<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Interoperability on CuraDevOps</title><link>https://curadevops.metacog.co.kr/tags/interoperability/</link><description>Recent content in Interoperability on CuraDevOps</description><generator>Hugo</generator><language>en-us</language><lastBuildDate>Wed, 12 Aug 2026 11:40:52 +0000</lastBuildDate><atom:link href="https://curadevops.metacog.co.kr/tags/interoperability/index.xml" rel="self" type="application/rss+xml"/><item><title>CNCF: Docker and ModelPack push AI model interoperability</title><link>https://curadevops.metacog.co.kr/insights/2026-08-12-advancing-ai-model-interoperability-with-docker-and-modelpac/</link><pubDate>Wed, 12 Aug 2026 11:40:52 +0000</pubDate><guid>https://curadevops.metacog.co.kr/insights/2026-08-12-advancing-ai-model-interoperability-with-docker-and-modelpac/</guid><description>&lt;ul>
&lt;li>&lt;strong>Platform/SRE — Learn:&lt;/strong> Early-stage standards work around packaging and running AI models may eventually affect platform infrastructure choices, but nothing here is GA or operationally actionable today.&lt;/li>
&lt;li>&lt;strong>CI/CD — Skip&lt;/strong>&lt;/li>
&lt;li>&lt;strong>Leader — Learn:&lt;/strong> A CNCF-backed push for AI model interoperability is worth tracking as an emerging standard that could influence build-vs-buy decisions for AI workload platforms in future planning cycles.&lt;/li>
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