foxhunt/scripts/README.md

RunPod Deployment Script

Script: runpod_deploy.py

Automated deployment script for RunPod GPU pods in EUR-IS region (SECURE cloud).

Features

• Scans available GPUs with ≥16GB VRAM
• Auto-selects best value GPU (RTX 4090 preferred, then cheapest)
• Supports custom GPU selection
• Dry-run mode for testing
• Automatic network volume attachment

Requirements

pip install requests python-dotenv

Configuration

Create .env.runpod with:

RUNPOD_API_KEY=your_api_key
RUNPOD_VOLUME_ID=your_volume_id

Usage Examples

# Auto-select best value GPU (dry run)
./scripts/runpod_deploy.py --dry-run

# Deploy with default settings (RTX 4090 preferred)
./scripts/runpod_deploy.py

# Deploy with specific GPU
./scripts/runpod_deploy.py --gpu-type "RTX 3090"

# Custom image and larger disk
./scripts/runpod_deploy.py \
  --image runpod/pytorch:2.1.0-py3.10-cuda11.8.0-devel \
  --container-disk 100

# With custom command
./scripts/runpod_deploy.py --command "jupyter lab --allow-root"

Default Configuration

• Cloud Type: SECURE (no spot interruptions)
• Region: EUR-IS (Iceland - low latency to Europe)
• Image: runpod/pytorch:2.4.0-py3.11-cuda12.4.1-devel-ubuntu22.04
• Container Disk: 50GB
• Network Volume: Attached from .env.runpod
• Ports: 8888/http (Jupyter)

GPU Selection Logic

1. If --gpu-type specified and available → use it
2. Else if RTX 4090 available → use it (best value)
3. Else → use cheapest available GPU

Output

✅ POD DEPLOYED SUCCESSFULLY
======================================================================
Pod ID:          abc123-xyz789
GPU:             RTX 4090 (24GB)
Cost:            $0.340/hr
Image:           runpod/pytorch:2.4.0
Status:          RUNNING
======================================================================

📝 NEXT STEPS:
1. Wait 2-3 minutes for pod to initialize
2. Access Jupyter at: https://abc123-8888.proxy.runpod.net
3. SSH access: ssh root@abc123.ssh.runpod.io
4. Monitor pod: https://www.runpod.io/console/pods

Cost Warning

The script will display hourly costs. Remember to stop pods when done to avoid unnecessary charges.

---

Local CI/CD Pipeline Simulator

Script: local_ci_pipeline.sh

Simulates GitLab CI/CD pipeline locally before deployment. Tests Docker image builds and deployments in a safe, local environment.

Features

• 3-stage pipeline: Build → Test → Push
• GLIBC 2.35 validation (Ubuntu 22.04)
• CUDA 12.4.1 + cuDNN 9 library checks
• Entrypoint script validation
• Docker Hub push readiness
• Color-coded output with timing
• Dry-run mode for testing
• Exit on first failure (CI/CD behavior)

Requirements

# Docker installed and running
docker info

# Docker Hub authentication (for push stage)
docker login

Usage Examples

# Full pipeline (Build + Test + Push)
./scripts/local_ci_pipeline.sh

# Test build only (skip push)
./scripts/local_ci_pipeline.sh --skip-push

# Dry-run (show commands without executing)
./scripts/local_ci_pipeline.sh --dry-run

# Verbose output for debugging
./scripts/local_ci_pipeline.sh --verbose --skip-push

Pipeline Stages

Stage 0: Pre-Flight Checks (🔍)

• Docker daemon running
• Docker BuildKit available
• Docker Hub authentication
• Dockerfile exists
• Git repository status

Stage 1: Build (🔨)

• Build Docker image with CUDA 12.4.1 + cuDNN 9
• Verify image size (~4.8 GB)
• Duration: ~2-3 minutes

Stage 2: Test (🧪)

• GLIBC 2.35 validation
• CUDA libraries (libcuda, libcurand, libcublas, libcudnn)
• nvidia-smi availability (optional)
• Binary GLIBC dependencies
• Entrypoint script validation
• Duration: ~10-20 seconds

Stage 3: Push (🚀)

• Push image to Docker Hub
• Verify authentication
• Warn about PRIVATE repository
• Duration: ~1-5 minutes

Output Example

========================================
🚀 LOCAL CI/CD PIPELINE SIMULATOR
========================================

ℹ Simulating GitLab CI/CD pipeline locally
ℹ Image: jgrusewski/foxhunt:latest

========================================
🔍 STAGE 0: PRE-FLIGHT CHECKS
========================================
✓ All required commands available
✓ Docker daemon running
✓ Docker Hub authenticated
⏱ Pre-flight checks completed in 0m 3s

========================================
🔨 STAGE 1: BUILD
========================================
✓ Docker image built successfully: 4.80 GB
⏱ Build completed in 2m 34s

========================================
🧪 STAGE 2: TEST
========================================
✓ GLIBC 2.35 validated
✓ CUDA libraries validated
⏱ Test completed in 0m 18s

========================================
🚀 STAGE 3: PUSH
========================================
✓ Image pushed successfully
⏱ Push completed in 3m 12s

========================================
✅ PIPELINE COMPLETE
========================================
✓ Total pipeline time: 6m 7s
ℹ GitLab CI/CD readiness: ✅

Troubleshooting

Error: Docker daemon not running

sudo systemctl start docker
docker info

Error: Docker Hub authentication failed

docker login
# Enter credentials for jgrusewski account

Error: GLIBC version mismatch

# Expected: GLIBC 2.35 (Ubuntu 22.04)
docker run --rm jgrusewski/foxhunt:latest ldd --version

Documentation

• Full guide: /LOCAL_CI_PIPELINE_GUIDE.md
• Dockerfile: /Dockerfile.runpod
• Total time: 4-9 minutes (vs. 10-15 min on GitLab)
• Cost: $0 (vs. GitLab CI/CD minutes)