Table of contents

Quick Start Guide

Deploy your first GPU container on Podstack in just a few minutes. This guide covers the essential steps from account setup to running workload.

Prerequisites

Before you begin:

  • Account created and verified
  • Wallet topped up with funds
  • Project created (or use default project)

Step 1: Add Funds to Your Wallet

  1. Navigate to Billing > Wallet
  2. Click Top Up
  3. Enter the amount (minimum varies)
  4. Complete payment via Razorpay (UPI, cards, net banking)
  5. Funds appear in your wallet immediately

Step 2: Create a Project

  1. Go to Projects in the sidebar
  2. Click Create Project
  3. Enter a project name and description
  4. Click Create

Projects help organize resources and enable team collaboration.

Step 3: Add an SSH Key

  1. Navigate to SSH Keys
  2. Click Add SSH Key
  3. Either:
    • Paste your existing public key, or
    • Click Generate New Key to create one
  4. Give the key a name and save
  5. If generated, download the private key (one-time only)

Step 4: Create Your First Pod

  1. Go to Compute > Pods
  2. Click Create Pod
  3. Configure your pod:

Basic Settings

  • Name: Give your pod a descriptive name
  • Project: Select your project
  • Image: Choose a container image (e.g., pytorch/pytorch:latest)

Resources

  • GPU Type: Select from available GPUs (A100, H100, V100, etc.)
  • GPU Count: Number of GPUs needed
  • CPU: Number of CPU cores
  • Memory: RAM allocation in GB

Access

  • SSH Key: Select your SSH key
  • Ports: Configure exposed ports (SSH is typically port 22)
  1. Review the estimated cost
  2. Click Create Pod

Step 5: Connect to Your Pod

Once the pod status shows Running:

Via SSH

ssh root@<pod-subdomain>.cloud.podstack.ai

The SSH connection details are displayed on the pod detail page.

Via Web Terminal

Click the Terminal button on the pod card to open a browser-based terminal.

Via Jupyter Notebook

If you enabled notebook access, click the Notebook link to open JupyterLab.

Step 6: Monitor Your Pod

From the Pods list or Pod Detail page, you can:

  • View Logs - See container output
  • Check Stats - Monitor CPU, memory, GPU usage
  • Stop/Start - Pause billing when not in use
  • Delete - Remove the pod when done

Cost Management Tips

  • Stop pods when not actively using them (billing pauses)
  • Right-size resources - don’t over-allocate GPUs or memory
  • Use templates - save configurations for quick redeployment
  • Monitor spending - check the dashboard for run rates

Next Steps