At scale, understanding performance in a distributed system means seeing beyond metrics and into real production execution.
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How Production Runtime Context Makes AI Agents More Reliable
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Latency Monitoring Strategies for High-Traffic Applications
Discover proven latency monitoring techniques to optimize performance, reduce downtime, and ensure seamless UX in high-traffic apps.
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Trusted by engineers.
Human & artificial alike.
Hud runs on millions of services across massive production environments, with negligible overhead.
“Hud eliminated our voodoo incidents. AI-powered root cause analysis turned days of drilling through tools into minutes.”
“Hud completely changed how early we detect, and how quickly we solve issues long before they impact the business.”
“AI helps us move faster only when it’s grounded in reality. Having accurate runtime context means our engineers, and our AI workflows, can reason about real production behavior and act on it safely.”
“We knew the crashes were caused by an ELU spike, but the question was what caused that spike. Using Hud, we found the answer in minutes with an AI-ready fix.”
“When engineering decisions are grounded in real execution data, it changes how confidently we ship, scale, and invest. That level of certainty directly supports the business as the platform continues to grow.”
