in the Kubernetes and cloud-native ecosystem as we count
Multi-tenant GPU Kubernetes on simulated hardware with Kamaji and HAMi精选导读
GPU teams usually face a bad trade-off. Give every team its own Kubernetes cluster and you pay for a control plane per team. Put everyone in one shared cluster and you get weak isolation. Either way,...
Filtering and reducing AI agent telemetry with the OpenTelemetry Collector精选导读
Turn on an AI coding agent’s telemetry and it throws a wall of text at you. It’s expensive to store and what’s worse, you can’t make sense of it. It’s all OpenTelemetry native, though. So you...
Before you evaluate an AI SRE, give your existing agent context精选导读
If you’re evaluating AI SRE products, you probably own most of one already. The coding agent your engineers use, whether that’s Claude Code, Codex or Cursor, can already investigate a Kubernetes cluster. What it usually…
How AI workloads are reshaping Kubernetes autoscaling精选导读
Kubernetes has quietly run much of the world’s containerized software on a division of labor between two control loops that rarely had to talk to each other. The scheduler places each pod on a node that...
Scale isn’t one number: three ways a Kubernetes control plane runs out of room精选导读
Three clusters in trouble, and they look nothing alike. The first is a training fleet. It sat at a few
AI agents vs. Kubernetes: where each belongs in the control loop精选导读
Kubernetes has always relied on agents, just not the kind dominating today’s AI conversations. A controller watches the current state,