# Can duration_drift catch a slowdown that happens gradually, not all at once?

Yes, because duration_drift checks two references at once, and each one is blind to what the other catches. One is the call site's rolling recent normal, which catches a sudden break like a deploy that doubles latency overnight. The other is pinned at the last deploy, a fixed point rather than a moving one, so a change that inches up over weeks still reads as far from where things stood at launch.

A rolling baseline alone would absorb slow creep a little each window until slow became the new normal with no finding ever firing. A pinned baseline alone would keep flagging a change forever, since it never resets. Running both means creep gets caught by the one that doesn't move, and a real break gets caught fast by the one that does. Only a person resets the pin, once they've confirmed the new normal is actually fine.

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Source: https://tessary.ai/answers/tessary-duration-drift/can-duration-drift-catch-a-gradual-slowdown
More on Tessary duration drift: https://tessary.ai/answers/tessary-duration-drift
From Tessary, agent reliability for AI agents in production: https://tessary.ai