For bentoml infrastructure and platform teams
BentoML: worker replication or GPU assignment?
Connect the first useful exception with the relevant runtime evidence. Did multiple workers load separate model copies on one GPU?
Free 30-day Team evaluation. No card or automatic subscription. Work email verification required.
Replay a resolved BentoML workflow incident
Upload your log file. Review the selected evidence and masking, then run diagnosis. Keep the original log for any follow-up questions.
Before uploading, review cloud data handling and local options.
Upload your log file. Large files are processed in your browser. Only selected evidence is submitted when you run diagnosis.
Try Denpex for 30 days. FREE.
No credit card. No automatic subscription. See whether Denpex helps with an incident you already understand.
Start your free 30-day Team evaluation
Up to 50 diagnoses a day for 30 days. Verify your work email to activate an eligible company evaluation, then replay a resolved incident and compare the evidence and next steps with your team's confirmed cause.
What a useful evaluation should establish
Compare one incident your team already resolved with the first failure, cited evidence and remaining questions. Did multiple workers load separate model copies on one GPU? Only assign a rank, device or safe recovery state when the submitted evidence establishes it.
Did multiple workers load separate model copies on one GPU?
Evidence to compare: Service worker count, per-process model loads and actual device assignment.
Replication changes memory demand even when a resource declaration is unchanged. Check process-to-device mapping before assuming one model instance exhausted the device.
Did the container expose the expected runtime and device?
Evidence to compare: Container image revision, device visibility and first library initialization error.
Host and container environments can differ. Confirm the failing process context before interpreting a missing library or unavailable device as a hardware fault.
Did host memory or device memory run out?
Evidence to compare: Container or scheduler host-memory limit, process kill evidence and first allocation exception.
Host memory and device memory are different resources. A host-memory kill needs different evidence from a GPU allocator failure; identify the failed operation before changing a limit.
Use Denpex alongside your existing telemetry tools to investigate submitted incident evidence. With monitoring configured on a supported plan, detected failures can trigger alerts and an automatic diagnosis from the captured evidence.
Inside Denpex
See the evidence, not just the claim
Follow the causal chain, inspect the quoted evidence and prepare the next handoff. These actual product captures use founder-account examples and the VS Code extension, with the source identified under each image. Open a capture to inspect it at full size.
Follow the failure through the cascade

Prepare the hardware escalation

Ask for the evidence that is missing

Keep the investigation in the editor
