foxhunt/RUNPOD_DEPLOY_QUICK_REF.md

RunPod Deployment Quick Reference

Prerequisites

# 1. Activate virtual environment
source .venv/bin/activate

# 2. Install dependencies
pip install -r ml/python/requirements.txt

# 3. Configure credentials in .env.runpod
# Required:
#   RUNPOD_API_KEY=<your_api_key>
#   RUNPOD_VOLUME_ID=<your_volume_id>
# Optional (for monitoring):
#   RUNPOD_S3_BUCKET=<bucket_name>
#   RUNPOD_S3_ACCESS_KEY=<access_key>
#   RUNPOD_S3_SECRET_KEY=<secret_key>

Common Commands

Basic Deployment

# Auto-select cheapest GPU
python3 scripts/runpod_deploy.py

# Specific GPU
python3 scripts/runpod_deploy.py --gpu-type "RTX A4000"

# Dry run (no deployment)
python3 scripts/runpod_deploy.py --dry-run

With Monitoring

# Monitor training logs
python3 scripts/runpod_deploy.py --monitor --timeout 2h

# Full automation (deploy + monitor + auto-stop)
python3 scripts/runpod_deploy.py \
  --gpu-type "RTX A4000" \
  --monitor \
  --auto-stop \
  --timeout 2h

Custom Training

# Custom epochs
python3 scripts/runpod_deploy.py \
  --command "--parquet-file /runpod-volume/test_data/ES_FUT_180d.parquet --epochs 100"

# Different model
python3 scripts/runpod_deploy.py \
  --command "/runpod-volume/binaries/train_mamba2_parquet --epochs 50"

Flag Reference

Flag	Description	Default
--gpu-type	Preferred GPU (e.g., "RTX 4090")	Auto-select cheapest
--image	Docker image	jgrusewski/foxhunt:latest
--command	Training command	TFT with ES_FUT_180d.parquet
--container-disk	Disk size in GB	50
--dry-run	Show plan without deploying	False
--monitor	Stream logs from S3	False
--auto-stop	Auto-terminate on completion	False
--timeout	Max monitoring time (30m, 2h)	120m
--monitor-interval	Log polling interval (seconds)	10

Cost Estimates

GPU	VRAM	Price/hr	100 epochs*
RTX A4000	16GB	$0.25	~$0.50
RTX A5000	24GB	$0.35	~$0.70
Tesla V100	16GB	$0.10	~$0.20
A100 80GB	80GB	$1.20	~$2.40

*Estimated for TFT training (~2h)

Troubleshooting

Module Import Error

WARNING: Could not import foxhunt_runpod module

Fix: Install dependencies

pip install -r ml/python/requirements.txt

S3 Monitoring Disabled

WARNING: S3 credentials not configured

Fix: Add to .env.runpod

RUNPOD_S3_BUCKET=se3zdnb5o4
RUNPOD_S3_ACCESS_KEY=<key>
RUNPOD_S3_SECRET_KEY=<secret>

GPU Not Available

GPU not available in EUR-IS datacenters

Fix: Try again (availability changes frequently) or select different GPU

Manual Pod Management

# View pods
curl -H "Authorization: Bearer $RUNPOD_API_KEY" \
  https://rest.runpod.io/v1/pods

# Stop pod
curl -X POST -H "Authorization: Bearer $RUNPOD_API_KEY" \
  https://rest.runpod.io/v1/pods/<pod_id>/stop

# Terminate pod
curl -X POST -H "Authorization: Bearer $RUNPOD_API_KEY" \
  https://rest.runpod.io/v1/pods/<pod_id>/terminate

Python API Usage

from foxhunt_runpod import RunPodClient, S3LogMonitor

# Deploy
client = RunPodClient(api_key="...", volume_id="...")
gpus = client.get_available_gpus(min_vram=16)
pod = client.deploy_pod(gpu_id=gpus[0]['id'], image="jgrusewski/foxhunt:latest")

# Monitor
monitor = S3LogMonitor(bucket_name="...", aws_access_key="...", aws_secret_key="...")
monitor.stream_logs(pod_id=pod['id'], timeout=7200)

# Cleanup
client.terminate_pod(pod['id'])

Best Practices

1. Always use --dry-run first to verify configuration
2. Set --timeout to prevent runaway costs
3. Use --monitor --auto-stop for unattended training
4. Check GPU pricing before deploying (shown in output)
5. Terminate pods when done to avoid charges

Example Workflow

# 1. Dry run to check configuration
python3 scripts/runpod_deploy.py --dry-run

# 2. Deploy with monitoring
python3 scripts/runpod_deploy.py \
  --gpu-type "RTX A4000" \
  --monitor \
  --auto-stop \
  --timeout 2h \
  --command "--parquet-file /runpod-volume/test_data/ES_FUT_180d.parquet --epochs 100"

# 3. Script will:
#    - Find available RTX A4000 in EUR-IS-1
#    - Deploy pod with volume mounted
#    - Stream logs in real-time
#    - Auto-terminate when complete
#    - Show final cost estimate

Support

• Module docs: ml/python/README.md
• Integration guide: RUNPOD_MODULE_INTEGRATION.md
• Script help: python3 scripts/runpod_deploy.py --help