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    <title>Slinky on Route179</title>
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    <description>Recent content in Slinky on Route179</description>
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    <copyright>2026 Sheng Chen</copyright>
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      <title>Running Slurm on Kubernetes with Slinky</title>
      <link>https://route179.dev/2026/08/16/slurm-on-kubernetes-with-slinky/</link>
      <pubDate>Sun, 16 Aug 2026 10:00:00 +1000</pubDate>
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      <description>&lt;p&gt;A few weeks ago I built a Slurm GPU cluster &lt;a href=&#34;https://route179.dev/2026/08/03/slurm-qwen-finetune/&#34;&gt;from scratch on bare
EC2&lt;/a&gt; and fine-tuned Qwen3-4B
across two &lt;code&gt;g6.12xlarge&lt;/code&gt; nodes. This post runs the &lt;strong&gt;same&lt;/strong&gt; Slurm fine-tune — but using the
&lt;a href=&#34;https://github.com/SlinkyProject/slurm-operator&#34;&gt;Slinky operator&lt;/a&gt; on Amazon EKS.&lt;/p&gt;
&lt;p&gt;Slinky is an open-source project for running Slurm inside Kubernetes: a Kubernetes operator,
with custom controllers and CRDs, that manages the lifecycle of a Slurm cluster and its &lt;code&gt;NodeSet&lt;/code&gt;s as native
Kubernetes resources. The point is to get the best of both worlds: combining Slurm&amp;rsquo;s
deterministic, fine-grained batch scheduling with Kubernetes&amp;rsquo; dynamic resource
allocation and rapid scaling.&lt;/p&gt;</description>
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