AWS-native incident investigation PoC

<p><em>Authored by Marco Aquilanti</em></p> <p>When a monitor fires, there's a familiar sequence of checks required to find the root cause. The engineers who set up the monitor

<h2> Introduction </h2> <p>AI coding assistants like GitHub Copilot, Cursor, Codeium, and Amazon CodeWhisperer now power a significant portion of modern software development and

<p>IncidentMind: Giving AI Agents Persistent Memory for Incident Resolution</p> <p>Modern AI agents can analyze incidents, inspect system metrics, and recommend troubleshooting

<p>I’ve seen enough postmortems to know that a large percentage of them are essentially polite fiction.</p> <p>We sit in a meeting, everyone is exhausted from the outage, and we

<p>In Part 3, we separated signals on purpose: </p> <ul> <li> <strong>metrics</strong> tell you <em>where to look</em> </li> <li> <strong>logs and traces</strong> tell you

<p>Most LLM API error handling starts out looking like normal HTTP error handling.</p> <p>If it is a <code>429</code>, retry later.</p> <p>If it is a <code>500</code>, retry with