<?xml version="1.0" encoding="UTF-8"?>
<rss xmlns:dc="http://purl.org/dc/elements/1.1/" version="2.0">
  <channel>
    <title>InfoQ - Observability - News</title>
    <link>https://www.infoq.com</link>
    <description>InfoQ Observability News feed</description>
    <item>
      <title>Instacart Builds Blueberry, an AI-Powered Assistant to Help On-Call Engineers Investigate Incidents</title>
      <link>https://www.infoq.com/news/2026/08/instacart-blueberry-sre-ai/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Observability-news</link>
      <description>&lt;img src="https://res.infoq.com/news/2026/08/instacart-blueberry-sre-ai/en/headerimage/generatedHeaderImage-1785721280661.jpg"/&gt;&lt;p&gt;Instacart introduced Blueberry, an AI-assisted incident response system that helps on-call engineers investigate production issues faster. It combines AI agents, operational data, and historical incident knowledge to generate grounded root cause hypotheses in Slack. It uses parallel subagents, MCP integrations, and incident history to reduce investigation time while keeping engineers in control.&lt;/p&gt; &lt;i&gt;By Leela Kumili&lt;/i&gt;</description>
      <category>Distributed Systems</category>
      <category>Reliability</category>
      <category>Large language models</category>
      <category>Artificial Intelligence</category>
      <category>Site Reliability Engineering</category>
      <category>Model Context Protocol (MCP)</category>
      <category>Developer Experience</category>
      <category>Operational Intelligence</category>
      <category>Slack</category>
      <category>Observability</category>
      <category>Platform Engineering</category>
      <category>Incident Response</category>
      <category>Development</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>DevOps</category>
      <category>Architecture &amp; Design</category>
      <category>news</category>
      <pubDate>Fri, 07 Aug 2026 14:34:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/08/instacart-blueberry-sre-ai/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Observability-news</guid>
      <dc:creator>Leela Kumili</dc:creator>
      <dc:date>2026-08-07T14:34:00Z</dc:date>
      <dc:identifier>/news/2026/08/instacart-blueberry-sre-ai/en</dc:identifier>
    </item>
    <item>
      <title>AI Is Transforming Incident Response - but the Hardest Problems May Still Belong to Humans</title>
      <link>https://www.infoq.com/news/2026/08/ai-incident-response/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Observability-news</link>
      <description>&lt;img src="https://res.infoq.com/news/2026/08/ai-incident-response/en/headerimage/generatedHeaderImage-1785503516175.jpg"/&gt;&lt;p&gt;Artificial intelligence is rapidly changing how engineering teams respond to production incidents, offering the ability to summarize incident channels, analyze unfamiliar code, suggest remediation steps, generate pull requests, and increasingly assist with diagnosis.&lt;/p&gt; &lt;i&gt;By Craig Risi&lt;/i&gt;</description>
      <category>Artificial Intelligence</category>
      <category>Incident Response</category>
      <category>Observability</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>DevOps</category>
      <category>news</category>
      <pubDate>Fri, 07 Aug 2026 12:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/08/ai-incident-response/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Observability-news</guid>
      <dc:creator>Craig Risi</dc:creator>
      <dc:date>2026-08-07T12:00:00Z</dc:date>
      <dc:identifier>/news/2026/08/ai-incident-response/en</dc:identifier>
    </item>
    <item>
      <title>HubSpot Redesigns JITA Authorization with Rule Engine Architecture</title>
      <link>https://www.infoq.com/news/2026/08/hubspot-jita-rule-engine/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Observability-news</link>
      <description>&lt;img src="https://res.infoq.com/news/2026/08/hubspot-jita-rule-engine/en/headerimage/generatedHeaderImage-1785708273545.jpg"/&gt;&lt;p&gt;HubSpot has redesigned its Just-In-Time Access (JITA) authorization system using a rule engine architecture. The system evaluates access requests through independent rules organized as a directed acyclic graph, adding structured decision metadata, rule-level observability, and governance workflows to replace complex conditional authorization logic.&lt;/p&gt; &lt;i&gt;By Leela Kumili&lt;/i&gt;</description>
      <category>Cloud Migration</category>
      <category>RightScale</category>
      <category>Architecture</category>
      <category>Workflow / BPM</category>
      <category>Rules Engines</category>
      <category>Governance</category>
      <category>Metrics</category>
      <category>Authorization</category>
      <category>Business Rules Engines</category>
      <category>Observability</category>
      <category>Development</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>Architecture &amp; Design</category>
      <category>news</category>
      <pubDate>Mon, 03 Aug 2026 13:59:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/08/hubspot-jita-rule-engine/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Observability-news</guid>
      <dc:creator>Leela Kumili</dc:creator>
      <dc:date>2026-08-03T13:59:00Z</dc:date>
      <dc:identifier>/news/2026/08/hubspot-jita-rule-engine/en</dc:identifier>
    </item>
  </channel>
</rss>
