<?xml version="1.0" encoding="UTF-8"?>
<rss xmlns:atom="http://www.w3.org/2005/Atom" version="2.0">
    <channel>
      <title>Alek&#x27;s Blog - continue</title>
      <link>https://blog.none.at</link>
      <description>Production notes on Kubernetes, OpenShift, and OVHcloud: observability, log archiving, service mesh, LLM inference, and digital sovereignty.</description>
      <generator>Zola</generator>
      <language>en</language>
      <atom:link href="https://blog.none.at/tags/continue/rss.xml" rel="self" type="application/rss+xml"/>
      <lastBuildDate>Sat, 27 Jun 2026 00:00:00 +0000</lastBuildDate>
      <item>
          <title>LLM Inference on OVH MKS: Connect IDEs and Web UIs</title>
          <pubDate>Tue, 02 Jun 2026 00:00:00 +0000</pubDate>
          <author>aleks</author>
          <link>https://blog.none.at/blog/2026/2026-06-02-llm-inference-on-ovh-agents/</link>
          <guid>https://blog.none.at/blog/2026/2026-06-02-llm-inference-on-ovh-agents/</guid>
          <description xml:base="https://blog.none.at/blog/2026/2026-06-02-llm-inference-on-ovh-agents/">&lt;p&gt;The first four parts of this series deployed a vLLM inference endpoint at
&lt;code&gt;https:&#x2F;&#x2F;llm.YOUR_DOMAIN&#x2F;v1&lt;&#x2F;code&gt;, protected by a Bearer token, running on an OVH RTX5000-28 GPU node.
This part shows how to connect coding assistants, web UIs, and other OpenAI-compatible clients
to that endpoint.&lt;&#x2F;p&gt;</description>
      </item>
    </channel>
</rss>
