Skip to main content

​
DeploymentSpec

New files declare the stable v1 file contract:
Pre-v1 files without the header are interpreted as v1. Unknown versions, kinds, and fields fail closed. See Upgrade and compatibility for the change policy. The primary path uses defaults:
The YAML form groups model, runtime, compute, provider, resources, scaling, and routing concerns. Mutable model revisions such as main are resolved and persisted as immutable Hugging Face commits before provisioning.
name identifies the deployment lifecycle. endpoint identifies the stable application-facing route and defaults to name when omitted. A new deployment revision can therefore replace the serving plan underneath support-production without changing application configuration. SGLang uses a built-in immutable workload profile. Custom OCI images declare the full contract in runtime.workload; see Custom OCI workloads. Mutable image tags and underspecified probes are rejected before provisioning. An optional serving object describes an advanced backend topology without exposing provider CRD shape to the core schema. Today backend: dynamo requires one outer graph replica, Kubernetes, and the kubernetes-dynamo adapter. See NVIDIA Dynamo for the simple command and the complete reviewable YAML form. compute.mode defaults to elastic; elastic replica bounds default to 1..1. Serverless requires min_replicas: 0 and defaults max_replicas to one when omitted. Revisions are immutable; changing a field creates a candidate. provider.adapter persists the exact implementation when more than one profile can serve a cloud/runtime pair; it is optional for an unambiguous default. Current executable elastic defaults include configured AWS EC2 and GCP Compute, while other provider-product profiles remain registered but deferred until their exact combination is qualified. AWS and GCP require an explicit provider.region. Cost is omitted unless a trustworthy provider measurement exists. resources.gpu_count is the number of accelerators allocated to each runtime replica and defaults to one. It is part of immutable intent, pricing, capacity history, benchmarks, recommendations, and inference passports. SkyPilot, GCP Compute, and Kubernetes compile the exact count into provider resources. AWS EC2 binds the count to INFERCRANE_AWS_GPU_COUNT for the configured instance type and rejects a mismatch before creating paid capacity. Serverless currently supports one accelerator per worker and rejects any other count explicitly.