coreweave-hello-world

name	coreweave-hello-world
description	Deploy a GPU workload on CoreWeave with kubectl. Use when running your first GPU job, testing inference, or verifying CoreWeave cluster access. Trigger with phrases like "coreweave hello world", "coreweave first deploy", "coreweave gpu test", "run on coreweave".
allowed-tools	Read, Write, Edit, Bash(kubectl:*)
version	1.0.0
license	MIT
author	Jeremy Longshore <[e-mail]>
tags	["saas","gpu-cloud","kubernetes","inference","coreweave"]
compatible-with	claude-code

CoreWeave Hello World

Overview

Deploy your first GPU workload on CoreWeave: a simple inference service using vLLM or a batch CUDA job. CoreWeave runs Kubernetes on bare-metal GPU nodes with A100, H100, and L40 GPUs.

Prerequisites

• Completed coreweave-install-auth setup
• kubectl configured with CoreWeave kubeconfig
• Namespace with GPU quota

Instructions

Step 1: Deploy a vLLM Inference Server

# vllm-inference.yaml
apiVersion: apps/v1
kind: Deployment
metadata:
  name: vllm-server
spec:
  replicas: 1
  selector:
    matchLabels:
      app: vllm-server
  template:
    metadata:
      labels:
        app: vllm-server
    spec:
      containers:
        - name: vllm
          image: vllm/vllm-openai:latest
          args:
            - "--model"
            - "meta-llama/Llama-3.1-8B-Instruct"
            - "--port"
            - "8000"
          ports:
            - containerPort: 8000
          resources:
            limits:
              nvidia.com/gpu: 
               
               
            
               
               
               
          
              
              
                
                   
                   
      
        
          
            
               
                    
                     
                     []