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    <title>InfoQ</title>
    <link>https://www.infoq.com</link>
    <description>InfoQ feed</description>
    <item>
      <title>Article: Implementing the Sidecar Pattern in Microservices-based ASP.NET Core Applications</title>
      <link>https://www.infoq.com/articles/asp-net-core-side-car/?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/asp-net-core-side-car/en/headerimage/Implementing-the-Sidecar-Pattern-in-Microservices-based-ASP-NET-Core-Applications-header-1778079284259.jpg"/&gt;&lt;p&gt;Today's applications require monitoring, logging, configuration, etc. Each of these concerns can be implemented as a component or a service. These cross-cutting concerns can be tightly integrated into the application. While this tight coupling ensures effective use of shared resources, an outage in any of these components can take your application down. Enter the sidecar design pattern.&lt;/p&gt; &lt;i&gt;By Joydip Kanjilal&lt;/i&gt;</description>
      <category>.NET 10</category>
      <category>.NET 9</category>
      <category>.NET</category>
      <category>Development</category>
      <category>article</category>
      <pubDate>Fri, 08 May 2026 09:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/articles/asp-net-core-side-car/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</guid>
      <dc:creator>Joydip Kanjilal</dc:creator>
      <dc:date>2026-05-08T09:00:00Z</dc:date>
      <dc:identifier>/articles/asp-net-core-side-car/en</dc:identifier>
    </item>
    <item>
      <title>Podcast: The AI Joy Gap: Why Some Developers Thrive While Others Struggle</title>
      <link>https://www.infoq.com/podcasts/some-developers-thrive-while-others-struggle/?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/podcasts/some-developers-thrive-while-others-struggle/en/smallimage/engineering-culture-podcast-thumbnail-1777018955276.jpg"/&gt;&lt;p&gt;In this podcast, Shane Hastie, Lead Editor for Culture &amp; Methods, spoke to Michael Parker, VP of Engineering at TurinTech AI, about bringing joy back to software development in the AI era, the emerging role of "factory architects" who orchestrate AI agents rather than write code directly, and the cultural divide between AI hype and the reality developers face on legacy codebases.&lt;/p&gt; &lt;i&gt;By Michael Parker&lt;/i&gt;</description>
      <category>Legacy Code</category>
      <category>Developer Experience</category>
      <category>Leadership</category>
      <category>Engineering Culture Podcast</category>
      <category>Psychological Safety</category>
      <category>Teamwork</category>
      <category>Collaboration</category>
      <category>Culture &amp; Methods</category>
      <category>podcast</category>
      <pubDate>Fri, 08 May 2026 09:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/podcasts/some-developers-thrive-while-others-struggle/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</guid>
      <dc:creator>Michael Parker</dc:creator>
      <dc:date>2026-05-08T09:00:00Z</dc:date>
      <dc:identifier>/podcasts/some-developers-thrive-while-others-struggle/en</dc:identifier>
    </item>
    <item>
      <title>OpenAI Introduces Websocket-Based Execution Mode to Reduce Latency in Agentic Workflows</title>
      <link>https://www.infoq.com/news/2026/05/openai-websocket-responses-api/?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/openai-websocket-responses-api/en/headerimage/generatedHeaderImage-1777845282531.jpg"/&gt;&lt;p&gt;OpenAI introduces a WebSocket-based execution mode for its Responses API to improve agentic workflow performance in coding agents and real-time AI systems. The update reduces latency by up to 40 percent by replacing HTTP request-response cycles with persistent connections, improving streaming, tool execution, and multi-step orchestration in production-scale AI systems.&lt;/p&gt; &lt;i&gt;By Leela Kumili&lt;/i&gt;</description>
      <category>Large language models</category>
      <category>Low Latency</category>
      <category>API</category>
      <category>Workflow Foundation</category>
      <category>Distributed Systems</category>
      <category>SDK</category>
      <category>Realtime API</category>
      <category>OpenAI</category>
      <category>Artificial Intelligence</category>
      <category>AI Architecture</category>
      <category>Agents</category>
      <category>AI Assisted Coding</category>
      <category>WebSocket</category>
      <category>Orchestration</category>
      <category>Optimization</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>Development</category>
      <category>Architecture &amp; Design</category>
      <category>news</category>
      <pubDate>Thu, 07 May 2026 14:48:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/05/openai-websocket-responses-api/?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>2026-05-07T14:48:00Z</dc:date>
      <dc:identifier>/news/2026/05/openai-websocket-responses-api/en</dc:identifier>
    </item>
    <item>
      <title>Presentation: Engineering at AI Speed: Lessons from the First Agentically Accelerated Software Project</title>
      <link>https://www.infoq.com/presentations/engineering-ai/?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/engineering-ai/en/mediumimage/medium-1777370739830.jpg"/&gt;&lt;p&gt;Adam Wolff discusses the evolution of Claude Code, explaining how AI shifts the SDLC bottleneck from implementation to architectural decision-making. He shares three "war stories" to show why dogfooding and rapid unshipping are vital. He explains that when coding costs drop to zero, the speed of learning becomes the only competitive advantage.&lt;/p&gt; &lt;i&gt;By Adam Wolff&lt;/i&gt;</description>
      <category>Artificial Intelligence</category>
      <category>QCon San Francisco 2025</category>
      <category>Software Development</category>
      <category>Transcripts</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>presentation</category>
      <pubDate>Thu, 07 May 2026 14:07:00 GMT</pubDate>
      <guid>https://www.infoq.com/presentations/engineering-ai/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</guid>
      <dc:creator>Adam Wolff</dc:creator>
      <dc:date>2026-05-07T14:07:00Z</dc:date>
      <dc:identifier>/presentations/engineering-ai/en</dc:identifier>
    </item>
    <item>
      <title>Applying Best Simple System for Now for Software Design</title>
      <link>https://www.infoq.com/news/2026/05/best-simple-system-design/?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/best-simple-system-design/en/headerimage/best-simple-system-design-header-1776687343321.jpg"/&gt;&lt;p&gt;Choosing between building up technical debt and missing delivery deadlines is a false dichotomy, Daniel Terhorst-North argued in his talk Best Simple System for Now. Programmers love to generalize rather than solve the immediate problem at hand, which can make future changes difficult. Instead, we need to build the skills and instincts for keeping things simple.&lt;/p&gt; &lt;i&gt;By Ben Linders&lt;/i&gt;</description>
      <category>Code Quality</category>
      <category>Scalability</category>
      <category>Architecture</category>
      <category>Technical Debt</category>
      <category>Design</category>
      <category>GOTO Conference</category>
      <category>Culture &amp; Methods</category>
      <category>news</category>
      <pubDate>Thu, 07 May 2026 11:43:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/05/best-simple-system-design/?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>2026-05-07T11:43:00Z</dc:date>
      <dc:identifier>/news/2026/05/best-simple-system-design/en</dc:identifier>
    </item>
    <item>
      <title>Google Announces GKE Agent Sandbox and Hypercluster at Next '26, Positioning Kubernetes as AI Agent</title>
      <link>https://www.infoq.com/news/2026/05/gke-agent-sandbox-hypercluster/?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/gke-agent-sandbox-hypercluster/en/headerimage/generatedHeaderImage-1777875585040.jpg"/&gt;&lt;p&gt;Google announced GKE Agent Sandbox and hypercluster at Cloud Next '26. Agent Sandbox uses gVisor kernel isolation for secure agent code execution at 300 sandboxes per second, built as an open-source Kubernetes SIG Apps subproject. It is currently the only native agent sandbox among the three major hyperscalers. Hypercluster manages a million chips from a single control plane.&lt;/p&gt; &lt;i&gt;By Steef-Jan Wiggers&lt;/i&gt;</description>
      <category>Google Cloud</category>
      <category>AI Architecture</category>
      <category>Cloud</category>
      <category>Containers</category>
      <category>Cloud Native Computing Foundation</category>
      <category>Google Cloud Platform</category>
      <category>DevOps</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>Architecture &amp; Design</category>
      <category>Development</category>
      <category>news</category>
      <pubDate>Thu, 07 May 2026 10:06:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/05/gke-agent-sandbox-hypercluster/?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>2026-05-07T10:06:00Z</dc:date>
      <dc:identifier>/news/2026/05/gke-agent-sandbox-hypercluster/en</dc:identifier>
    </item>
    <item>
      <title>Leading Open Source Author Calls for Verification over Trust in Software Supply Chains</title>
      <link>https://www.infoq.com/news/2026/05/stenberg-curl-verification-trust/?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/stenberg-curl-verification-trust/en/headerimage/generatedHeaderImage-1777409230642.jpg"/&gt;&lt;p&gt;In a blog post published in March 2026, Daniel Stenberg, creator and lead developer of curl, makes the case that the software industry's default position of trusting well-known components is no longer adequate. Stenberg argues that users and organisations should actively verify the software they consume, and he uses curl's own practices as a concrete example of how that can be done.&lt;/p&gt; &lt;i&gt;By Matt Saunders&lt;/i&gt;</description>
      <category>Software Supply Chain</category>
      <category>Verification</category>
      <category>Dependency Management</category>
      <category>DevOps</category>
      <category>Culture &amp; Methods</category>
      <category>news</category>
      <pubDate>Thu, 07 May 2026 07:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/05/stenberg-curl-verification-trust/?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>2026-05-07T07:00:00Z</dc:date>
      <dc:identifier>/news/2026/05/stenberg-curl-verification-trust/en</dc:identifier>
    </item>
    <item>
      <title>LinkedIn Consolidates Hiring Data Pipelines to Power AI Driven Talent Systems</title>
      <link>https://www.infoq.com/news/2026/05/linkedin-unified-hiring-platform/?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-unified-hiring-platform/en/headerimage/generatedHeaderImage-1776925266106.jpg"/&gt;&lt;p&gt;LinkedIn introduced a unified integrations platform to standardize and reconcile hiring data across systems. The platform reduces onboarding time by 72%, improves data consistency and completeness, and enables scalable AI-driven hiring features through standardized schemas, orchestration workflows, and centralized data processing.&lt;/p&gt; &lt;i&gt;By Leela Kumili&lt;/i&gt;</description>
      <category>Platforms</category>
      <category>Hiring</category>
      <category>Evolutionary Architecture</category>
      <category>Integration</category>
      <category>Unification</category>
      <category>Data Analytics</category>
      <category>Data Pipelines</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>Development</category>
      <category>Architecture &amp; Design</category>
      <category>news</category>
      <pubDate>Wed, 06 May 2026 14:15:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/05/linkedin-unified-hiring-platform/?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>2026-05-06T14:15:00Z</dc:date>
      <dc:identifier>/news/2026/05/linkedin-unified-hiring-platform/en</dc:identifier>
    </item>
    <item>
      <title>Presentation: AI-First Software Delivery: Balancing Innovation with Proven Practices</title>
      <link>https://www.infoq.com/presentations/ai-first-practices/?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-first-practices/en/mediumimage/medium-1777371216610.jpeg"/&gt;&lt;p&gt;Wes Reisz discusses the shift toward AI-first software delivery, emphasizing that agentic workflows are not one-size-fits-all.  He explains a strategic two-by-two model based on code longevity and automated verification to decide between supervised and unsupervised agents.  He shares the RIPER-5 framework - Research, Innovate, Plan, Execute, Review - to amplify engineering discipline.&lt;/p&gt; &lt;i&gt;By Wes Reisz&lt;/i&gt;</description>
      <category>Artificial Intelligence</category>
      <category>Best Practices</category>
      <category>QCon AI 2025</category>
      <category>Transcripts</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>presentation</category>
      <pubDate>Wed, 06 May 2026 11:12:00 GMT</pubDate>
      <guid>https://www.infoq.com/presentations/ai-first-practices/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</guid>
      <dc:creator>Wes Reisz</dc:creator>
      <dc:date>2026-05-06T11:12:00Z</dc:date>
      <dc:identifier>/presentations/ai-first-practices/en</dc:identifier>
    </item>
    <item>
      <title>Attacker Bought 30 WordPress Plugins on Flippa and Backdoored All of Them</title>
      <link>https://www.infoq.com/news/2026/05/wordpress-plugins-supply-chain/?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/wordpress-plugins-supply-chain/en/headerimage/generatedHeaderImage-1777874069748.jpg"/&gt;&lt;p&gt;An attacker purchased 30+ WordPress plugins on Flippa for six figures, planted a PHP deserialization backdoor in the first commit, and waited eight months before activating it across 400,000 installations. The attack used Ethereum smart contracts to resolve C2. WordPress.org has no mechanism for reviewing plugin ownership transfers, a gap that npm and PyPI addressed years ago.&lt;/p&gt; &lt;i&gt;By Steef-Jan Wiggers&lt;/i&gt;</description>
      <category>Security Vulnerabilities</category>
      <category>Application Security</category>
      <category>Software Supply Chain</category>
      <category>Dependency Management</category>
      <category>Development</category>
      <category>Architecture &amp; Design</category>
      <category>news</category>
      <pubDate>Wed, 06 May 2026 10:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/05/wordpress-plugins-supply-chain/?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>2026-05-06T10:00:00Z</dc:date>
      <dc:identifier>/news/2026/05/wordpress-plugins-supply-chain/en</dc:identifier>
    </item>
    <item>
      <title>Google New TPU Generation is Specifically Designed for Agents and SOTA Model Training</title>
      <link>https://www.infoq.com/news/2026/05/google-8th-tpu-generation/?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/google-8th-tpu-generation/en/headerimage/google-8th-gen-tpus-1778060595193.jpeg"/&gt;&lt;p&gt;Google has unvelied a new generation of Tensor Processing Units (TPUs), featuring two specialized chips designed to accelerate model training and agent workflows, which require continuous, multi-step reasoning, and action loops distributed across multiple models. The new TPUs deliver better performance, memory, and energy efficiency, the company says.&lt;/p&gt; &lt;i&gt;By Sergio De Simone&lt;/i&gt;</description>
      <category>Agents</category>
      <category>GPU</category>
      <category>Large language models</category>
      <category>Google</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>Development</category>
      <category>news</category>
      <pubDate>Wed, 06 May 2026 10:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/05/google-8th-tpu-generation/?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>2026-05-06T10:00:00Z</dc:date>
      <dc:identifier>/news/2026/05/google-8th-tpu-generation/en</dc:identifier>
    </item>
    <item>
      <title>Article: Beyond the Benchmark: A Metrics-Driven Approach to Sustained iOS Performance on Real Devices</title>
      <link>https://www.infoq.com/articles/metrics-driven-approach-ios-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/articles/metrics-driven-approach-ios-performance/en/headerimage/metrics-driven-approach-ios-performance-header-1777624958302.jpg"/&gt;&lt;p&gt;iOS performance engineering often defaults to a mental model where performance is a property of a component. Performance is instead an emergent behavior of the interaction between application code, device hardware, OS resource management, network conditions, and user behavior patterns over time. This article gives a direct, first-party path to capturing performance issues using Xcode Instruments.&lt;/p&gt; &lt;i&gt;By Vasuki Uday Kiran Vudathala&lt;/i&gt;</description>
      <category>User Experience</category>
      <category>Xcode</category>
      <category>Mobile</category>
      <category>iOS</category>
      <category>Performance</category>
      <category>Development</category>
      <category>article</category>
      <pubDate>Wed, 06 May 2026 09:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/articles/metrics-driven-approach-ios-performance/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</guid>
      <dc:creator>Vasuki Uday Kiran Vudathala</dc:creator>
      <dc:date>2026-05-06T09:00:00Z</dc:date>
      <dc:identifier>/articles/metrics-driven-approach-ios-performance/en</dc:identifier>
    </item>
    <item>
      <title>Grafana's Kubernetes Monitoring Helm Chart v4 Brings Multiple Fixes</title>
      <link>https://www.infoq.com/news/2026/05/kubernetes-monitoring-helm/?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/kubernetes-monitoring-helm/en/headerimage/generatedHeaderImage-1777406799196.jpg"/&gt;&lt;p&gt;Grafana Labs has released version 4 of its Kubernetes Monitoring Helm chart, describing it as the most significant update the chart has received since its introduction. The release, announced in April 2026 by Pete Wall and Beverly Buchanan, addresses a range of configuration problems that had accumulated as users scaled to larger and more complex deployments.&lt;/p&gt; &lt;i&gt;By Matt Saunders&lt;/i&gt;</description>
      <category>Kubernetes</category>
      <category>Monitoring</category>
      <category>helm</category>
      <category>DevOps</category>
      <category>news</category>
      <pubDate>Wed, 06 May 2026 07:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/05/kubernetes-monitoring-helm/?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>2026-05-06T07:00:00Z</dc:date>
      <dc:identifier>/news/2026/05/kubernetes-monitoring-helm/en</dc:identifier>
    </item>
    <item>
      <title>Inside Claude Code Auto Mode: Anthropic’s Autonomous Coding System with Human Approval Gates</title>
      <link>https://www.infoq.com/news/2026/05/anthropic-claude-code-auto-mode/?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/anthropic-claude-code-auto-mode/en/headerimage/generatedHeaderImage-1777787075311.jpg"/&gt;&lt;p&gt;Anthropic has introduced auto mode in Claude Code, enabling multi-step software development workflows with reduced manual intervention. The feature combines automated execution with layered safety mechanisms, including input filtering, action evaluation, and two-stage classification, while maintaining human approval checkpoints for sensitive operations.&lt;/p&gt; &lt;i&gt;By Leela Kumili&lt;/i&gt;</description>
      <category>autonomous</category>
      <category>AI Architecture</category>
      <category>AI Development</category>
      <category>Developer Experience</category>
      <category>Anthropic</category>
      <category>AI Assisted Coding</category>
      <category>Claude</category>
      <category>AI Coding</category>
      <category>Orchestration</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>Development</category>
      <category>Architecture &amp; Design</category>
      <category>news</category>
      <pubDate>Tue, 05 May 2026 14:38:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/05/anthropic-claude-code-auto-mode/?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>2026-05-05T14:38:00Z</dc:date>
      <dc:identifier>/news/2026/05/anthropic-claude-code-auto-mode/en</dc:identifier>
    </item>
    <item>
      <title>Presentation: How Netflix Shapes our Fleet for Efficiency and Reliability</title>
      <link>https://www.infoq.com/presentations/strategy-workload-hardware/?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/strategy-workload-hardware/en/mediumimage/medium-1777370214319.jpg"/&gt;&lt;p&gt;The speakers explain the inherent tension between service efficiency and reliability at Netflix's global scale. They share a mental model for "risk-adjusted net value," moving beyond simple CPU utilization to focus on capacity buffers. They discuss hardware shaping, proactive traffic steering, and reactive levers like "hammers" and prioritized load shedding to protect critical playback.&lt;/p&gt; &lt;i&gt;By Joseph Lynch, Argha C&lt;/i&gt;</description>
      <category>Resilience</category>
      <category>QCon San Francisco 2025</category>
      <category>Hardware</category>
      <category>Case Study</category>
      <category>Transcripts</category>
      <category>DevOps</category>
      <category>presentation</category>
      <pubDate>Tue, 05 May 2026 14:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/presentations/strategy-workload-hardware/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</guid>
      <dc:creator>Joseph Lynch, Argha C</dc:creator>
      <dc:date>2026-05-05T14:00:00Z</dc:date>
      <dc:identifier>/presentations/strategy-workload-hardware/en</dc:identifier>
    </item>
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