Creating Pods

This guide walks through creating a new pod on Podstack with all available configuration options.

Quick Create

1. Navigate to Compute > Pods
2. Click Create Pod
3. Fill in the required fields (name, image, resources)
4. Click Create

Configuration Options

Basic Information

Pod Name A descriptive name for your pod. Must be unique within the project.

Project Select the project this pod belongs to. Resources are billed to the project owner.

Container Image The Docker image to run. Examples:

• pytorch/pytorch:2.0.0-cuda11.7-cudnn8-runtime
• tensorflow/tensorflow:latest-gpu
• nvidia/cuda:12.0-base
• jupyter/scipy-notebook

Private Registry (optional) For private images, provide:

• Registry URL
• Username
• Password/Token

Resource Allocation

GPU Configuration

• GPU Type: Select from available types (A100, H100, V100, etc.)
• GPU Count: Number of GPUs (0 for CPU-only)

CPU and Memory

• CPU Cores: 1-128 cores (fractional values supported, e.g., 0.5)
• Memory: RAM in GB

Storage

• Disk Size: Ephemeral storage for the container

Networking

Exposed Ports Configure ports to expose for external access:

• Container Port: Port inside the container
• Protocol: TCP or UDP
• Public: Whether to expose externally

Common ports:

Access Configuration

SSH Key Select an SSH key for terminal access. Keys can be managed in SSH Keys.

Notebook Access (optional) Enable Jupyter notebook with:

• Username
• Password

Environment Variables

Add environment variables as key-value pairs:

CUDA_VISIBLE_DEVICES=0,1
MODEL_PATH=/data/models

Init Command (optional)

Command to run when the container starts:

pip install -r requirements.txt && python train.py

Volume Mounts

Mount persistent storage:

• NFS Volumes: Select from your existing volumes
• Mount Path: Where to mount inside the container (e.g., /data)

Cost Estimation

Before creating, review the estimated cost showing:

• Hourly rate breakdown (GPU, CPU, memory, storage)
• Total hourly cost

Ensure your wallet has sufficient balance.

Creating from Template

To use a saved configuration:

1. Go to Templates
2. Find your template
3. Click Deploy
4. Modify any settings if needed
5. Click Create

After Creation

Once created, the pod will:

1. Pull the container image
2. Allocate resources
3. Start the container
4. Transition to Running status

This typically takes 30 seconds to a few minutes depending on image size.

Troubleshooting

Pod stuck in Pending

• Check if requested GPU type is available
• Verify wallet has sufficient balance
• Review resource limits

Image pull failed

• Verify image name and tag
• Check private registry credentials
• Ensure image exists and is accessible

Next Steps

Once your pod is running, learn how to connect to it.