DevOps & Cloud · By ai-dynamo

Selects and freezes a question-driven AIPerf workload, objective, load policy, and Kubernetes execution manifest for a successfully deployed Dynamo candidate.

ai-dynamo/dynamo

Deploys one assigned DynamoGraphDeployment and proves it with an OpenAI-compatible smoke test.

ai-dynamo/dynamo

Materializes one evidence-backed proposal from a flexible knowledge-consult.md into a challenger-ready deploy-draft.yaml by applying only its selected DGD change to the current successful manifest.

ai-dynamo/dynamo

Answers "for this model, this hardware, this GPU budget and this workload, what is the best known serving configuration, and how much do I trust it?" by walking an ordered set of recipe catalogs…

ai-dynamo/dynamo

Adversarially reviews an evidence-backed Dynamo optimization proposal and DGD draft for comparability, duplication, attribution, correctness, feasibility, and worthwhile GPU spend.

ai-dynamo/dynamo

Synthesizes a canonical userworkload.yaml and captures the user's immutable DynamoGraphDeployment from an optimization user's initial request, attachments, and minimal follow-up interview.

ai-dynamo/dynamo

Validates and normalizes raw AIPerf outputs, then evaluates valid results against target SLOs and comparable prior candidates.

ai-dynamo/dynamo

Drafts a candidate baseline DynamoGraphDeployment from interview requirements when no catalog recipe matches the user's model, hardware, and backend, presenting per-decision evidence for the user's…

ai-dynamo/dynamo

Launches, monitors, debugs, and collects one run-scoped AIPerf Kubernetes benchmark without changing its workload semantics.

ai-dynamo/dynamo