Mark học AI

Video #85 · Behind the scenes of an AI system · Part 7/7

What is AI system monitoring? Dashboards, alerts and drift

Ten at night, the on-call engineer's phone buzzes: an alert from the monitoring system.

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Ten at night

Ten at night, the on-call engineer's phone buzzes. An alert from the monitoring system.

DASHBOARD

The tracking board

The dashboard shows numbers called metrics: response speed, cost per hour, refusal rate, and how often customers click "not satisfied".

ALERT

Cross the line, the alarm rings

Each metric has a red line. When the needle crosses it, an alert rings, and the person on call takes a look right away.

TONIGHT

What happened?

Tonight, the "not satisfied" rate tripled. The engineer opens the logs and follows the trace, as in part six. It turns out the bank just launched a new card, customers are asking about it, and the documents don't cover it yet.

DRIFT

The world changes, the system stands still

That's drift: the world changes, users ask new kinds of questions, but the system stays the same.

FEEDBACK LOOP

Incidents become test questions

After the fix, they add questions about the new card to the eval set. The loop closes, called a feedback loop: incidents become lessons, and lessons become test questions.

RECAP

The whole series in one picture

The whole series in one picture: cloud, input guardrails, output guardrails, evaluation, logging, monitoring. Every two-second answer has a whole assembly line behind it.

This article is based on the video Monitoring: AI's control room from the Mark học AI channel. Watch the video (in Vietnamese) to see the animations.