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 a known-good point that only a person moves, so a change that inches up over weeks still reads as far from where things stood when the pin was set.

A rolling baseline on its own would absorb slow creep, a little each window, until slow was the new normal and nothing ever fired. A pinned baseline on its own would keep flagging forever, since it never resets by itself.

Both need history before either can say anything. A call site with too few comparable turns has no baseline to compare against, so a freshly tagged one stays quiet while the sample count climbs.

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Two ways to run Tessary.

Tessary is an open-source agent reliability platform. Cloud and self-hosted run the same workflow on the OpenTelemetry traces your agent already emits.

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docker compose -f oci://docker.io/tessaryai/tessary:compose up -d -y