For aleph alpha infrastructure and model engineering teams
Aleph Alpha Scaling: find the error before a training collective stalls.
Review the parallelism configuration and earliest rank exception together. Distinguish setup and memory evidence from a later collective timeout.
Free 30-day Team evaluation. No card or automatic subscription. Work email verification required.
Replay a resolved Aleph Alpha 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: Which parallel training stage failed first? Only attribute a process, rank, device or recovery state when the submitted evidence establishes it.
Which parallel training stage failed first?
Evidence to compare: Per-rank logs, parallelism configuration and the first failing operation.
A pipeline peer can wait after another rank exits. Rank attribution requires identifiers in the submitted evidence, not an assumption based on the loudest timeout.
Did the environment fail before model execution?
Evidence to compare: Library revision, dependency versions and startup traceback.
The repository documents CUDA and extension dependencies. An import or extension failure must be separated from a live distributed communication fault.
Does the evidence support a memory or precision change?
Evidence to compare: The actual allocation or non-finite exception and relevant configuration.
A timeout alone does not justify changing precision or sharding. Compare the initiating error and a known good configuration before proposing a bounded next check.
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
