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    <title>InfoQ</title>
    <link>https://www.infoq.com</link>
    <description>InfoQ feed</description>
    <item>
      <title>DuckDB Quack: Client/Server Protocol over HTTP for Multi-User Analytics</title>
      <link>https://www.infoq.com/news/2026/05/duckdb-quack-protocol/?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/2026/05/duckdb-quack-protocol/en/headerimage/generatedHeaderImage-1779460941997.jpg"/&gt;&lt;p&gt;DuckDB has recently announced Quack, a new remote protocol over HTTP that lets multiple DuckDB instances connect to and work with the same database over a network. The protocol introduces client-server capabilities to a database that was previously mostly local and embedded.&lt;/p&gt; &lt;i&gt;By Renato Losio&lt;/i&gt;</description>
      <category>SQL</category>
      <category>Data Analytics</category>
      <category>Distributed Data</category>
      <category>Apache Arrow</category>
      <category>duckdb</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>Development</category>
      <category>news</category>
      <pubDate>Sun, 31 May 2026 11:17:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/05/duckdb-quack-protocol/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</guid>
      <dc:creator>Renato Losio</dc:creator>
      <dc:date>2026-05-31T11:17:00Z</dc:date>
      <dc:identifier>/news/2026/05/duckdb-quack-protocol/en</dc:identifier>
    </item>
    <item>
      <title>Arm Open-Sources Metis, an AI Security Framework Outperforming Traditional SAST Tools</title>
      <link>https://www.infoq.com/news/2026/05/arm-metis-agentic-security/?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/2026/05/arm-metis-agentic-security/en/headerimage/arm-metis-1780165811953.jpeg"/&gt;&lt;p&gt;Arm has open-sourced Metis, an agentic AI security framework designed to autonomously uncover complex software vulnerabilities. Unlike traditional pattern-based tools, Metis applies semantic reasoning to analyze cross-component dependencies and provides clear, natural language explanations for its findings.&lt;/p&gt; &lt;i&gt;By Sergio De Simone&lt;/i&gt;</description>
      <category>Open Source</category>
      <category>Static Analysis</category>
      <category>Large language models</category>
      <category>ARM</category>
      <category>Security</category>
      <category>Security Vulnerabilities</category>
      <category>Agents</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>DevOps</category>
      <category>Development</category>
      <category>news</category>
      <pubDate>Sat, 30 May 2026 19:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/05/arm-metis-agentic-security/?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>2026-05-30T19:00:00Z</dc:date>
      <dc:identifier>/news/2026/05/arm-metis-agentic-security/en</dc:identifier>
    </item>
    <item>
      <title>Google Cloud Suspends Railway's Production Account, Causing Eight-Hour Platform-Wide Outage</title>
      <link>https://www.infoq.com/news/2026/05/railway-gcp-account-outage/?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/2026/05/railway-gcp-account-outage/en/headerimage/generatedHeaderImage-1779878225205.jpg"/&gt;&lt;p&gt;Google Cloud's automated systems suspended Railway's production account without notice, triggering an eight-hour platform-wide outage affecting 3 million users. The cascade took down workloads across all providers including AWS and bare metal because Railway's control plane was hosted on GCP. Railway is demoting GCP to backup-only status.&lt;/p&gt; &lt;i&gt;By Steef-Jan Wiggers&lt;/i&gt;</description>
      <category>Cloud</category>
      <category>Google Cloud Platform</category>
      <category>Cloud Architecture</category>
      <category>Google</category>
      <category>Google Cloud</category>
      <category>Site Reliability Engineering</category>
      <category>DevOps</category>
      <category>Development</category>
      <category>Architecture &amp; Design</category>
      <category>news</category>
      <pubDate>Sat, 30 May 2026 10:03:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/05/railway-gcp-account-outage/?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>2026-05-30T10:03:00Z</dc:date>
      <dc:identifier>/news/2026/05/railway-gcp-account-outage/en</dc:identifier>
    </item>
    <item>
      <title>How Meta Rebuilt Data Ingestion for Petabyte-Scale Reliability</title>
      <link>https://www.infoq.com/news/2026/05/meta-cdc-migration/?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/2026/05/meta-cdc-migration/en/headerimage/generatedHeaderImage-1779134681732.jpg"/&gt;&lt;p&gt;The engineering team at Meta recently outlined how the company migrated a data ingestion platform that transfers several petabytes of MySQL social graph data daily to improve reliability and operational efficiency. The team used techniques like reverse shadowing and continuous checksum monitoring to ensure zero downtime during the transition.&lt;/p&gt; &lt;i&gt;By Renato Losio&lt;/i&gt;</description>
      <category>Big Data Infrastructure</category>
      <category>migration</category>
      <category>Facebook</category>
      <category>MySQL</category>
      <category>Scalability</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>Architecture &amp; Design</category>
      <category>news</category>
      <pubDate>Sat, 30 May 2026 06:01:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/05/meta-cdc-migration/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</guid>
      <dc:creator>Renato Losio</dc:creator>
      <dc:date>2026-05-30T06:01:00Z</dc:date>
      <dc:identifier>/news/2026/05/meta-cdc-migration/en</dc:identifier>
    </item>
    <item>
      <title>AI-Assisted Migration Tool Helps Teams Move from ingress-nginx to Higress in Minutes</title>
      <link>https://www.infoq.com/news/2026/05/ai-nginx-higress/?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/2026/05/ai-nginx-higress/en/headerimage/generatedHeaderImage-1779528783880.jpg"/&gt;&lt;p&gt;The Cloud Native Computing Foundation has highlighted a new AI-assisted migration approach that enabled engineers to migrate 60 ingress-nginx resources to Higress in roughly 30 minutes, demonstrating how artificial intelligence is increasingly being applied to modernize Kubernetes networking and gateway infrastructure.&lt;/p&gt; &lt;i&gt;By Craig Risi&lt;/i&gt;</description>
      <category>migration</category>
      <category>NGINX</category>
      <category>Artificial Intelligence</category>
      <category>AI Development</category>
      <category>Infrastructure</category>
      <category>Infrastructure as Code</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>DevOps</category>
      <category>news</category>
      <pubDate>Fri, 29 May 2026 12:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/05/ai-nginx-higress/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</guid>
      <dc:creator>Craig Risi</dc:creator>
      <dc:date>2026-05-29T12:00:00Z</dc:date>
      <dc:identifier>/news/2026/05/ai-nginx-higress/en</dc:identifier>
    </item>
    <item>
      <title>Presentation: Building Evals for AI Adoption: From Principles to Practice</title>
      <link>https://www.infoq.com/presentations/eval-ai-adoption/?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/eval-ai-adoption/en/mediumimage/medium-1779185675202.jpeg"/&gt;&lt;p&gt;Mallika Rao discusses the hidden risk of evaluation debt in production AI systems, drawing on her experience at Twitter, Walmart, and Netflix. She explains why traditional metrics fail modern architectures, breaks down a five-layer evaluation stack spanning infrastructure and UX, and shares a diagnostic maturity model to help engineering leaders eliminate silent semantic failures.&lt;/p&gt; &lt;i&gt;By Mallika Rao&lt;/i&gt;</description>
      <category>QCon AI 2025</category>
      <category>Large language models</category>
      <category>Artificial Intelligence</category>
      <category>Adoption</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>presentation</category>
      <pubDate>Fri, 29 May 2026 12:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/presentations/eval-ai-adoption/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</guid>
      <dc:creator>Mallika Rao</dc:creator>
      <dc:date>2026-05-29T12:00:00Z</dc:date>
      <dc:identifier>/presentations/eval-ai-adoption/en</dc:identifier>
    </item>
    <item>
      <title>GitHub Slashes Agent Workflow Token Spend up to 62% with Daily Audits and MCP Pruning</title>
      <link>https://www.infoq.com/news/2026/05/github-agentic-token-savings/?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/2026/05/github-agentic-token-savings/en/headerimage/header-1779918825690.jpeg"/&gt;&lt;p&gt;GitHub reports cutting token costs in agentic CI workflows by up to 62% by pruning unused MCP tools, swapping some MCP calls for gh CLI, and running daily “auditor” and “optimizer” agents. A token-usage.jsonl artefact and an Effective Tokens metric help track spend across models and spot regressions.&lt;/p&gt; &lt;i&gt;By Mark Silvester&lt;/i&gt;</description>
      <category>FinOps</category>
      <category>AI Architecture</category>
      <category>github</category>
      <category>Software Engineering</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>DevOps</category>
      <category>Development</category>
      <category>Architecture &amp; Design</category>
      <category>news</category>
      <pubDate>Fri, 29 May 2026 08:30:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/05/github-agentic-token-savings/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</guid>
      <dc:creator>Mark Silvester</dc:creator>
      <dc:date>2026-05-29T08:30:00Z</dc:date>
      <dc:identifier>/news/2026/05/github-agentic-token-savings/en</dc:identifier>
    </item>
    <item>
      <title>Presentation: From Founding Engineer to CTO to CEO – At the Same Startup</title>
      <link>https://www.infoq.com/presentations/framework-best-practices-startup/?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/framework-best-practices-startup/en/mediumimage/medium-1779194881438.jpeg"/&gt;&lt;p&gt;Trisha Ballakur discusses her journey from a backend software engineer to CTO and CEO, using her startup Pointz as a case study. She explains how to implement bottom-up customer discovery to find product-market fit, effectively delegate to global contractors to reduce build times, customize open-source repos like Valhalla, and apply engineering test-case models to business development.&lt;/p&gt; &lt;i&gt;By Trisha Ballakur&lt;/i&gt;</description>
      <category>Best Practices</category>
      <category>QCon San Francisco 2025</category>
      <category>Transcripts</category>
      <category>Startup</category>
      <category>Culture &amp; Methods</category>
      <category>presentation</category>
      <pubDate>Thu, 28 May 2026 12:33:00 GMT</pubDate>
      <guid>https://www.infoq.com/presentations/framework-best-practices-startup/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</guid>
      <dc:creator>Trisha Ballakur</dc:creator>
      <dc:date>2026-05-28T12:33:00Z</dc:date>
      <dc:identifier>/presentations/framework-best-practices-startup/en</dc:identifier>
    </item>
    <item>
      <title>Accountability is the Goal for AI, with EU Regulations Supporting Transparency</title>
      <link>https://www.infoq.com/news/2026/05/accountability-AI-EU-regulations/?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/2026/05/accountability-AI-EU-regulations/en/headerimage/accountability-regulation-supporting-transparency-header-1779711042392.jpg"/&gt;&lt;p&gt;AI bias mirrors human bias; both stem from our language and lived experiences. Ethics and AI are inseparable, but AI changes affordances, making harmful actions easier to carry out. The EU regulations apply to AI, since digital products are products. The ultimate goal is accountability: companies must ensure transparency, and laws should favor using the simplest AI that gets the job done.&lt;/p&gt; &lt;i&gt;By Ben Linders&lt;/i&gt;</description>
      <category>Ethics</category>
      <category>Keynote</category>
      <category>Regulation</category>
      <category>GOTO Conference</category>
      <category>Artificial Intelligence</category>
      <category>Products</category>
      <category>GDPR</category>
      <category>Culture &amp; Methods</category>
      <category>news</category>
      <pubDate>Thu, 28 May 2026 11:08:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/05/accountability-AI-EU-regulations/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</guid>
      <dc:creator>Ben Linders</dc:creator>
      <dc:date>2026-05-28T11:08:00Z</dc:date>
      <dc:identifier>/news/2026/05/accountability-AI-EU-regulations/en</dc:identifier>
    </item>
    <item>
      <title>Microsoft Announces Azure Linux 4.0, Its First General-Purpose Server Linux Distribution</title>
      <link>https://www.infoq.com/news/2026/05/azure-linux-4-server/?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;Microsoft announced Azure Linux 4.0 and Azure Container Linux at Open Source Summit. Azure Linux 4.0 is a Fedora-based general-purpose server distribution for Azure VMs, the first time Microsoft has offered a supported Linux beyond container hosting. Azure Container Linux is an immutable container-optimized host built on Flatcar.&lt;/p&gt; &lt;i&gt;By Steef-Jan Wiggers&lt;/i&gt;</description>
      <category>Open Source</category>
      <category>Linux</category>
      <category>Cloud</category>
      <category>Containers</category>
      <category>Operating Systems</category>
      <category>Microsoft Azure</category>
      <category>DevOps</category>
      <category>Development</category>
      <category>Architecture &amp; Design</category>
      <category>news</category>
      <pubDate>Thu, 28 May 2026 09:49:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/05/azure-linux-4-server/?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>2026-05-28T09:49:00Z</dc:date>
      <dc:identifier>/news/2026/05/azure-linux-4-server/en</dc:identifier>
    </item>
    <item>
      <title>Article: Stragglers, Not Failures: How Adaptive Hedged Requests Reduce p99 Latency by 74 Percent</title>
      <link>https://www.infoq.com/articles/adaptive-hedged-requests-p99-latency/?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/adaptive-hedged-requests-p99-latency/en/headerimage/adaptive-hedged-requests-p99-latency-header-1779785816730.jpg"/&gt;&lt;p&gt;n fan-out microservice architectures, slow-but-completing requests accumulate across services and drive p99 latency far higher than per-service metrics suggest. This article presents an adaptive hedging mechanism that uses DDSketch for real-time quantile estimation, windowed rotation to handle distribution drift, and a token-bucket budget to prevent load amplification.&lt;/p&gt; &lt;i&gt;By Prathamesh Bhope&lt;/i&gt;</description>
      <category>Cloud</category>
      <category>Architecture</category>
      <category>Distributed Systems</category>
      <category>Performance</category>
      <category>DevOps</category>
      <category>Development</category>
      <category>Architecture &amp; Design</category>
      <category>article</category>
      <pubDate>Thu, 28 May 2026 09:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/articles/adaptive-hedged-requests-p99-latency/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</guid>
      <dc:creator>Prathamesh Bhope</dc:creator>
      <dc:date>2026-05-28T09:00:00Z</dc:date>
      <dc:identifier>/articles/adaptive-hedged-requests-p99-latency/en</dc:identifier>
    </item>
    <item>
      <title>Cloudflare Adds Support for Claude Managed Agents</title>
      <link>https://www.infoq.com/news/2026/05/cloudflare-claude-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/news/2026/05/cloudflare-claude-agents/en/headerimage/generatedHeaderImage-1779863264544.jpg"/&gt;&lt;p&gt;Cloudflare recently added support for Claude Managed Agents, allowing developers to run and manage Claude agents within Cloudflare. Developers can connect agents to private systems, choose their runtime environment, and monitor agent activity using Cloudflare services.&lt;/p&gt; &lt;i&gt;By Renato Losio&lt;/i&gt;</description>
      <category>Cloudflare</category>
      <category>Cloud</category>
      <category>Serverless</category>
      <category>Model Context Protocol (MCP)</category>
      <category>Anthropic</category>
      <category>Agents</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>Development</category>
      <category>news</category>
      <pubDate>Thu, 28 May 2026 06:23:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/05/cloudflare-claude-agents/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</guid>
      <dc:creator>Renato Losio</dc:creator>
      <dc:date>2026-05-28T06:23:00Z</dc:date>
      <dc:identifier>/news/2026/05/cloudflare-claude-agents/en</dc:identifier>
    </item>
    <item>
      <title>How LinkedIn Identified a Kernel Lock Contention Issue Causing Recurring System Freezes</title>
      <link>https://www.infoq.com/news/2026/05/linkedin-kernel-lock-freeze/?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/2026/05/linkedin-kernel-lock-freeze/en/headerimage/linkedin-kernel-lock-freeze-1779903552098.jpg"/&gt;&lt;p&gt;When LinkedIn engineers encountered short-lived, recurring outages where the database powering their user feed became unavailable and then recovered without leaving helpful traces, they had to devise a novel approach to uncover the root cause using off-CPU profiling with eBPF.&lt;/p&gt; &lt;i&gt;By Sergio De Simone&lt;/i&gt;</description>
      <category>LinkedIn</category>
      <category>Linux</category>
      <category>Rust</category>
      <category>Monitoring</category>
      <category>eBPF</category>
      <category>Memory</category>
      <category>Availability</category>
      <category>Profilers</category>
      <category>Architecture &amp; Design</category>
      <category>Development</category>
      <category>news</category>
      <pubDate>Wed, 27 May 2026 18:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/05/linkedin-kernel-lock-freeze/?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>2026-05-27T18:00:00Z</dc:date>
      <dc:identifier>/news/2026/05/linkedin-kernel-lock-freeze/en</dc:identifier>
    </item>
    <item>
      <title>Azure Logic Apps Adds Sandboxed Code Interpreters to Agent Workflows</title>
      <link>https://www.infoq.com/news/2026/05/azure-logic-apps-agents/?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;Microsoft added sandboxed code interpreters to Azure Logic Apps, enabling agents within integration workflows to generate and execute Python, JavaScript, C#, and PowerShell in Hyper-V isolated sessions. Architects get full control over model selection per workflow. The capability positions Logic Apps as an agent platform for integration alongside Foundry and Copilot Studio.&lt;/p&gt; &lt;i&gt;By Steef-Jan Wiggers&lt;/i&gt;</description>
      <category>Cloud</category>
      <category>Low Code</category>
      <category>AI Architecture</category>
      <category>Azure</category>
      <category>iPaaS</category>
      <category>LogicApps</category>
      <category>Agents</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>DevOps</category>
      <category>Development</category>
      <category>Architecture &amp; Design</category>
      <category>news</category>
      <pubDate>Wed, 27 May 2026 09:45:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/05/azure-logic-apps-agents/?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>2026-05-27T09:45:00Z</dc:date>
      <dc:identifier>/news/2026/05/azure-logic-apps-agents/en</dc:identifier>
    </item>
    <item>
      <title>Presentation: Designing AI Platforms for Reliability: Tools for Certainty, Agents for Discovery</title>
      <link>https://www.infoq.com/presentations/ai-platforms-reliability/?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/ai-platforms-reliability/en/mediumimage/medium-1779182751443.jpg"/&gt;&lt;p&gt;Aaron Erickson discusses the evolution of AI workflows, shifting from "vibe checking" to building reliable, multi-agent frameworks. He explains how to combine deterministic software guardrails with agentic discovery, optimize agent hierarchies, leverage time-series foundation models, and implement rigorous evaluation pyramids to ensure architecture scales effectively in production.&lt;/p&gt; &lt;i&gt;By Aaron Erickson&lt;/i&gt;</description>
      <category>QCon AI 2025</category>
      <category>Artificial Intelligence</category>
      <category>Transcripts</category>
      <category>Reliability</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>presentation</category>
      <pubDate>Wed, 27 May 2026 09:04:00 GMT</pubDate>
      <guid>https://www.infoq.com/presentations/ai-platforms-reliability/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</guid>
      <dc:creator>Aaron Erickson</dc:creator>
      <dc:date>2026-05-27T09:04:00Z</dc:date>
      <dc:identifier>/presentations/ai-platforms-reliability/en</dc:identifier>
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