clef-serve was parked at 0 while candle-vllm took a card. worker-1 holds
four V100s, so the coder takes one and clef takes one, leaving two free
for a TP=2 candle run.
The gateway already routes the clef-flash model to clef-serve:80 on
/v1/systemone, so this single replica count is what turns that route on.
The Clef runtime was running from hand-applied objects that existed only in the cluster.
A rebuild would have lost it.
Three things move into git:
- clef-serve.yaml: the Deployment and the Service the gateway routes to
- configMapGenerator for clef-serve/app.py, so an edit to the code rolls the pod
instead of leaving a stale copy mounted
- clef-flash.yaml is deleted: it described an SGLang predictor that cannot run on a
V100, and its slot is now clef-serve.yaml
Recorded in the manifest, because both cost hours: SGLang needs CUDA 13 for Clef and
CUDA 13 has no sm_70 kernels, and device_map over two cards breaks the forward pass with
'indices should be either on cpu or on the same device as the indexed tensor'.
Still open and written down in the file: the image cannot be pushed, because Cloudflare
answers 413 for layers above 100 MB. So each start pip-installs and needs PyPI.
rock