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API Reference

Complete reference for using the AICR API Server.

Overview

The AICR API Server provides HTTP REST access to recipe generation and bundle creation for GPU-accelerated infrastructure. Use the API for programmatic access to configuration recommendations and deployment artifacts.

Version numbers in the sample requests and responses below (server version, chart versions, driver versions) are illustrative. The authoritative, current versions are in the Component Catalog and the Container Images BOM.

┌──────────────┐      ┌──────────────┐
│ GET /recipe  │─────▶│   Recipe     │
└──────────────┘      └──────────────┘
        │
        ▼
┌──────────────┐      ┌──────────────┐
│ POST /bundle │─────▶│  bundles.zip │
└──────────────┘      └──────────────┘

API vs CLI

  • Use the API for remote recipe generation and bundle creation
  • Use the CLI for local operations, snapshot capture, and ConfigMap integration
Feature API CLI
Recipe generation ✅ GET/POST /v1/recipe; profile- and Slurm-accounting-aware GET/POST /v2/recipe ✅ aicr recipe
Value query ✅ GET/POST /v1/query; profile- and Slurm-accounting-aware GET/POST /v2/query ✅ aicr query
Bundle creation ✅ POST /v1/bundle; profile- and Slurm-accounting-aware POST /v2/bundle ✅ aicr bundle
Bundle attestation ✅ POST /v1/bundle?attest=true; profile- and Slurm-accounting-aware POST /v2/bundle?attest=true (server signs as itself) ✅ aicr bundle --attest (interactive or ambient OIDC)
Snapshot capture ❌ Use CLI ✅ aicr snapshot
ConfigMap I/O ❌ Use CLI ✅ cm:// URIs
Agent deployment ❌ Use CLI ✅ aicr snapshot

Base URL

Local development (example):

http://localhost:8080

Start the local server:

docker pull ghcr.io/nvidia/aicrd:latest
docker run -p 8080:8080 ghcr.io/nvidia/aicrd:latest

Quick Start

Get a Recipe

Generate an optimized configuration recipe for your environment:

# GET: Basic recipe for H100 on EKS (query parameters)
curl "http://localhost:8080/v1/recipe?accelerator=h100&service=eks"

# GET: Training workload on Ubuntu
curl "http://localhost:8080/v1/recipe?accelerator=h100&service=eks&intent=training&os=ubuntu"

# POST: Recipe from criteria file (YAML body)
curl -X POST "http://localhost:8080/v1/recipe" \
  -H "Content-Type: application/x-yaml" \
  -d 'kind: RecipeCriteria
apiVersion: aicr.run/v1alpha2
metadata:
  name: my-config
spec:
  service: eks
  accelerator: h100
  intent: training'

# Save recipe to file
curl -s "http://localhost:8080/v1/recipe?accelerator=h100&service=eks" -o recipe.json

Generate Bundles

Create deployment bundles from a recipe:

# Pipe recipe directly to bundle endpoint.
# The POST body must be a fully-hydrated RecipeResult; piping GET /v1/recipe
# output (as below) supplies one. Do not hand-author a partial body.
curl -s "http://localhost:8080/v1/recipe?accelerator=h100&service=eks" | \
  curl -X POST "http://localhost:8080/v1/bundle" \
    -H "Content-Type: application/json" -d @- -o bundles.zip

# Extract the bundles
unzip bundles.zip -d ./bundles

# Verify the complete extracted inventory before deployment
(cd ./bundles && aicr verify .)

Endpoints

GET /

Service information and available routes.

curl "http://localhost:8080/"

Response:

{
  "service": "aicrd",
  "version": "v0.14.0",
  "routes": [
    "/v1/recipe", "/v1/query", "/v1/bundle",
    "/v2/recipe", "/v2/query", "/v2/bundle"
  ]
}

GET /v1/recipe

Generate an optimized configuration recipe based on environment parameters.

Query Parameters:

Parameter Type Default Description
service string any K8s service: eks, gke, aks, oke, ocp, kind, lke, bcm, any
accelerator string any GPU type: h100, h200, gb200, b200, a100, l40, l40s, rtx-pro-6000, any
gpu string any Alias for accelerator
intent string any Workload: training, inference, any
os string any Node OS: ubuntu, rhel, cos, amazonlinux, ol, talos, any
platform string any Platform/framework: dynamo, kubeflow, nim, runai, slurm, any
nodes integer 0 GPU node count (0 = any)

Examples:

# Minimal request
curl "http://localhost:8080/v1/recipe"

# Specify accelerator
curl "http://localhost:8080/v1/recipe?accelerator=h100"

# Full specification
curl "http://localhost:8080/v1/recipe?service=eks&accelerator=h100&intent=training&os=ubuntu&nodes=8"

# Using gpu alias. Note: the profiled families (service=aks, service=gke)
# are rejected on /v1 — use /v2/recipe for those (see the AKS/GKE
# cut-over note below).
curl "http://localhost:8080/v1/recipe?gpu=gb200&service=eks&os=ubuntu"

# Pretty print with jq
curl -s "http://localhost:8080/v1/recipe?accelerator=h100" | jq '.'

POST /v1/recipe

Generate an optimized configuration recipe from a criteria file body. This endpoint provides an alternative to query parameters, accepting a Kubernetes-style RecipeCriteria resource in the request body.

Content Types:

  • application/json - JSON format
  • application/x-yaml - YAML format

Request Body:

The request body must be a RecipeCriteria resource:

kind: RecipeCriteria
apiVersion: aicr.run/v1alpha2
metadata:
  name: my-criteria
spec:
  service: eks
  accelerator: gb200
  os: ubuntu
  intent: training
  platform: kubeflow
  nodes: 8

Examples:

# POST with YAML body
curl -X POST "http://localhost:8080/v1/recipe" \
  -H "Content-Type: application/x-yaml" \
  -d 'kind: RecipeCriteria
apiVersion: aicr.run/v1alpha2
metadata:
  name: training-config
spec:
  service: eks
  accelerator: h100
  intent: training'

# POST with JSON body
curl -X POST "http://localhost:8080/v1/recipe" \
  -H "Content-Type: application/json" \
  -d '{
    "kind": "RecipeCriteria",
    "apiVersion": "aicr.run/v1alpha2",
    "metadata": {"name": "training-config"},
    "spec": {
      "service": "eks",
      "accelerator": "h100",
      "intent": "training"
    }
  }'

# POST with criteria file
curl -X POST "http://localhost:8080/v1/recipe" \
  -H "Content-Type: application/yaml" \
  -d @criteria.yaml

# Pretty print response
curl -s -X POST "http://localhost:8080/v1/recipe" \
  -H "Content-Type: application/json" \
  -d '{"kind":"RecipeCriteria","apiVersion":"aicr.run/v1alpha2","spec":{"service":"eks","accelerator":"h100"}}' \
  | jq '.'

Error Responses:

  • 400 Bad Request - Invalid criteria format, missing required fields, or invalid enum values
  • 400 Bad Request - A stated criteria dimension is not honored by any applicable recipe overlay (uncovered dimension). This applies to both GET /v1/recipe and POST /v1/recipe: every dimension you state (service, accelerator, intent, os, platform) must be matched by at least one applied overlay, or the request fails instead of silently returning a recipe that ignores it. nodes is exempt — it is advisory and never required to be covered. The response's details.uncovered array names the offending dimension(s), the requested value, and any validCompletions (additional criteria that would make the request coverable). Snapshot-driven resolution (CLI --snapshot / Go SDK) may additionally attach excludedOverlays and constraintWarnings to the error; the HTTP API resolves from criteria only and never emits those two fields.
  • 405 Method Not Allowed - Only GET and POST are supported

Uncovered-Dimension Error Example:

{
  "code": "INVALID_REQUEST",
  "message": "platform 'kubeflow' for criteria(service=eks, accelerator=h100, intent=training, platform=kubeflow) requires os (valid: ubuntu)",
  "details": {
    "uncovered": [
      {
        "dimension": "platform",
        "requestedValue": "kubeflow",
        "validCompletions": [{"os": "ubuntu"}]
      }
    ]
  },
  "requestId": "550e8400-e29b-41d4-a716-446655440000",
  "timestamp": "2025-01-15T10:30:00Z",
  "retryable": false
}

Response:

{
  "apiVersion": "aicr.run/v1alpha2",
  "kind": "RecipeResult",
  "metadata": {
    "version": "v0.14.0",
    "appliedOverlays": [
      "base",
      "eks",
      "eks-training",
      "gb200-eks-training"
    ],
    "excludedOverlays": [
      {
        "name": "h100-eks-ubuntu-training",
        "reason": "mixin-constraint-failed"
      }
    ],
    "constraintWarnings": [
      {
        "overlay": "h100-eks-ubuntu-training",
        "constraint": "OS.sysctl./proc/sys/kernel/osrelease",
        "expected": ">= 6.8",
        "actual": "5.15.0",
        "reason": "mixin-constraint-failed: expected >= 6.8, got 5.15.0"
      }
    ]
  },
  "criteria": {
    "service": "eks",
    "accelerator": "gb200",
    "intent": "training",
    "os": "any",
    "platform": "any"
  },
  "constraints": [
    {
      "name": "GPU.driver.version",
      "value": "580.82.07"
    },
    {
      "name": "GPU.driver.cudaVersion",
      "value": "13.1"
    }
  ],
  "componentRefs": [
    {
      "name": "gpu-operator",
      "type": "Helm",
      "chart": "gpu-operator",
      "source": "https://helm.ngc.nvidia.com/nvidia",
      "version": "v25.3.3"
    },
    {
      "name": "network-operator",
      "type": "Helm",
      "chart": "network-operator",
      "source": "https://helm.ngc.nvidia.com/nvidia",
      "version": "v25.4.0"
    }
  ],
  "deploymentOrder": [
    "gpu-operator",
    "network-operator"
  ]
}

metadata.excludedOverlays is optional. When present, each entry includes the overlay name and a machine-readable reason such as constraint-failed or mixin-constraint-failed.

metadata.gpuDriverState is optional and appears only for snapshot-driven recipes. It records the NVIDIA kernel driver state observed on the sampled GPU node — preinstalled or absent — and is omitted when no snapshot was provided or the snapshot carried no usable driver-loaded reading. The bundle-time CheckDriverOwnershipCoherence validation consumes it: a recipe whose snapshot observed no driver (absent) is blocked from bundling with the preinstalled-driver assumption, since that would leave GPU nodes driverless.

metadata.mariaDBOperatorState is optional and appears when a snapshot supplies MariaDB Operator conflict evidence during resolution of AICR-provided Slurm accounting. It records absent, api-detected, crs-detected, or unknown; query-generated recipes and older snapshots without the collector subtype omit the field. Recipe generation remains observational: api-detected, crs-detected, and unknown emit warnings but still produce a recipe. At bundle time, crs-detected and unknown block AICR-provided installation, while api-detected or omitted evidence warns but proceeds; absent proceeds silently.

GET /v1/query

Query a specific value from a fully hydrated recipe. Resolves a recipe from criteria (same parameters as GET /v1/recipe), merges all base, overlay, and inline overrides, then returns the value at the given selector path.

Query Parameters:

All GET /v1/recipe parameters are supported, plus:

Parameter Type Required Description
selector string Yes Dot-delimited path to the value to extract (e.g. components.gpu-operator.values.driver.version). Empty string returns the entire hydrated recipe.

Response:

  • Scalar values (string, number, bool) are returned as plain JSON values
  • Complex values (maps, lists) are returned as JSON objects/arrays

Error Responses:

Omitting selector returns 400 Bad Request with code INVALID_REQUEST. An explicitly empty selector= remains valid and returns the entire hydrated recipe.

GET /v1/query and POST /v1/query resolve a recipe through the same engine as /v1/recipe, so a stated criteria dimension not honored by any applicable overlay fails the same way: 400 Bad Request with the details.uncovered array described in the POST /v1/recipe error responses above.

Examples:

# Get a specific Helm value
curl -s "http://localhost:8080/v1/query?service=eks&accelerator=h100&intent=training&selector=components.gpu-operator.values.driver.version"

# Get deployment order
curl -s "http://localhost:8080/v1/query?service=eks&accelerator=h100&intent=training&selector=deploymentOrder" | jq '.'

# Get a component subtree
curl -s "http://localhost:8080/v1/query?service=eks&accelerator=h100&selector=components.gpu-operator.values.driver" | jq '.'

POST /v1/query

Alternative to GET /v1/query that accepts the criteria and selector in the request body. The body is a QueryRequest with a criteria object (same fields as the RecipeCriteria spec) and a selector string.

Content Types:

  • application/json - JSON format
  • application/x-yaml - YAML format

Request Body:

criteria:
  service: eks
  accelerator: h100
  intent: training
selector: "components.gpu-operator.values.driver.version"

Examples:

curl -X POST "http://localhost:8080/v1/query" \
  -H "Content-Type: application/json" \
  -d '{
    "criteria": {"service": "eks", "accelerator": "h100", "intent": "training"},
    "selector": "components.gpu-operator.values.driver.version"
  }'

The response format matches GET /v1/query: scalar values are returned as plain JSON values; maps and lists are returned as JSON objects/arrays.

Configured v2 endpoints

v2 in the route and apiVersion in a recipe document are independent version axes. The route segment versions the transient HTTP contract; aicr.run/v1alpha2 and aicr.run/v1alpha3 identify persisted recipe schemas. Therefore, /v2/recipe can return either artifact version and /v2/bundle accepts both, plus versionless legacy artifacts. Selecting a profile or resolving a Slurm accounting mode—not the route number—determines whether the artifact uses v1alpha3.

/v2/recipe, /v2/query, and /v2/bundle expose the configured HTTP contract for profiles and Slurm accounting. The AKS and GKE families are the embedded profile adopters (gpuStack), so /v1/recipe and /v1/query requests with service=aks or service=gke now reject and must move to /v2; /v1/bundle rejects only profile-bearing recipe bodies, so legacy unprofiled AKS/GKE recipes still bundle there (see the cut-over note below). /v1 remains unchanged for families without a profile.

GET /v2/recipe. Accepts the /v1/recipe criteria parameters plus optional profile=name=value and slurmAccountingMode. Profile omission applies the resolved declaration's required default. Slurm accounting accepts disabled, customer-managed, or aicr-provided; omission defaults a Slurm recipe to disabled. The setting is recorded at configuration.slurm.accounting.mode in an aicr.run/v1alpha3 RecipeResult. The v2 route rejects unknown query parameters and conflicting repeated values.

# AKS, non-default value (omit profile= for the azure-managed default):
curl "http://localhost:8080/v2/recipe?service=aks&accelerator=h100&os=ubuntu&intent=training&profile=gpuStack=operator-managed"

# Slurm with AICR-provided accounting
curl "http://localhost:8080/v2/recipe?service=eks&accelerator=h100&intent=training&os=ubuntu&platform=slurm&slurmAccountingMode=aicr-provided"

POST /v2/recipe. Accepts a strict JSON or YAML envelope. criteria is the plain criteria object, not a RecipeCriteria resource. Profile selection may be supplied in the envelope, as the profile query parameter, or in both places when the values agree. slurmAccountingMode is supplied as the same query parameter used by GET. Conflicting selections are rejected:

criteria:
  service: aks
  accelerator: h100
  intent: training
profile: gpuStack=azure-managed

Unknown fields, duplicate or trailing documents, malformed selections, and selections against an unprofiled composition fail with 400 INVALID_REQUEST. POST envelopes require Content-Type: application/json or Content-Type: application/x-yaml; missing, aliased, or unsupported media types are rejected.

GET and POST /v2/query. GET accepts the v2 recipe parameters, including slurmAccountingMode, plus selector. POST accepts the same strict envelope with a required selector. POST profile selection follows the same query/envelope agreement rule as /v2/recipe:

criteria:
  service: aks
  accelerator: h100
profile: gpuStack=azure-managed
selector: metadata.selectedProfile

POST /v2/bundle. Uses the same query parameters and ZIP response as POST /v1/bundle. It carries no profile-selection field because its body is an already-selected RecipeResult. It accepts legacy aicr.run/v1alpha2 recipes, including older artifacts that omit apiVersion, and strictly decodes profiled or accounting-configured aicr.run/v1alpha3 recipes. The request requires Content-Type: application/json or Content-Type: application/x-yaml; missing, aliased, or unsupported media types are rejected.

# The AKS and GKE families are the embedded adopters (gpuStack profiles).
# -f stops on an HTTP error so a 4xx/5xx recipe body is never staged and
# an error response is never written to bundles.zip. POSIX sh suffices:
# the commands are sequential (no pipeline), so pipefail is not needed.
set -eu
curl -fsS -o recipe.json \
  "http://localhost:8080/v2/recipe?service=aks&accelerator=h100&os=ubuntu&intent=training&profile=gpuStack=operator-managed"
curl -fsS -X POST "http://localhost:8080/v2/bundle" \
  -H "Content-Type: application/json" -d @recipe.json -o bundles.zip

Profile-bearing responses record metadata.selectedProfile; accounting-aware responses record configuration.slurm.accounting. Both use recipe apiVersion aicr.run/v1alpha3. Their owned paths are immutable across AICR's supported override surfaces: divergent static values, intersecting dynamic paths, owned-component removal, and argocd-helm install-time values fail closed before output.

The /v1 routes remain the legacy contract. Explicit profile and slurmAccountingMode input is rejected; Slurm recipes remain implicitly disabled and use the aicr.run/v1alpha2 response shape. /v1/recipe and /v1/query reject a composition after it adopts a profile even when the request omits selection, and /v1/bundle rejects a profile-bearing body. Migrate a converted workflow to v2 as one cut-over.

AKS/GKE cut-over: the AKS and GKE families are the embedded adopters, so /v1/recipe and /v1/query requests with service=aks or service=gke now reject. Move GET clients to GET /v2/recipe / GET /v2/query (identical query parameters, plus optional profile=gpuStack=azure-managed or profile=gpuStack=operator-managed on AKS, and profile=gpuStack=gcp-managed or profile=gpuStack=operator-managed on GKE); move POST clients to POST /v2/recipe / POST /v2/query, converting the body to the strict envelope described above (a plain criteria object with an explicit Content-Type, not the v1 RecipeCriteria resource). Then POST the resulting aicr.run/v1alpha3 recipes to /v2/bundle. Other families are unaffected on /v1 until they adopt a profile.

# GKE migration: /v2/recipe (omit profile= for the gcp-managed default,
# or select gpuStack=operator-managed explicitly), then POST to /v2/bundle.
# -f stops on an HTTP error so a 4xx/5xx recipe body is never staged and
# an error response is never written to bundles.zip.
set -euo pipefail
curl -fsS -o recipe.json \
  "http://localhost:8080/v2/recipe?service=gke&accelerator=h100&os=cos&intent=training&profile=gpuStack=operator-managed"
curl -fsS -X POST "http://localhost:8080/v2/bundle" \
  -H "Content-Type: application/json" -d @recipe.json -o bundles.zip

POST /v1/bundle

Generate deployment bundles from a recipe.

Query Parameters:

Parameter Type Default Description
bundlers string (all) Comma-delimited list of recipe component names to bundle (e.g. gpu-operator,network-operator). Whitespace around names is trimmed. Components not listed are skipped as if disabled (their dependency edges are treated as satisfied externally). A name the recipe does not declare, or one that is disabled (by the recipe or a set enabled=false override), is rejected with HTTP 400.
set string[] Value overrides (format: bundler:path.to.field=value). Repeat for multiple. The reserved prefix deployer: carries Argo CD Application options for deployer=argocd and deployer=argocd-helm (namePrefix, destinationServer, project, cascadeDelete), e.g. set=deployer:namePrefix=tenant-a-. Unknown deployer: keys — or the prefix with any other deployer — are rejected with HTTP 400. See the CLI reference's Argo CD Deployer Options for full semantics.
dynamic string[] Declare value paths as install-time parameters (format: component:path.to.field). Repeat for multiple. Supported with deployer=helm, deployer=argocd-helm, deployer=flux, and deployer=helmfile.
system-node-selector string[] Node selectors for system components (format: key=value). Repeat for multiple.
system-node-toleration string[] Tolerations for system components (format: key=value:effect). Repeat for multiple.
accelerated-node-selector string[] Node selectors for GPU nodes (format: key=value). Repeat for multiple.
accelerated-node-toleration string[] Tolerations for GPU nodes (format: key=value:effect). Repeat for multiple.
nodes int 0 Estimated number of GPU nodes (0 = unset). Written to Helm value paths declared in the registry under nodeScheduling.nodeCountPaths.
vendor-charts bool false Pull upstream Helm chart bytes into the bundle at bundle time so the artifact is fully self-contained and air-gap deployable. Each vendored chart is recorded in provenance.yaml with name, version, source URL, and SHA256. Trades the upstream CVE-yank fail-loud signal for offline deployability — see the CLI reference's "Vendoring Charts for Air-Gap" section for the full tradeoff. Requires the helm binary on the API server's $PATH and registry credentials configured for any private upstream repos (HELM_REPOSITORY_USERNAME/HELM_REPOSITORY_PASSWORD for HTTP(S); docker config for OCI). If prerequisites are missing the request fails with a structured error code (SERVICE_UNAVAILABLE / HTTP 503 for missing helm, UNAUTHORIZED / HTTP 401 for credentials).
serial bool false Sequence components strictly one at a time in deployment order, disabling the parallel rollout of independent components. Affects deployer=argocd, argocd-helm, flux, and helmfile (helm is already serial): argocd falls back to a linear sync-wave per folder, flux chains each HelmRelease dependsOn to the previous component, and helmfile chains every release via needs: into one linear apply order. An escape hatch for reproducing the pre-parallelism ordering or bisecting a rollout.
deployer string helm Deployment method: helm, argocd, argocd-helm, flux, or helmfile
repo string Git repository URL for GitOps deployments (used with deployer=argocd and deployer=flux; ignored by deployer=argocd-helm)
app-name string Parent Argo Application name (default: aicr-stack for deployer=argocd-helm, nvidia-stack for deployer=argocd). Must be a DNS-1123 subdomain. Required when deploying multiple non-overlapping AICR bundles to the same Argo CD namespace so the parent Applications do not collide. For deployer=argocd-helm, the value is the chart default and can still be overridden at install time via helm install --set appName=.... Rejected with HTTP 400 on other deployers.
attest bool false Return a cryptographically signed bundle. When true, the server signs the bundle as itself using its operator-configured signing identity; no signing key, token, or identity is ever taken from the request. Parsed with Go strconv.ParseBool semantics; a present-but-unparseable value is rejected with HTTP 400. Absent or false returns an unsigned bundle. If the server has no signing identity configured, attest=true is rejected with HTTP 400 (Server is not configured for attestation). See Server-Side Signing for setup.

Request Body:

The request body is the recipe (RecipeResult) directly. No wrapper object is needed. Current artifacts carry apiVersion: aicr.run/v1alpha2 or aicr.run/v1alpha3 and kind: RecipeResult. The v1alpha3 form identifies recipes carrying metadata.selectedProfile, typed configuration.slurm.accounting, or both; profile-bearing artifacts must use /v2/bundle. New clients should preserve the version emitted by recipe resolution.

For backward compatibility, the endpoint also accepts:

  • Legacy artifacts that omit apiVersion or kind, or carry them as empty strings after a decode/remarshal round trip.
  • The kind: Recipe value this contract published through v0.18.0.

The handler does not validate kind, so all three shapes reach the bundler identically. apiVersion is the exception, validated as described next.

apiVersion has no equivalent legacy window on purpose. An artifact group/version bump is a hard break with no transition period, so a recipe stamped with a prior group/version should be regenerated rather than sent.

This one is enforced. The shared artifact gate rejects any apiVersion outside aicr.run/v1alpha2 and aicr.run/v1alpha3 with a 400, on this endpoint as well as on the CLI file-load path, so a prior group/version fails rather than being silently accepted. An absent or empty apiVersion is still admitted as the legacy shape.

Round-trip caveat for kind: Recipe. The header is copied into the generated bundle's recipe.yaml rather than normalized. The CLI file loader tolerates an absent or empty kind but rejects Recipe, so a bundle generated from a kind: Recipe body cannot be fed back through aicr bundle -r or aicr validate -r. Send kind: RecipeResult if you need the emitted artifact to remain reloadable.

The same limit reaches the tooling that reads a bundle's recipe.yaml, so TestGrid publication and evidence synthesis also reject such a bundle. Only bundles generated from a kind: Recipe HTTP body are affected; the CLI always writes RecipeResult.

Components

These are the recipe components in recipes/registry.yaml — the names the bundlers query parameter accepts (a request may only name components the recipe declares). The registry is the authoritative source — see the component catalog for the full, current list with detailed descriptions. The table below is illustrative of commonly used components:

Component Description
agentgateway Kubernetes Gateway API implementation for AI/ML inference (InferencePool routing)
agentgateway-crds Kubernetes Gateway API CRDs for AI/ML inference (Gateway API + Inference Extension)
aws-ebs-csi-driver Amazon EBS CSI driver (EKS)
aws-efa AWS Elastic Fabric Adapter device plugin (EKS)
cert-manager TLS certificate management
dynamo-platform NVIDIA Dynamo inference serving platform
gatekeeper OPA Gatekeeper policy controller
gke-nccl-tcpxo NCCL TCPxO network plugin for optimized collective communication (GKE)
gpu-operator NVIDIA GPU Operator — driver and runtime lifecycle
gpu-operator-ocp GPU Operator variant for OpenShift (OCP)
gpu-operator-ocp-olm GPU Operator for OpenShift via Operator Lifecycle Manager (OLM)
grove Dynamo pod lifecycle management
k8s-ephemeral-storage-metrics Ephemeral storage usage metrics
k8s-nim-operator NVIDIA NIM Operator for inference microservice deployments
kai-scheduler DRA-aware gang scheduler with topology-aware placement
kube-prometheus-stack Prometheus, Grafana, Alertmanager monitoring stack
kubeflow-trainer Kubeflow Training Operator for distributed training
kueue Kubernetes-native job queuing for batch and AI workloads
network-operator NVIDIA Network Operator — RDMA, SR-IOV, host networking
network-operator-ocp Network Operator variant for OpenShift (OCP)
network-operator-ocp-olm Network Operator for OpenShift via Operator Lifecycle Manager (OLM)
nfd Node Feature Discovery — labels nodes with hardware features; publishes per-node NodeResourceTopology CRDs on production GPU recipes
nfd-ocp Node Feature Discovery variant for OpenShift (OCP)
nfd-ocp-olm Node Feature Discovery for OpenShift via Operator Lifecycle Manager (OLM)
nodewright-customizations Environment-specific node tuning profiles
nodewright-operator OS-level node tuning and kernel configuration
nvidia-dra-driver-gpu Dynamic Resource Allocation driver for GPUs
nvsentinel GPU health monitoring and automated remediation
prometheus-adapter Custom metrics for HPA scaling
prometheus-operator-crds CRDs for the prometheus-operator (Alertmanager, Prometheus, ServiceMonitor, etc.)
slinky-slurm Slinky-managed Slurm cluster instance (Controller, LoginSet, NodeSet, RestApi); reconciled by slinky-slurm-operator
slinky-slurm-operator SchedMD Slinky Slurm operator and admission webhook
slinky-slurm-operator-crds CRDs for the SchedMD Slinky Slurm operator (slinky.slurm.net)
mariadb-operator-crds Official MariaDB Operator CRDs; installed only for AICR-provided Slurm accounting
mariadb-operator Official MariaDB Operator; installed only for AICR-provided Slurm accounting
slurm-accounting-mariadb Installation-managed MariaDB instance and Secret generation contract for Slurm accounting; installed only for AICR-provided Slurm accounting

Examples:

Note: The POST body must be a fully-hydrated RecipeResult — the server adopts the body as-is and does not hydrate registry defaults, so a hand-authored partial body (missing namespace, valuesFile, overrides, dependencyRefs) yields empty values and namespaces in the generated bundle. Obtain a complete body from aicr recipe ... --format json --output - (the CLI defaults to YAML, but POST /v1/bundle JSON-decodes its body) or GET /v1/recipe and pass it unchanged. The inline bodies below are elided for brevity (only a few component fields shown) — use a generated RecipeResult, not these literals.

To bundle a subset of the recipe's components, use the bundlers query parameter (e.g. ?bundlers=gpu-operator,network-operator) rather than hand-trimming componentRefs — trimming the body silently drops required dependencies and breaks deployers like Helmfile on dangling dependencyRefs. The filter prunes those edges safely (a filtered-out dependency is assumed satisfied externally) and rejects unknown or disabled component names with HTTP 400. Slurm accounting adds required-component checks: customer-managed mode requires slinky-slurm, while AICR-provided mode also requires mariadb-operator-crds, mariadb-operator, and slurm-accounting-mariadb. A bundlers filter that omits any required component is rejected with HTTP 400; required components are not automatically added to the selection.

Enabled Helm refs must reference a deployable primary: an external chart (a source repository plus an effective version — empty, whitespace-only, or a bare v is rejected; the chart name falls back to the component name when chart is unset, but a chart without a source is rejected) or local primary manifestFiles. chart, source, and version values carrying surrounding whitespace are rejected — deployers consume them verbatim. Incoherent refs are rejected with HTTP 400 naming the component. Component ref names must also be unique within a recipe (enabled or disabled refs) when non-empty; a duplicate non-empty name is rejected with HTTP 400 naming the conflicting positions. Refs with an empty name are exempt from the uniqueness check.

# Basic: pipe recipe to bundle
curl -s "http://localhost:8080/v1/recipe?accelerator=h100&service=eks" | \
  curl -X POST "http://localhost:8080/v1/bundle" \
    -H "Content-Type: application/json" -d @- -o bundles.zip

# Advanced: with value overrides and Argo CD deployer
curl -s "http://localhost:8080/v1/recipe?accelerator=h100&service=eks" | \
  curl -X POST "http://localhost:8080/v1/bundle?deployer=argocd&repo=https://github.com/my-org/my-gitops-repo.git&set=gpuoperator:gds.enabled=true" \
    -H "Content-Type: application/json" -d @- -o bundles.zip

# With node scheduling for system and GPU nodes
# (recipe.json must be a fully-hydrated RecipeResult, e.g. from GET /v1/recipe)
curl -X POST "http://localhost:8080/v1/bundle?system-node-selector=nodeGroup=system&system-node-toleration=dedicated=system:NoSchedule&accelerated-node-selector=nvidia.com/gpu.present=true&accelerated-node-toleration=nvidia.com/gpu=present:NoSchedule" \
  -H "Content-Type: application/json" \
  -d @recipe.json \
  -o bundles.zip

# Generate bundles from a saved (fully-hydrated) recipe
curl -X POST "http://localhost:8080/v1/bundle" \
  -H "Content-Type: application/json" \
  -d @recipe.json \
  -o bundles.zip

# Elided literal body (NOT complete — use a generated RecipeResult instead)
curl -X POST "http://localhost:8080/v1/bundle" \
  -H "Content-Type: application/json" \
  -d '{
    "apiVersion": "aicr.run/v1alpha2",
    "kind": "RecipeResult",
    "componentRefs": [
      {"name": "gpu-operator", "type": "Helm", "chart": "gpu-operator", "source": "https://helm.ngc.nvidia.com/nvidia", "version": "v26.3.3", "namespace": "gpu-operator", "valuesFile": "components/gpu-operator/values.yaml"},
      {"name": "network-operator", "type": "Helm", "chart": "network-operator", "source": "https://helm.ngc.nvidia.com/nvidia", "version": "26.1.1", "namespace": "nvidia-network-operator", "valuesFile": "components/network-operator/values.yaml"}
    ],
    "deploymentOrder": ["gpu-operator", "network-operator"]
  }' \
  -o bundles.zip

Response Headers:

Header Description Example
Content-Type Always application/zip application/zip
Content-Disposition Download filename attachment; filename="bundles.zip"
X-Bundle-Files Number of verified regular files streamed into the archive 10
X-Bundle-Size Aggregate uncompressed bytes of those verified regular files 45678
X-Bundle-Duration Generation time 1.234s

Before writing the response, the server stages a private, revalidated closed-world inventory. The ZIP contains only the inventory-derived directories and regular files, including recipe.yaml when present; unverified entries are rejected rather than archived. X-Bundle-Files and X-Bundle-Size are derived from that same frozen inventory.

Bundle Structure

bundles.zip
├── deploy.sh                    # root automation script (executable)
├── README.md                    # root deployment guide
├── checksums.txt                # SHA256 for every regular payload file in the archive
├── recipe.yaml                  # canonical post-resolution recipe (helm deployer)
├── 001-<component>/             # per-component folder (NNN-prefixed)
│   ├── install.sh               # component install script
│   ├── values.yaml              # static Helm values
│   ├── cluster-values.yaml      # per-cluster dynamic values
│   └── upstream.env             # CHART/REPO/VERSION (upstream-helm only)
└── 002-<component>/
    ├── install.sh
    ├── values.yaml
    └── cluster-values.yaml

Checksums are root-level only; component folders carry install.sh at their root (no scripts/ subdirectory), and no uninstall.sh/undeploy.sh is generated. After extraction, aicr verify . performs full closed-world verification: every manifest digest must match and every additional file or directory, symlink, or other non-regular object is rejected, except the exact allowed inventory metadata paths.

Server-Side Signing

Pass ?attest=true to POST /v1/bundle to receive a cryptographically signed bundle. The server signs the bundle as itself using an operator-configured signing identity. This is the trust boundary: no signing key, token, or identity is ever taken from the request, so any client that can reach the endpoint gets bundles signed under the server's identity, never its own.

A signed bundle additionally carries, inside the returned zip:

attestation/bundle-attestation.sigstore.json   # signature over the bundle
attestation/aicr-attestation.sigstore.json     # aicrd tool-provenance attestation

attest=true requires a configured signing identity. If none is configured the request is rejected with HTTP 400 (Server is not configured for attestation). An unparseable attest value is also HTTP 400. Absent or false returns an unsigned bundle, as before.

The server supports two mutually exclusive signing modes, selected by environment variables at startup. The configuration is validated fail-fast: a malformed or ambiguous setting stops the server from starting.

Mode A: KMS key. Set AICR_SIGNING_KEY to a cosign KMS URI. The bundle is signed with a long-lived key held in the KMS; no OIDC identity is involved.

Mode B: keyless against a private Sigstore. Set AICR_FULCIO_URL to a private Fulcio CA plus a token source. The server obtains a short-lived signing certificate from Fulcio using its own OIDC identity. Operator setup for Mode B:

  • Run a private Fulcio that trusts the cluster's ServiceAccount token issuer.
  • Mount a projected ServiceAccount token with audience sigstore into the aicrd pod, and point AICR_IDENTITY_TOKEN_FILE at it. The token is read fresh for every signed request because ServiceAccount tokens rotate.
  • Alternatively, when aicrd itself runs inside GitHub Actions, its ambient OIDC environment is used as the token source.
Variable Mode Purpose
AICR_SIGNING_KEY A cosign KMS URI (awskms://, gcpkms://, azurekms://, hashivault://). Its presence selects Mode A.
AICR_FULCIO_URL B Private Fulcio CA endpoint. Its presence (with a token source) selects Mode B.
AICR_IDENTITY_TOKEN_FILE B Path to the server's OIDC token (projected ServiceAccount token, audience sigstore). Read fresh per request.
AICR_REKOR_URL A, B Rekor transparency-log endpoint override.
AICR_SIGNING_CONFIG_PATH A, B Sigstore SigningConfig JSON for Rekor v2 targeting.
AICR_TLOG_UPLOAD A Set false to skip the Rekor upload for air-gapped KMS signing. KMS-only; keyless always uploads.
AICR_BINARY_ATTESTATION_FILE A, B Absolute path to the aicrd binary attestation. Unset defaults to the conventional <executable>-attestation.sigstore.json next to the running binary. Set it when the attestation ships elsewhere in the image, e.g. a ko build stages assets under KO_DATA_PATH (/var/run/ko/aicrd-attestation.sigstore.json) rather than next to the binary.
AICR_BINARY_ATTESTATION_IDENTITY_REGEXP A, B Certificate-identity pattern the server pins its own binary attestation to. Unset uses the release-workflow default (on-tag.yaml). A custom value MUST still contain NVIDIA/aicr so it stays pinned to the NVIDIA org; it retargets which NVIDIA workflow attested the binary (e.g. an e2e workflow), not the org, and a value that is not so pinned fails startup. Mirrors the CLI's --certificate-identity-regexp.

Setting both AICR_SIGNING_KEY and the keyless variables is ambiguous and the server refuses to start.

Server signing also requires the aicrd binary attestation (aicrd-attestation.sigstore.json, issued under the NVIDIA-CI identity and bound to the aicrd binary digest) to be shipped inside the container image. The server verifies it once at startup and embeds it as tool provenance (attestation/aicr-attestation.sigstore.json) in every signed bundle. If signing is enabled but that attestation is missing or invalid, the server fails to start. Producing that attestation in the CI/release pipeline is a separate dependency, tracked outside this feature.

By default the server discovers that attestation next to its own executable. Set AICR_BINARY_ATTESTATION_FILE to point at an explicit path when the image stages it elsewhere: a ko-built image places assets under KO_DATA_PATH (/var/run/ko/aicrd-attestation.sigstore.json), not next to the binary. Only the attestation file path changes; it is still verified against the aicrd binary's own digest.

GET /health

Service health check (liveness probe).

curl "http://localhost:8080/health"

Response:

{
  "status": "healthy",
  "timestamp": "2026-01-11T10:30:00Z"
}

GET /ready

Service readiness check (readiness probe).

curl "http://localhost:8080/ready"

Response:

{
  "status": "ready",
  "timestamp": "2026-01-11T10:30:00Z"
}

GET /metrics

Prometheus metrics endpoint.

curl "http://localhost:8080/metrics"

Key Metrics:

Metric Type Description
aicr_http_requests_total counter Total HTTP requests by method, path, status
aicr_http_request_duration_seconds histogram Request latency distribution
aicr_http_requests_in_flight gauge Current concurrent requests
aicr_rate_limit_rejects_total counter Rate limit rejections

Complete Workflow Example

Fetch a recipe and generate bundles in one workflow:

#!/bin/bash

# Step 1: Get recipe for H100 on EKS for training
echo "Fetching recipe..."
curl -s "http://localhost:8080/v1/recipe?accelerator=h100&service=eks&intent=training" \
  -o recipe.json

# Display recipe summary
echo "Recipe components:"
jq -r '.componentRefs[] | "  - \(.name): \(.version)"' recipe.json

# Step 2: Generate bundles from recipe (pipe directly)
# recipe.json is the fully-hydrated RecipeResult fetched in Step 1.
echo "Generating bundles..."
curl -s -X POST "http://localhost:8080/v1/bundle" \
  -H "Content-Type: application/json" \
  -d @recipe.json \
  -o bundles.zip

# Alternative: one-liner without intermediate file
# curl -s "http://localhost:8080/v1/recipe?accelerator=h100&service=eks" | \
#   curl -X POST "http://localhost:8080/v1/bundle" \
#     -H "Content-Type: application/json" -d @- -o bundles.zip

# Step 3: Extract and verify
echo "Extracting bundles..."
unzip -q bundles.zip -d ./deployment

# Verify the complete inventory (checksums.txt is at the bundle root)
echo "Verifying bundle inventory..."
cd deployment
aicr verify .

# Step 4: Deploy (example)
echo "Bundle ready for deployment:"
ls -la

Error Handling

Error Response Format

{
  "code": "ERROR_CODE",
  "message": "Human-readable error description",
  "details": { ... },
  "requestId": "550e8400-e29b-41d4-a716-446655440000",
  "timestamp": "2026-01-11T10:30:00Z",
  "retryable": true
}

Error Codes

Code HTTP Status Description Retryable
INVALID_REQUEST 400 Invalid query parameters, request body, or disallowed criteria value No
UNAUTHORIZED 401 Authentication or authorization failure No
NOT_FOUND 404 Selector path not found in the resolved configuration No
METHOD_NOT_ALLOWED 405 Wrong HTTP method No
CONFLICT 409 Resource state conflict (e.g., already exists or version mismatch) No
RATE_LIMIT_EXCEEDED 429 Too many requests Yes
INTERNAL 500 Server error Yes
SERVICE_UNAVAILABLE 503 Server temporarily unavailable Yes
TIMEOUT 504 Operation exceeded its time limit Yes

INVALID_REQUEST is not always 400: POST /v1/query and POST /v1/recipe return it with HTTP 413 Request Entity Too Large when the request body exceeds the server's body-size limit (MaxRecipePOSTBytes).

Handling Rate Limits

# Check rate limit headers
curl -I "http://localhost:8080/v1/recipe?accelerator=h100"

# Response headers:
# X-RateLimit-Limit: 100
# X-RateLimit-Remaining: 95
# X-RateLimit-Reset: 1736589000

When rate limited (HTTP 429), use the Retry-After header:

# Retry with backoff
response=$(curl -s -w "%{http_code}" "http://localhost:8080/v1/recipe?accelerator=h100")
if [ "${response: -3}" = "429" ]; then
  retry_after=$(curl -sI "http://localhost:8080/v1/recipe" | grep -i "Retry-After" | awk '{print $2}')
  echo "Rate limited. Retrying after ${retry_after}s..."
  sleep "$retry_after"
fi

Rate Limiting

  • Limit: 100 requests per second (a single process-global token bucket shared across all clients, not per-IP)
  • Burst: 200 requests
  • Headers: X-RateLimit-Limit, X-RateLimit-Remaining, X-RateLimit-Reset
  • 429 Response: Includes Retry-After header

Criteria Allowlists

The API server can be configured to restrict which criteria values are allowed. This enables operators to limit the API to specific accelerators, services, intents, or OS types.

Configuration

Allowlists are configured via environment variables when starting the server:

Environment Variable Description Example
AICR_ALLOWED_ACCELERATORS Comma-separated list of allowed GPU types h100,l40
AICR_ALLOWED_SERVICES Comma-separated list of allowed K8s services eks,gke
AICR_ALLOWED_INTENTS Comma-separated list of allowed workload intents training
AICR_ALLOWED_OS Comma-separated list of allowed OS types ubuntu,rhel

Behavior:

  • If an environment variable is not set, all values for that criteria are allowed
  • If an environment variable is set, only the specified values are permitted
  • The any value is always allowed regardless of allowlist configuration
  • Allowlists apply to the recipe, query, and bundle endpoints on both routes — /v1/recipe, /v1/query, /v1/bundle, /v2/recipe, /v2/query, and /v2/bundle

Example Configuration

# Start server allowing only H100 and L40 GPUs on EKS
docker run -p 8080:8080 \
  -e AICR_ALLOWED_ACCELERATORS=h100,l40 \
  -e AICR_ALLOWED_SERVICES=eks \
  ghcr.io/nvidia/aicrd:latest

Error Response

When a disallowed criteria value is requested:

curl "http://localhost:8080/v1/recipe?accelerator=gb200&service=eks"

Response (HTTP 400):

{
  "code": "INVALID_REQUEST",
  "message": "accelerator type not allowed",
  "details": {
    "requested": "gb200",
    "allowed": ["h100", "l40"]
  },
  "requestId": "550e8400-e29b-41d4-a716-446655440000",
  "timestamp": "2026-01-27T10:30:00Z",
  "retryable": false
}

CLI Behavior

The CLI (aicr) is not affected by allowlists. Allowlists only apply to the API server, allowing operators to restrict API access while maintaining full CLI functionality for administrative tasks.

Programming Language Examples

Python

import requests
import zipfile
import io

BASE_URL = "http://localhost:8080"

# Get recipe
params = {
    "accelerator": "h100",
    "service": "eks",
    "intent": "training",
    "os": "ubuntu"
}

resp = requests.get(f"{BASE_URL}/v1/recipe", params=params)
resp.raise_for_status()
recipe = resp.json()

print(f"Recipe has {len(recipe['componentRefs'])} components")

# Generate bundles — the (fully-hydrated) recipe is the request body.
resp = requests.post(
    f"{BASE_URL}/v1/bundle",
    json=recipe,
)
resp.raise_for_status()

# Extract zip
with zipfile.ZipFile(io.BytesIO(resp.content)) as zf:
    zf.extractall("./deployment")
    print(f"Extracted {len(zf.namelist())} files")

Go

package main

import (
    "encoding/json"
    "fmt"
    "io"
    "net/http"
    "net/url"
    "os"
)

func main() {
    baseURL := "http://localhost:8080"

    // Get recipe
    params := url.Values{}
    params.Add("accelerator", "h100")
    params.Add("service", "eks")
    
    resp, err := http.Get(baseURL + "/v1/recipe?" + params.Encode())
    if err != nil {
        panic(err)
    }
    defer resp.Body.Close()

    var recipe map[string]interface{}
    json.NewDecoder(resp.Body).Decode(&recipe)
    
    fmt.Printf("Got recipe with %d components\n", 
        len(recipe["componentRefs"].([]interface{})))
}

JavaScript/Node.js

const BASE_URL = "http://localhost:8080";

async function main() {
    // Get recipe
    const params = new URLSearchParams({
        accelerator: "h100",
        service: "eks",
        intent: "training"
    });
    
    const recipeResp = await fetch(`${BASE_URL}/v1/recipe?${params}`);
    const recipe = await recipeResp.json();
    
    console.log(`Recipe has ${recipe.componentRefs.length} components`);
    
    // Generate bundles — the (fully-hydrated) recipe is the request body.
    const bundleResp = await fetch(`${BASE_URL}/v1/bundle`, {
        method: "POST",
        headers: { "Content-Type": "application/json" },
        body: JSON.stringify(recipe),
    });
    
    // Save zip
    const buffer = await bundleResp.arrayBuffer();
    require("fs").writeFileSync("bundles.zip", Buffer.from(buffer));
    console.log("Bundles saved to bundles.zip");
}

main();

Shell Script (Batch Processing)

#!/bin/bash
# Generate recipes for multiple environments

# /v2/recipe accepts every family (profiled and unprofiled); the aks and
# gke entries below would be rejected on /v1 because those families carry
# the gpuStack profile (see the AKS/GKE cut-over note).
environments=(
  "os=ubuntu&accelerator=h100&service=eks"
  "os=cos&accelerator=h100&service=gke"
  "os=ubuntu&accelerator=h100&service=aks"
)

for env in "${environments[@]}"; do
  echo "Fetching recipe for: $env"

  curl -s "http://localhost:8080/v2/recipe?${env}" \
    | jq -r '.componentRefs[] | "\(.name): \(.version)"'

  echo ""
done

OpenAPI Specification

The full OpenAPI 3.1 specification is available at: api/aicr/v1/server.yaml

Generate client SDKs:

# Download spec
curl https://raw.githubusercontent.com/NVIDIA/aicr/main/api/aicr/v1/server.yaml \
  -o openapi.yaml

# Generate Python client
openapi-generator-cli generate -i openapi.yaml -g python -o ./python-client

# Generate Go client
openapi-generator-cli generate -i openapi.yaml -g go -o ./go-client

# Generate TypeScript client
openapi-generator-cli generate -i openapi.yaml -g typescript-fetch -o ./ts-client

Troubleshooting

Common Issues

"Invalid accelerator type" error:

# Use valid values: h100, h200, gb200, b200, a100, l40, l40s, rtx-pro-6000, any
curl "http://localhost:8080/v1/recipe?accelerator=h100"

"Recipe is required" error:

# The body IS the RecipeResult itself — not wrapped in a {"recipe": ...} field.
# Pass a fully-hydrated RecipeResult (e.g. from GET /v1/recipe) directly:
curl -s "http://localhost:8080/v1/recipe?accelerator=h100&service=eks" | \
  curl -X POST "http://localhost:8080/v1/bundle" \
    -H "Content-Type: application/json" -d @- -o bundles.zip

Empty zip file:

# Check recipe has componentRefs
curl -s "http://localhost:8080/v1/recipe?accelerator=h100" | jq '.componentRefs'

Connection refused (local):

# Start local server first
make server

See Also