NVIDIA NIM

NVIDIA NIM Health API

Liveness, readiness, and startup probes exposed by self-hosted NIM containers (/v1/health/live, /v1/health/ready) and a Prometheus /v1/metrics scrape endpoint for GPU utilization, request latency, and queue depth. Drives Kubernetes pod lifecycle and HPA scaling via the NIM Operator.

Documentation GitHub OpenAPI

Operations 3

Each operation below carries the questions people ask an LLM about it and the instructions they give an agent to run it. Generated by API Evangelist overlay

GET /v1/health/live Check that the NIM container process is alive · Liveness Probe #

Ask an LLM

“Is my NIM container process still running, for a Kubernetes liveness probe?”

“Which endpoint tells me whether the inference container has crashed or hung?”

Tell an agent

Check whether the NIM container process is alive.

Run the liveness probe against my NIM container.

GET /v1/health/ready Check that the model is loaded and ready · Readiness Probe #

Ask an LLM

“Has the model engine finished loading so the NIM can start accepting traffic?”

“Which check tells a load balancer the container is ready to serve inference requests?”

Tell an agent

Check whether the NIM model engine is loaded and ready for requests.

Run the readiness probe before sending traffic to the container.

GET /v1/metrics Get Prometheus metrics for a NIM container · Prometheus Metrics #

Ask an LLM

“Where can I scrape GPU utilization and request latency metrics for my NIM deployment?”

“Can I see the current request queue depth for an inference container in Prometheus format?”

Tell an agent

Fetch the Prometheus metrics from my NIM container.

Show the GPU utilization, latency histograms and queue depth for this NIM.

Documentation

📖

Documentation

https://docs.nvidia.com/nim/large-language-models/latest/observability.html

Specifications

⚙

OpenAPI

https://raw.githubusercontent.com/api-evangelist/nvidia-nim/refs/heads/main/openapi/nvidia-nim-health-api-openapi.yml

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OpenAPI Specification

openapi: 3.2.0
info:
  title: NVIDIA NIM Biology (BioNeMo) ASR Health API
  description: NVIDIA BioNeMo NIMs for drug discovery and structural biology. Each model is a containerized microservice with its own task-specific payload but a consistent JSON contract. Includes protein structure prediction (AlphaFold2, ESMFold, OpenFold), protein generation (ProtGPT2, RFDiffusion), molecular property prediction (MolMIM), small molecule generation, and molecular docking (DiffDock).
  version: '2026-05-25'
  contact:
    name: NVIDIA Developer Support
    url: https://forums.developer.nvidia.com/c/ai-data-science/nemo-llm-service/
  license:
    name: NVIDIA AI Enterprise License
    url: https://www.nvidia.com/en-us/data-center/products/ai-enterprise/
servers:
- url: https://integrate.api.nvidia.com
  description: NVIDIA-hosted NIM endpoint
- url: http://localhost:8000
  description: Self-hosted NIM container default
security:
- BearerAuth: []
tags:
- name: Health
  description: Liveness, readiness, and metrics probes
paths:
  /v1/health/live:
    get:
      summary: Liveness Probe
      description: Returns 200 OK if the container process is alive. Used as Kubernetes livenessProbe.
      operationId: getLiveness
      tags:
      - Health
      responses:
        '200':
          description: Container is alive.
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/HealthStatus'
        '503':
          description: Container is unhealthy and should be restarted.
  /v1/health/ready:
    get:
      summary: Readiness Probe
      description: Returns 200 OK only once the model engine has loaded and the container can accept traffic.
      operationId: getReadiness
      tags:
      - Health
      responses:
        '200':
          description: Ready to serve.
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/HealthStatus'
        '503':
          description: Not ready yet (e.g. model still loading).
  /v1/metrics:
    get:
      summary: Prometheus Metrics
      description: Prometheus text exposition format. Includes GPU utilization, request latency histograms, queue depth, and engine-specific counters.
      operationId: getMetrics
      tags:
      - Health
      responses:
        '200':
          description: Prometheus metrics payload.
          content:
            text/plain:
              schema:
                type: string
components:
  schemas:
    HealthStatus:
      type: object
      properties:
        message:
          type: string
          example: Service is live.
        object:
          type: string
          example: health-response
  securitySchemes:
    BearerAuth:
      type: http
      scheme: bearer
      bearerFormat: nvapi-...