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      <title>CSIRO Uses Serverless Architecture to Query 100x More Genomic Variants on AWS</title>
      <link>https://www.infoq.com/news/2026/10/csiro-serverless-genomic-variant/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Scalability</link>
      <description>&lt;img src="https://www.infoq.com/styles/static/images/logo/logo_bigger.jpg"/&gt;&lt;p&gt;CSIRO has developed Serverless Beacon, a serverless architecture for querying genomic variants without copying VCF files into a central database. The system combines Amazon S3, Lambda, Athena and DynamoDB, using metadata indexes and HTTP byte range requests to query compressed genomic regions. Tests reported 1.52 second average latency for 10,000 base pair queries.&lt;/p&gt; &lt;i&gt;By Leela Kumili&lt;/i&gt;</description>
      <category>Scalability</category>
      <category>AWS Lambda</category>
      <category>Serverless</category>
      <category>Cost Optimization</category>
      <category>S3</category>
      <category>Applied Research</category>
      <category>Distributed Systems</category>
      <category>Architecture</category>
      <category>AWS</category>
      <category>Distributed Query</category>
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      <pubDate>Fri, 23 Oct 2026 14:30:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/10/csiro-serverless-genomic-variant/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Scalability</guid>
      <dc:creator>Leela Kumili</dc:creator>
      <dc:date>2026-10-23T14:30:00Z</dc:date>
      <dc:identifier>/news/2026/10/csiro-serverless-genomic-variant/en</dc:identifier>
    </item>
    <item>
      <title>Article: Distributed Spring Batch without a Message Broker</title>
      <link>https://www.infoq.com/articles/spring-batch-without-broker/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Scalability</link>
      <description>&lt;img src="https://res.infoq.com/articles/spring-batch-without-broker/en/headerimage/Distributed-Spring-Batch-Without-a-Message-Broker-header-1792419294298.jpg"/&gt;&lt;p&gt;Distributed Spring Batch partitioning already needs a shared, persistent job repository. This article makes that database the whole coordination plane and drops the message broker, sizing work to the live node count, a per-job master with no standing coordinator, compare-and-set claiming that prevents double-execution, two-phase heartbeat failover, and where a broker is still the right choice.&lt;/p&gt; &lt;i&gt;By Janardhan Reddy Chejarla&lt;/i&gt;</description>
      <category>Java</category>
      <category>Spring Batch</category>
      <category>Distributed Systems</category>
      <category>Data Partitioning</category>
      <category>Messaging</category>
      <category>Architecture &amp; Design</category>
      <category>Development</category>
      <category>article</category>
      <pubDate>Wed, 21 Oct 2026 09:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/articles/spring-batch-without-broker/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Scalability</guid>
      <dc:creator>Janardhan Reddy Chejarla</dc:creator>
      <dc:date>2026-10-21T09:00:00Z</dc:date>
      <dc:identifier>/articles/spring-batch-without-broker/en</dc:identifier>
    </item>
    <item>
      <title>GitHub Actions Runner Controller 0.15.0 Targets Reliability at Scale</title>
      <link>https://www.infoq.com/news/2026/10/github-runner-controller-0-15/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Scalability</link>
      <description>&lt;img src="https://res.infoq.com/news/2026/10/github-runner-controller-0-15/en/headerimage/generatedHeaderImage-1791971221854.jpg"/&gt;&lt;p&gt;GitHub has released Actions Runner Controller (ARC) 0.15.0, introducing reliability, scalability, and observability improvements for organisations running self-hosted GitHub Actions runners on Kubernetes.&lt;/p&gt; &lt;i&gt;By Craig Risi&lt;/i&gt;</description>
      <category>Scalability</category>
      <category>GitHub Actions</category>
      <category>github</category>
      <category>DevOps</category>
      <category>news</category>
      <pubDate>Tue, 20 Oct 2026 12:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/10/github-runner-controller-0-15/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Scalability</guid>
      <dc:creator>Craig Risi</dc:creator>
      <dc:date>2026-10-20T12:00:00Z</dc:date>
      <dc:identifier>/news/2026/10/github-runner-controller-0-15/en</dc:identifier>
    </item>
    <item>
      <title>Presentation: Beyond the Prototype: Scaling Framework Agnostic AI Agent Infrastructure with Ray</title>
      <link>https://www.infoq.com/presentations/scale-llm-agents-production-ray/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Scalability</link>
      <description>&lt;img src="https://res.infoq.com/presentations/scale-llm-agents-production-ray/en/mediumimage/medium-1792065446239.jpg"/&gt;&lt;p&gt;The speakers discuss transitioning AI agents from local FastAPI prototypes to resilient production systems on Kubernetes using Ray. They share operational insights on RayCluster topology, stateful memory handling, auto-scaling on dynamic traffic, and robust control plane designs, while highlighting critical guardrails, multi-region setups, and LLM-as-a-judge evaluation pipelines.&lt;/p&gt; &lt;i&gt;By Deepak Mohanakumar Chandramouli, Bhumik Vinodkumar Thakkar&lt;/i&gt;</description>
      <category>Scalability</category>
      <category>Large language models</category>
      <category>Machine Learning</category>
      <category>Agents</category>
      <category>Transcripts</category>
      <category>QCon AI Boston 2026</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>Architecture &amp; Design</category>
      <category>Development</category>
      <category>presentation</category>
      <pubDate>Tue, 20 Oct 2026 11:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/presentations/scale-llm-agents-production-ray/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Scalability</guid>
      <dc:creator>Deepak Mohanakumar Chandramouli, Bhumik Vinodkumar Thakkar</dc:creator>
      <dc:date>2026-10-20T11:00:00Z</dc:date>
      <dc:identifier>/presentations/scale-llm-agents-production-ray/en</dc:identifier>
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