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      <title>Inside Netflix’s Graph Abstraction: Handling 650TB of Graph Data in Milliseconds Globally</title>
      <link>https://www.infoq.com/news/2026/03/netflix-graph-abstraction/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=gRPC</link>
      <description>&lt;img src="https://res.infoq.com/news/2026/03/netflix-graph-abstraction/en/headerimage/netflixgrapharchitecure-1773194590219.jpeg"/&gt;&lt;p&gt;Netflix engineers built Graph Abstraction, a high-throughput platform managing 650 TB of graph data with millisecond latency. Supporting services from Netflix Gaming’s social graphs to operational topology graphs, it maintains global availability via asynchronous replication. This article covers its architecture, caching, and traversal design for high-scale performance.&lt;/p&gt; &lt;i&gt;By Leela Kumili&lt;/i&gt;</description>
      <category>Caching</category>
      <category>Low Latency</category>
      <category>Clustering &amp; Caching</category>
      <category>Distributed Systems</category>
      <category>Abstraction</category>
      <category>KVM</category>
      <category>gRPC</category>
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      <pubDate>Mon, 23 Mar 2026 13:54:00 GMT</pubDate>
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      <dc:creator>Leela Kumili</dc:creator>
      <dc:date>2026-03-23T13:54:00Z</dc:date>
      <dc:identifier>/news/2026/03/netflix-graph-abstraction/en</dc:identifier>
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    <item>
      <title>HubSpot’s Sidekick: Multi-Model AI Code Review with 90% Faster Feedback and 80% Engineer Approval</title>
      <link>https://www.infoq.com/news/2026/03/hubspot-ai-code-review-agent/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=gRPC</link>
      <description>&lt;img src="https://www.infoq.com/styles/static/images/logo/logo_bigger.jpg"/&gt;&lt;p&gt;HubSpot engineers introduced Sidekick, an internal AI powered code review system that analyzes pull requests using large language models and filters feedback through a secondary “judge agent.” The system reduced time to first feedback on pull requests by about 90 percent and is now used across tens of thousands of internal pull requests.&lt;/p&gt; &lt;i&gt;By Leela Kumili&lt;/i&gt;</description>
      <category>OpenAI</category>
      <category>Java</category>
      <category>Agents</category>
      <category>Claude</category>
      <category>Gemini</category>
      <category>Code Reviews</category>
      <category>Frameworks</category>
      <category>Anthropic</category>
      <category>gRPC</category>
      <category>github</category>
      <category>Workflow / BPM</category>
      <category>Development</category>
      <category>Architecture &amp; Design</category>
      <category>Culture &amp; Methods</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>news</category>
      <pubDate>Wed, 18 Mar 2026 14:38:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/03/hubspot-ai-code-review-agent/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=gRPC</guid>
      <dc:creator>Leela Kumili</dc:creator>
      <dc:date>2026-03-18T14:38:00Z</dc:date>
      <dc:identifier>/news/2026/03/hubspot-ai-code-review-agent/en</dc:identifier>
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