<?xml version="1.0" encoding="UTF-8"?>
<rss xmlns:dc="http://purl.org/dc/elements/1.1/" version="2.0">
  <channel>
    <title>InfoQ - Scaling</title>
    <link>https://www.infoq.com</link>
    <description>InfoQ Scaling feed</description>
    <item>
      <title>Uber Separates Scaling Intent From Execution on Kubernetes Platform</title>
      <link>https://www.infoq.com/news/2026/09/uber-kubernetes-scaling/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Scaling</link>
      <description>&lt;img src="https://res.infoq.com/news/2026/09/uber-kubernetes-scaling/en/headerimage/generatedHeaderImage-1790360989750.jpg"/&gt;&lt;p&gt;Uber has published a detailed account of its new ServiceScale controller, which allows multiple orchestrators to safely manage the scaling of the same Kubernetes workloads. The blog post, written by senior software engineers Egor Grishechko and Srikar Paruchuru, describes how the company separated scaling intent from execution to support regional failover without carrying reserved idle capacity.&lt;/p&gt; &lt;i&gt;By Matt Saunders&lt;/i&gt;</description>
      <category>Scaling</category>
      <category>Kubernetes</category>
      <category>DevOps</category>
      <category>news</category>
      <pubDate>Mon, 28 Sep 2026 09:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/09/uber-kubernetes-scaling/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Scaling</guid>
      <dc:creator>Matt Saunders</dc:creator>
      <dc:date>2026-09-28T09:00:00Z</dc:date>
      <dc:identifier>/news/2026/09/uber-kubernetes-scaling/en</dc:identifier>
    </item>
    <item>
      <title>Presentation: Adaptive Recommenders in the Real World: Inference, Evals, and System Design</title>
      <link>https://www.infoq.com/presentations/adaptive-recommendation-systems-architecture/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Scaling</link>
      <description>&lt;img src="https://res.infoq.com/presentations/adaptive-recommendation-systems-architecture/en/mediumimage/mallika-medium-1789632229433.jpeg"/&gt;&lt;p&gt;Mallika Rao explains that the true complexity of adaptive recommendation systems lies outside model architecture. She discusses how real-time feedback loops, retrieval freshness, multi-stage orchestration, and end-to-end latency budgeting enable systems to continuously learn and evolve in production under real-world operational constraints like latency, cost, and observability.&lt;/p&gt; &lt;i&gt;By Mallika Rao&lt;/i&gt;</description>
      <category>Data</category>
      <category>Scaling</category>
      <category>Performance</category>
      <category>Transcripts</category>
      <category>Observability</category>
      <category>QCon AI Boston 2026</category>
      <category>Machine Learning</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>Development</category>
      <category>Architecture &amp; Design</category>
      <category>presentation</category>
      <pubDate>Sat, 26 Sep 2026 11:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/presentations/adaptive-recommendation-systems-architecture/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Scaling</guid>
      <dc:creator>Mallika Rao</dc:creator>
      <dc:date>2026-09-26T11:00:00Z</dc:date>
      <dc:identifier>/presentations/adaptive-recommendation-systems-architecture/en</dc:identifier>
    </item>
    <item>
      <title>Stateless MCP Removes Session Affinity Requirements for AWS Server Deployments</title>
      <link>https://www.infoq.com/news/2026/09/aws-stateless-mcp/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Scaling</link>
      <description>&lt;img src="https://res.infoq.com/news/2026/09/aws-stateless-mcp/en/headerimage/generatedHeaderImage-1788807776891.jpg"/&gt;&lt;p&gt;AWS details how the latest Model Context Protocol specification removes protocol-level sessions, sticky-session requirements, and session storage for remote MCP servers. The change enables independent request routing and simpler horizontal scaling while shifting application state, retries, observability, and idempotency concerns to other layers.&lt;/p&gt; &lt;i&gt;By Leela Kumili&lt;/i&gt;</description>
      <category>Deployment</category>
      <category>Scaling</category>
      <category>Load Balancing</category>
      <category>OpenTelemetry</category>
      <category>Distributed Systems</category>
      <category>AWS Lambda</category>
      <category>AWS</category>
      <category>Serverless</category>
      <category>Microservices</category>
      <category>Observability</category>
      <category>W3C</category>
      <category>Frameworks</category>
      <category>Model Context Protocol (MCP)</category>
      <category>AI Architecture</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>Architecture &amp; Design</category>
      <category>Development</category>
      <category>news</category>
      <pubDate>Fri, 25 Sep 2026 12:58:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/09/aws-stateless-mcp/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Scaling</guid>
      <dc:creator>Leela Kumili</dc:creator>
      <dc:date>2026-09-25T12:58:00Z</dc:date>
      <dc:identifier>/news/2026/09/aws-stateless-mcp/en</dc:identifier>
    </item>
  </channel>
</rss>
