Manage Pods

This page covers the core Pod management operations. For CLI usage, first install the Runpod CLI and configure your API key:

runpodctl config --apiKey RUNPOD_API_KEY

Quick reference

Action	Web UI	CLI
Deploy	Pods page → Deploy	`runpodctl create pods --name NAME --gpuType "GPU" --imageName "IMAGE"`
Start	Expand Pod → Play icon	`runpodctl start pod POD_ID`
Stop	Expand Pod → Stop icon	`runpodctl stop pod POD_ID`
Terminate	Expand Pod → Trash icon	`runpodctl remove pod POD_ID`
List	Pods page	`runpodctl get pod`

Deploy a Pod

Deploy preconfigured Pods from the Runpod Hub for quick setup.

Web
CLI
REST API

Open the Pods page and click Deploy.
(Optional) Attach a network volume for persistent storage.
Select GPU or CPU, then configure:

GPU: Select GPU type → Name your Pod → (Optional) Choose a template → Set GPU count → Click Deploy On-DemandCPU: Select CPU type → Choose instance configuration → Name your Pod → Click Deploy On-Demand

CUDA compatibility: Ensure the host CUDA version matches your requirements. If you see “OCI runtime create failed” errors, use Additional filters → CUDA Versions to select compatible machines.

runpodctl create pods \
  --name hello-world \
  --gpuType "NVIDIA A40" \
  --imageName "runpod/pytorch:3.10-2.0.0-117" \
  --containerDiskSize 10 \
  --volumeSize 100

curl --request POST \
  --url https://rest.runpod.io/v1/pods \
  --header 'Authorization: Bearer RUNPOD_API_KEY' \
  --header 'Content-Type: application/json' \
  --data '{
    "name": "my-pod",
    "imageName": "runpod/pytorch:2.1.0-py3.10-cuda11.8.0-devel-ubuntu22.04",
    "gpuTypeIds": ["NVIDIA GeForce RTX 4090"],
    "gpuCount": 1,
    "containerDiskInGb": 50,
    "volumeInGb": 20
  }'

See the Pod API reference for all parameters.

Stop a Pod

Stopping a Pod releases the GPU and preserves data in /workspace (volume disk). Container disk data is cleared.

You’ll still be charged for volume disk storage while stopped. Terminate the Pod if you don’t need to retain your environment.

Pods with network volumes attached cannot be stopped, only terminated. Your /workspace data is preserved in the network volume.

Open the Pods page and expand your Pod.
Click the Stop button (square icon) and confirm.

runpodctl stop pod $RUNPOD_POD_ID

Schedule a stop (e.g., after 2 hours):

sleep 2h; runpodctl stop pod $RUNPOD_POD_ID &

Start a Pod

Resume a stopped Pod. Note: You may be allocated zero GPUs if capacity has changed.

Open the Pods page and expand your Pod.
Click the Start button (play icon).

runpodctl start pod $RUNPOD_POD_ID

Terminate a Pod

Terminating permanently deletes all data not stored in a network volume. Export important data first.

Open the Pods page and expand your Pod.
Stop the Pod if running, then click Terminate (trash icon) and confirm.

# Single Pod
runpodctl remove pod $RUNPOD_POD_ID

# Bulk remove by name
runpodctl remove pods my-bulk-task --podCount 40

View logs

Pods provide two log types:

Container logs: Application output (stdout)
System logs: Pod lifecycle events (startup, shutdown, errors)

Access logs from the Pods page by expanding your Pod and clicking Logs.

Troubleshooting

Issue	Solution
Zero GPUs on restart	See Zero GPU Pods
Pod stuck initializing	Check logs for command errors; ensure you have an idle job (e.g., `sleep infinity`) if using SSH
Docker Compose not working	Not supported. Use a custom template with your dependencies baked in.

Need help? Contact support.

Get started

Flash

Serverless

Pods

Storage

Public Endpoints

Instant Clusters

Integrations

Hub

Fine-tuning

Reference

Quick reference

Deploy a Pod

Stop a Pod

Start a Pod

Terminate a Pod

View logs

Troubleshooting

Get started

Flash

Serverless

Pods

Storage

Public Endpoints

Instant Clusters

Integrations

Hub

Fine-tuning

Reference

​Quick reference

​Deploy a Pod

​Stop a Pod

​Start a Pod

​Terminate a Pod

​View logs

​Troubleshooting

Quick reference

Deploy a Pod

Stop a Pod

Start a Pod

Terminate a Pod

View logs

Troubleshooting