For hyperstack infrastructure and model engineering teams
Hyperstack Docker cannot select a GPU driver: container runtime or CUDA?
Compare the chosen image, Docker runtime and first container error. A container that cannot request a GPU is different from a model that starts and then fails.
Free 30-day Team evaluation. No card or automatic subscription. Work email verification required.
Replay a resolved Hyperstack 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 the first failure, quoted evidence and unresolved questions with an incident your team has already resolved. Begin with this question: Can the container runtime expose the assigned GPU? Only attribute a process, rank, device or recovery state when the submitted evidence establishes it.
Can the container runtime expose the assigned GPU?
Evidence to compare: Image revision, Docker runtime configuration and the GPU-selection error.
A missing container-runtime capability occurs before model execution. Do not diagnose model memory usage from a container that never acquired GPU access.
Does the application fail after startup?
Evidence to compare: The first worker initialization result and subsequent CUDA exception.
If the runtime boundary is healthy, the application needs its own evidence. Keep those phases separate instead of treating every CUDA-related message as the same fault.
Which configuration is supported by the provider?
Evidence to compare: The deployed base image and relevant driver/toolkit compatibility reference.
A preconfigured image establishes a supported baseline. A useful incident comparison records deviations without blindly reinstalling drivers on a shared or active workload.
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
