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    <title>InfoQ</title>
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    <description>InfoQ feed</description>
    <item>
      <title>Anthropic Adds Opt-In Security Scanning for Critical Open-Source Projects</title>
      <link>https://www.infoq.com/news/2026/10/anthropic-oss-security-scanner/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</link>
      <description>&lt;img src="https://res.infoq.com/news/2026/10/anthropic-oss-security-scanner/en/headerimage/generatedHeaderImage-1792523938215.jpg"/&gt;&lt;p&gt;AI company Anthropic has launched OSS Scanner, a free, opt-in service to find vulnerabilities in open-source projects. Enrolled maintainers receive periodic security reports generated by the company's strongest models, including Claude Mythos. The reports are sent without human review, and project maintainers can choose to validate their findings and decide which proposed fixes to accept.&lt;/p&gt; &lt;i&gt;By Matt Saunders&lt;/i&gt;</description>
      <category>Open Source</category>
      <category>Anthropic</category>
      <category>AI Security</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>news</category>
      <pubDate>Fri, 23 Oct 2026 09:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/10/anthropic-oss-security-scanner/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</guid>
      <dc:creator>Matt Saunders</dc:creator>
      <dc:date>2026-10-23T09:00:00Z</dc:date>
      <dc:identifier>/news/2026/10/anthropic-oss-security-scanner/en</dc:identifier>
    </item>
    <item>
      <title>NgRx 22: Resource Extensions and Dynamic Deep Signals for Angular</title>
      <link>https://www.infoq.com/news/2026/10/ngrx-22-angular/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</link>
      <description>&lt;img src="https://res.infoq.com/news/2026/10/ngrx-22-angular/en/headerimage/generatedHeaderImage-1792664456149.jpg"/&gt;&lt;p&gt;NgRx 22 adds experimental resource extensions that change Angular's resource behavior, so value() is retained during reloads and no longer throws on errors. It also introduces dynamic deep signals for union types, a SignalStoreFeatureType utility, and ESLint v10 support. Upgrading requires Angular 22 and TypeScript 6.0, and most breaking changes have automated migrations.&lt;/p&gt; &lt;i&gt;By Daniel Curtis&lt;/i&gt;</description>
      <category>Web Development</category>
      <category>JavaScript</category>
      <category>AngularJS</category>
      <category>TypeScript</category>
      <category>Angular</category>
      <category>Development</category>
      <category>news</category>
      <pubDate>Fri, 23 Oct 2026 08:08:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/10/ngrx-22-angular/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</guid>
      <dc:creator>Daniel Curtis</dc:creator>
      <dc:date>2026-10-23T08:08:00Z</dc:date>
      <dc:identifier>/news/2026/10/ngrx-22-angular/en</dc:identifier>
    </item>
    <item>
      <title>Study Finds AI-generated Code Fails to Boost Productivity Due to Downstream Bottlenecks</title>
      <link>https://www.infoq.com/news/2026/10/jellyfish-ai-productivity/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</link>
      <description>&lt;img src="https://res.infoq.com/news/2026/10/jellyfish-ai-productivity/en/headerimage/claude-built-c-compiler-1792676797236.jpeg"/&gt;&lt;p&gt;A recent Harvard study of 718 firms, using the Jellyfish analytics platform, finds that although AI coding assistants and agents increase code volume, this does not translate into a corresponding increase in completed work, partly because AI-generated code increases the workload in later stages of development, particularly code review.&lt;/p&gt; &lt;i&gt;By Sergio De Simone&lt;/i&gt;</description>
      <category>Large language models</category>
      <category>Claude</category>
      <category>copilot</category>
      <category>Productivity</category>
      <category>AI coding agents</category>
      <category>github</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>Architecture &amp; Design</category>
      <category>Development</category>
      <category>news</category>
      <pubDate>Thu, 22 Oct 2026 14:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/10/jellyfish-ai-productivity/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</guid>
      <dc:creator>Sergio De Simone</dc:creator>
      <dc:date>2026-10-22T14:00:00Z</dc:date>
      <dc:identifier>/news/2026/10/jellyfish-ai-productivity/en</dc:identifier>
    </item>
    <item>
      <title>Presentation: Actors for Agents: Patterns for Production AI</title>
      <link>https://www.infoq.com/presentations/actors-for-production-ai-agents/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</link>
      <description>&lt;img src="https://res.infoq.com/presentations/actors-for-production-ai-agents/en/mediumimage/medium-1792065780503.jpeg"/&gt;&lt;p&gt;Manju Rajashekhar explains how the actor model solves the complex runtime challenges of production AI agents. By treating agents as distributed systems, he discusses state ownership, message passing, write-through state, and supervision boundaries to manage failures, continuations, and mutable execution graphs, moving agentic workflows beyond fragile demos to resilient architecture.&lt;/p&gt; &lt;i&gt;By Manju Rajashekhar&lt;/i&gt;</description>
      <category>Fault Tolerance</category>
      <category>Agents</category>
      <category>Architecture</category>
      <category>Distributed Systems</category>
      <category>Transcripts</category>
      <category>Actor Model</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>Thu, 22 Oct 2026 11:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/presentations/actors-for-production-ai-agents/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</guid>
      <dc:creator>Manju Rajashekhar</dc:creator>
      <dc:date>2026-10-22T11:00:00Z</dc:date>
      <dc:identifier>/presentations/actors-for-production-ai-agents/en</dc:identifier>
    </item>
    <item>
      <title>Vercel Labs Open-Sources fx: A Zig Coding Agent Designed to Be Embedded</title>
      <link>https://www.infoq.com/news/2026/10/vercel-zig-fx-agent/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</link>
      <description>&lt;img src="https://res.infoq.com/news/2026/10/vercel-zig-fx-agent/en/headerimage/generatedHeaderImage-1792649903570.jpg"/&gt;&lt;p&gt;Vercel Labs has released fx, an experimental open-source coding agent written in Zig. It runs as a CLI, a script component, or an embedded library, including a WebAssembly build. Early feedback questioned its model-agnostic claim and a name conflict with an existing tool. Vercel says the project is pre-1.0 and changing quickly.&lt;/p&gt; &lt;i&gt;By Daniel Curtis&lt;/i&gt;</description>
      <category>Web Development</category>
      <category>Agents</category>
      <category>AI Coding</category>
      <category>OpenAI</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>Development</category>
      <category>news</category>
      <pubDate>Thu, 22 Oct 2026 09:33:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/10/vercel-zig-fx-agent/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</guid>
      <dc:creator>Daniel Curtis</dc:creator>
      <dc:date>2026-10-22T09:33:00Z</dc:date>
      <dc:identifier>/news/2026/10/vercel-zig-fx-agent/en</dc:identifier>
    </item>
    <item>
      <title>Article: AI Changes the Data Interface, Not the Query Engine</title>
      <link>https://www.infoq.com/articles/ai-changes-data-interface/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</link>
      <description>&lt;img src="https://res.infoq.com/articles/ai-changes-data-interface/en/headerimage/header-1792487239242.jpg"/&gt;&lt;p&gt;This article presents a disaster-recovery analytics workflow in which an AI agent generates constrained SQL or Python, DuckDB computes reproducible facts from Parquet, and the agent interprets the results. It explains the determinism split, replayable analysis, and four signals for deciding when an embedded engine is sufficient or a managed lakehouse is justified.&lt;/p&gt; &lt;i&gt;By Peihao Yuan&lt;/i&gt;</description>
      <category>Agentic AI Architecture</category>
      <category>duckdb</category>
      <category>Data Lake</category>
      <category>Disaster Recovery</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>Architecture &amp; Design</category>
      <category>article</category>
      <pubDate>Thu, 22 Oct 2026 09:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/articles/ai-changes-data-interface/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</guid>
      <dc:creator>Peihao Yuan</dc:creator>
      <dc:date>2026-10-22T09:00:00Z</dc:date>
      <dc:identifier>/articles/ai-changes-data-interface/en</dc:identifier>
    </item>
    <item>
      <title>Harbor Adds Docker Sandboxes to Run Reproducible AI Agent Evals in Isolated MicroVMs</title>
      <link>https://www.infoq.com/news/2026/10/ai-agents-harbor-docker/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</link>
      <description>&lt;img src="https://res.infoq.com/news/2026/10/ai-agents-harbor-docker/en/headerimage/generatedHeaderImage-1792589629439.jpg"/&gt;&lt;p&gt;Docker announced that Harbor, the open-source agent evaluation framework, now works with Docker Sandboxes. This change allows each evaluation task to run in its own microVM. So, instead of sharing a container, tasks are isolated for better performance&lt;/p&gt; &lt;i&gt;By Claudio Masolo&lt;/i&gt;</description>
      <category>Agentic AI Architecture</category>
      <category>Docker</category>
      <category>DevOps</category>
      <category>news</category>
      <pubDate>Thu, 22 Oct 2026 09:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/10/ai-agents-harbor-docker/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</guid>
      <dc:creator>Claudio Masolo</dc:creator>
      <dc:date>2026-10-22T09:00:00Z</dc:date>
      <dc:identifier>/news/2026/10/ai-agents-harbor-docker/en</dc:identifier>
    </item>
    <item>
      <title>Developer Behind the AI-Built Adobe Clones Says They Are “Not Anywhere Close to Ready</title>
      <link>https://www.infoq.com/news/2026/10/photocraft-adobe-parity/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</link>
      <description>&lt;img src="https://www.infoq.com/styles/static/images/logo/logo_bigger.jpg"/&gt;&lt;p&gt;A developer used Claude Opus 5.5 to build open-source replacements for seven Adobe applications, promoted them across Reddit with a projection of roughly 100% parity within a month, then told Hacker News the project was not anywhere close to ready. Its own roadmap puts it at 45% ready for real work and 2,300 to 4,100 agent-hours from full parity.&lt;/p&gt; &lt;i&gt;By Steef-Jan Wiggers&lt;/i&gt;</description>
      <category>Open Source</category>
      <category>AI Development</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>Culture &amp; Methods</category>
      <category>Architecture &amp; Design</category>
      <category>Development</category>
      <category>DevOps</category>
      <category>news</category>
      <pubDate>Thu, 22 Oct 2026 07:41:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/10/photocraft-adobe-parity/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</guid>
      <dc:creator>Steef-Jan Wiggers</dc:creator>
      <dc:date>2026-10-22T07:41:00Z</dc:date>
      <dc:identifier>/news/2026/10/photocraft-adobe-parity/en</dc:identifier>
    </item>
    <item>
      <title>eMudhra Intermediate CA Compromise</title>
      <link>https://www.infoq.com/news/2026/10/emudhra-ca-compromise/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</link>
      <description>&lt;img src="https://res.infoq.com/news/2026/10/emudhra-ca-compromise/en/headerimage/weak-link-1792602361259.jpeg"/&gt;&lt;p&gt;Private keys for eight eMudhra intermediate CA certificates have been compromised, allowing attackers to forge certificates for any site. The keys were revealed due to low entropy, not through a known breach. Browsers blocked them using revocation lists, but other software had to remove the emSign ECC G3 root. Unpatched systems remain exposed to forged certificates, including client auth and mTLS.&lt;/p&gt; &lt;i&gt;By Chris Swan&lt;/i&gt;</description>
      <category>Security</category>
      <category>Web</category>
      <category>Security Incident</category>
      <category>Architecture &amp; Design</category>
      <category>DevOps</category>
      <category>news</category>
      <pubDate>Wed, 21 Oct 2026 17:30:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/10/emudhra-ca-compromise/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</guid>
      <dc:creator>Chris Swan</dc:creator>
      <dc:date>2026-10-21T17:30:00Z</dc:date>
      <dc:identifier>/news/2026/10/emudhra-ca-compromise/en</dc:identifier>
    </item>
    <item>
      <title>Netflix Bridges AWS IAM and Internal Identity with Workload Attestation</title>
      <link>https://www.infoq.com/news/2026/10/netflix-workload-attestation-aws/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</link>
      <description>&lt;img src="https://www.infoq.com/styles/static/images/logo/logo_bigger.jpg"/&gt;&lt;p&gt;Netflix has developed a workload attestation mechanism for Apache Spark jobs running on Amazon EMR. The design combines AWS IAM identity with signed claims from Netflix’s control plane before issuing short-lived internal X.509 certificates, allowing managed compute workloads to authenticate to internal services without directly injecting credentials.&lt;/p&gt; &lt;i&gt;By Leela Kumili&lt;/i&gt;</description>
      <category>Amazon</category>
      <category>Netflix</category>
      <category>MapReduce</category>
      <category>Authentication</category>
      <category>Service Identification</category>
      <category>Security</category>
      <category>Distributed Systems</category>
      <category>AWS</category>
      <category>Identity Management</category>
      <category>Architecture &amp; Design</category>
      <category>Development</category>
      <category>DevOps</category>
      <category>news</category>
      <pubDate>Wed, 21 Oct 2026 13:45:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/10/netflix-workload-attestation-aws/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</guid>
      <dc:creator>Leela Kumili</dc:creator>
      <dc:date>2026-10-21T13:45:00Z</dc:date>
      <dc:identifier>/news/2026/10/netflix-workload-attestation-aws/en</dc:identifier>
    </item>
    <item>
      <title>Article Series: Agentic AI Architecture</title>
      <link>https://www.infoq.com/articles/agentic-ai-architecture-article-series/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</link>
      <description>&lt;img src="https://res.infoq.com/articles/agentic-ai-architecture-article-series/en/headerimage/agentic-ai-architecture-article-series-header-image-1792490151960.jpg"/&gt;&lt;p&gt;In this article series, we try to establish agentic AI architecture as a new type of software architecture that will likely dominate the industry for years to come. The articles, written by industry experts, cover various elements and aspects of agentic AI architecture. We aim to present the latest trends and developments shaping the new type of architecture as it enters the mainstream.&lt;/p&gt; &lt;i&gt;By Rafał Gancarz&lt;/i&gt;</description>
      <category>Agentic AI Architecture</category>
      <category>Article Series</category>
      <category>Agents</category>
      <category>Microservices</category>
      <category>Agentic AI Architecture Series</category>
      <category>Frameworks</category>
      <category>AI Architecture</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>Architecture &amp; Design</category>
      <category>article</category>
      <pubDate>Wed, 21 Oct 2026 11:30:00 GMT</pubDate>
      <guid>https://www.infoq.com/articles/agentic-ai-architecture-article-series/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</guid>
      <dc:creator>Rafał Gancarz</dc:creator>
      <dc:date>2026-10-21T11:30:00Z</dc:date>
      <dc:identifier>/articles/agentic-ai-architecture-article-series/en</dc:identifier>
    </item>
    <item>
      <title>Presentation: AI is an Amplifier: Scale High Performance, Not Dysfunction</title>
      <link>https://www.infoq.com/presentations/dora-ai-adoption-engineering-performance/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</link>
      <description>&lt;img src="https://res.infoq.com/presentations/dora-ai-adoption-engineering-performance/en/mediumimage/medium-1791447741420.jpg"/&gt;&lt;p&gt;Nathen Harvey shares insights from DORA research on AI adoption in software delivery. He explains why AI acts as an amplifier, how the DORA AI Capabilities Model drives outcomes, and why engineering leaders must evolve beyond bottlenecks like code reviews to achieve sustainable productivity, reduce delivery instability, and empower developers without burning out their teams.&lt;/p&gt; &lt;i&gt;By Nathen Harvey&lt;/i&gt;</description>
      <category>Performance</category>
      <category>Continuous Improvement</category>
      <category>Adoption</category>
      <category>Management</category>
      <category>Transcripts</category>
      <category>QCon London 2026</category>
      <category>Continuous Delivery</category>
      <category>Code Quality</category>
      <category>Artificial Intelligence</category>
      <category>Productivity</category>
      <category>Culture &amp; Methods</category>
      <category>Development</category>
      <category>DevOps</category>
      <category>presentation</category>
      <pubDate>Wed, 21 Oct 2026 11:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/presentations/dora-ai-adoption-engineering-performance/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</guid>
      <dc:creator>Nathen Harvey</dc:creator>
      <dc:date>2026-10-21T11:00:00Z</dc:date>
      <dc:identifier>/presentations/dora-ai-adoption-engineering-performance/en</dc:identifier>
    </item>
    <item>
      <title>Google SynthID Detector Simplifies Watermark Detection and Expands Support to Other AI Providers</title>
      <link>https://www.infoq.com/news/2026/10/synthid-watermarking-detector/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</link>
      <description>&lt;img src="https://res.infoq.com/news/2026/10/synthid-watermarking-detector/en/headerimage/cyberark-model-security-1792576150415.jpeg"/&gt;&lt;p&gt;Google DeepMind announced the global availability of SynthID Detector, a tool designed to help identify AI-generated content, including media created using AI tools from SynthID partners such as OpenAI, NVIDIA, and Kakao, with Apple support expected soon.&lt;/p&gt; &lt;i&gt;By Sergio De Simone&lt;/i&gt;</description>
      <category>Microsoft</category>
      <category>Google</category>
      <category>OpenAI</category>
      <category>Facebook</category>
      <category>Metadata</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>Development</category>
      <category>news</category>
      <pubDate>Wed, 21 Oct 2026 10:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/10/synthid-watermarking-detector/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</guid>
      <dc:creator>Sergio De Simone</dc:creator>
      <dc:date>2026-10-21T10:00:00Z</dc:date>
      <dc:identifier>/news/2026/10/synthid-watermarking-detector/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=global</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=global</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>Cilium 1.20 Expands Gateway API and Opens eBPF Datapath for Kubernetes</title>
      <link>https://www.infoq.com/news/2026/10/cilium-120-kubernetes-networking/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</link>
      <description>&lt;img src="https://res.infoq.com/news/2026/10/cilium-120-kubernetes-networking/en/headerimage/generatedHeaderImage-1792161419866.jpg"/&gt;&lt;p&gt;Cilium 1.20 has been released with broader Kubernetes Gateway API support, an extensible eBPF datapath and further work on sidecarless mutual TLS. The release also makes the newer netkit network device easier to introduce across Kubernetes fleets that run different Linux kernel versions.&lt;/p&gt; &lt;i&gt;By Matt Saunders&lt;/i&gt;</description>
      <category>eBPF</category>
      <category>Kubernetes</category>
      <category>API Gateway</category>
      <category>DevOps</category>
      <category>news</category>
      <pubDate>Wed, 21 Oct 2026 09:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/10/cilium-120-kubernetes-networking/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</guid>
      <dc:creator>Matt Saunders</dc:creator>
      <dc:date>2026-10-21T09:00:00Z</dc:date>
      <dc:identifier>/news/2026/10/cilium-120-kubernetes-networking/en</dc:identifier>
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