Components · AI pipeline

Model router

Sends easy requests to a cheap model, hard ones to a big one.

Lesson
Coming soon
Zone
ai
Place it
7 cr on the blank canvas, free inside a problem

At a glance

Did you know
A router sends easy requests to small, cheap models and hard ones to larger models.
Rule of thumb
Measure quality per route: savings that hurt answers are not savings.
Watch out
Misrouting; the cheap path fails and falls back.

Its settings in ScaleMySystems

What you can change on it in the lab, and what each number does.

Concurrency (slots)
Calls it can work on at once (per instance when autoscaling). Needed slots ≈ calls per second × seconds each takes. Extra calls wait in the queue, then are rejected.
Queue capacity
Calls allowed to wait for a free slot. A bigger queue absorbs bursts but adds waiting time; 0 rejects straight away.
Latency (p50) (ms)
Typical time one call takes here, before any calls it makes itself. Slots are held for this long.
Latency (p99) (ms)
The slowest 1% of calls. Callers must set their timeout above this or they cut off healthy calls.

Problems that start with it

  • Model routing sends everything to the big model A router splits traffic between a large model and a small one, but it is set to send 90% of chats to the large model, which has 200 concurrent streams. 60 chats arrive a second.
  • A/B test of a new model version An experiment splits chats 50/50 between the current model (A) and a new version (B). B was deployed with only 60 concurrent streams; 40 chats arrive a second.

Full lesson coming soon

Lessons are being added one component at a time: how it works, its settings, a live exercise to break and fix it, interview questions and a short check. See the Circuit breaker lesson for what one looks like.