<?xml version="1.0" encoding="UTF-8"?>
<rss xmlns:dc="http://purl.org/dc/elements/1.1/" version="2.0">
  <channel>
    <title>InfoQ - Incident Response - News</title>
    <link>https://www.infoq.com</link>
    <description>InfoQ Incident Response News feed</description>
    <item>
      <title>More Incidents Don't Necessarily Mean Less Reliability</title>
      <link>https://www.infoq.com/news/2026/08/incidents-reliability-metrics/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Incident+Response-news</link>
      <description>&lt;img src="https://res.infoq.com/news/2026/08/incidents-reliability-metrics/en/headerimage/generatedHeaderImage-1785853951990.jpg"/&gt;&lt;p&gt;One of the most common assumptions in engineering leadership is that a rising number of reported incidents signals declining system reliability. However, a recent article from Great Circle argues that the opposite is often true: an increase in incident counts may actually indicate that an organization's incident management culture is improving.&lt;/p&gt; &lt;i&gt;By Craig Risi&lt;/i&gt;</description>
      <category>Service Reliability</category>
      <category>Metrics</category>
      <category>Incident Response</category>
      <category>Observability</category>
      <category>DevOps</category>
      <category>news</category>
      <pubDate>Fri, 14 Aug 2026 12:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/08/incidents-reliability-metrics/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Incident+Response-news</guid>
      <dc:creator>Craig Risi</dc:creator>
      <dc:date>2026-08-14T12:00:00Z</dc:date>
      <dc:identifier>/news/2026/08/incidents-reliability-metrics/en</dc:identifier>
    </item>
    <item>
      <title>Stripe Uses Graph Search and State Machines to Automate Database Remediation</title>
      <link>https://www.infoq.com/news/2026/08/database-remediation-graph/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Incident+Response-news</link>
      <description>&lt;img src="https://res.infoq.com/news/2026/08/database-remediation-graph/en/headerimage/generatedHeaderImage-1785167911858.jpg"/&gt;&lt;p&gt;The engineering team at Stripe recently described how they automated database incident recovery by modeling their global infrastructure as a graph. Using graph search algorithms together with state machines, the team computes and executes remediation plans automatically.&lt;/p&gt; &lt;i&gt;By Renato Losio&lt;/i&gt;</description>
      <category>GraphDB</category>
      <category>MongoDB</category>
      <category>State-machine</category>
      <category>Database</category>
      <category>Site Reliability Engineering</category>
      <category>Incident Response</category>
      <category>Architecture &amp; Design</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>DevOps</category>
      <category>news</category>
      <pubDate>Sun, 09 Aug 2026 06:55:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/08/database-remediation-graph/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Incident+Response-news</guid>
      <dc:creator>Renato Losio</dc:creator>
      <dc:date>2026-08-09T06:55:00Z</dc:date>
      <dc:identifier>/news/2026/08/database-remediation-graph/en</dc:identifier>
    </item>
    <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=Incident+Response-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>Operational Intelligence</category>
      <category>Developer Experience</category>
      <category>Slack</category>
      <category>Incident Response</category>
      <category>Platform Engineering</category>
      <category>Observability</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=Incident+Response-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=Incident+Response-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>Observability</category>
      <category>Incident Response</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=Incident+Response-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>
  </channel>
</rss>
