Component Catalog
AICR recipes are composed of components — the individual software packages that make up a GPU-accelerated Kubernetes runtime. This page lists every component that can appear in a recipe.
Note: Components are included as appropriate in recipes. Not every component listed here will appear in a recipe.
The source of truth is recipes/registry.yaml. Each entry in the registry defines the component's Helm chart (or Kustomize source), default version, namespace, and node scheduling configuration. If a component is not listed there, it cannot appear in a recipe.
Components
| Component | Description | Source |
|---|---|---|
| gpu-operator | Manages the GPU driver and runtime lifecycle on Kubernetes nodes. Handles driver installation, container runtime configuration, device plugin, and GPU feature discovery. | NVIDIA GPU Operator |
| network-operator | Manages high-performance networking for GPU workloads. Configures RDMA, SR-IOV, and host networking for multi-node communication. | NVIDIA Network Operator |
| gke-nccl-tcpxo | NCCL TCPxO network plugin for GKE. Provides optimized collective communication for multi-node GPU workloads on Google Kubernetes Engine. GKE-specific. | — |
| aws-efa | Device plugin for AWS Elastic Fabric Adapter. Enables low-latency networking on EKS clusters with EFA-capable instances. EKS-specific. | AWS EFA K8s Device Plugin |
| cert-manager | Automates TLS certificate management. Required by several operators for webhook and API server certificates. | cert-manager |
| skyhook-operator | OS-level node tuning and configuration management. Applies kernel parameters, sysctl settings, and system-level optimizations to nodes. | Skyhook |
| skyhook-customizations | Environment-specific node tuning profiles applied via Skyhook. Extends the operator with kernel params, hugepages, and other host-level configurations. | — |
| nvsentinel | GPU health monitoring and automated remediation. Detects GPU errors and can cordon or drain affected nodes. | NVSentinel |
| nvidia-dra-driver-gpu | Dynamic Resource Allocation (DRA) driver for GPUs. Advertises GPUs via the Kubernetes resource.k8s.io/v1 API instead of the legacy device plugin. Requires Kubernetes 1.34+ (DRA is GA in 1.34). See AKS GPU Setup for details. CLI alias: dradriver. | NVIDIA DRA Driver |
| kube-prometheus-stack | Cluster monitoring: Prometheus, Grafana, Alertmanager, and node exporters. Provides GPU and cluster metrics collection and dashboards. | kube-prometheus-stack |
| prometheus-adapter | Exposes custom metrics from Prometheus to the Kubernetes metrics API. Enables HPA scaling based on GPU utilization and other custom metrics. | prometheus-adapter |
| aws-ebs-csi-driver | CSI driver for Amazon EBS volumes. Provides persistent storage for workloads on EKS. EKS-specific. | AWS EBS CSI Driver |
| k8s-ephemeral-storage-metrics | Exports ephemeral storage usage metrics per pod. Useful for monitoring scratch space consumption on GPU nodes. | k8s-ephemeral-storage-metrics |
| kai-scheduler | DRA-aware gang scheduler with hierarchical queues and topology-aware placement. Ensures distributed training jobs land on nodes with optimal interconnect topology. | KAI Scheduler |
| dynamo-crds | Custom Resource Definitions for NVIDIA Dynamo inference serving. Installed separately to support CRD lifecycle management. | Dynamo |
| dynamo-platform | NVIDIA Dynamo inference serving platform. Distributed inference with prefix-cache-aware routing and disaggregated prefill/decode. | Dynamo |
| kgateway-crds | Custom Resource Definitions for kgateway (Kubernetes Gateway API implementation). | kgateway |
| kgateway | Kubernetes Gateway API implementation. Provides model-aware ingress routing for inference workloads. | kgateway |
| kubeflow-trainer | Kubeflow Training Operator for distributed training jobs (PyTorch, etc.). Manages multi-node training job lifecycle with JobSet integration. | Kubeflow Trainer |
How Components Are Selected
Not every component appears in every recipe. The recipe engine selects components based on the overlay chain for your environment:
- Base components (cert-manager, kube-prometheus-stack) appear in most recipes.
- Cloud-specific components (aws-efa, aws-ebs-csi-driver) are added when the service matches.
- Intent-specific components (kubeflow-trainer, dynamo-platform, kai-scheduler) are added based on workload intent.
- Accelerator/OS-specific tuning (skyhook-customizations, nvidia-dra-driver-gpu) varies by hardware and OS combination.
To see exactly which components appear in a given recipe, generate one:
aicr recipe --service eks --accelerator h100 --os ubuntu --intent training -o recipe.yamlThe output lists every component with its pinned version and configuration values.
Adding Components
New components are added declaratively in recipes/registry.yaml — no Go code required. See the Contributing Guide and Bundler Development docs for details.