Why Retries Are More Dangerous Than Failures in Production Systems

<p>Not every failure is permanent.</p> <p>This is something I didn't think about before. When something fails in my app, my first thought was something broke, fix it. But when I

<p>In distributed systems, failure is not an exception—it’s the default.</p> <p>Network calls fail. Services timeout. APIs return 500s. The real question isn’t <em>“Will things

<p>Four agents entered an infinite loop in November 2025. They ran for 11 days. The bill was $47,000. Nobody noticed until it was over.</p> <p>The team was running a market

<h1> Production Was Down… But Everything Looked Normal 🤯 </h1> <blockquote> <p>A real debugging story about silent failures and why thinking matters more than tools.</p>

<p>Sarvar's post about discovering a hidden retry in a 5-agent pipeline (one agent taking 22.6s while others took 5s) is a perfect case study in why observability infrastructure

<p>Most applications don't fail because of bad code.</p> <p>They fail because of bad architecture decisions made early that nobody questioned <br /> until it was too late.</p>

<p>You've heard of DevOps. You've heard of AIOps. You've probably heard of MLOps.</p> <p>But there's a category that doesn't exist yet — and it's the one the AI industry needs

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