Documentation Index
Fetch the complete documentation index at: https://runcrate.ai/docs/llms.txt
Use this file to discover all available pages before exploring further.
Persistent volumes survive instance termination. Your AI agent can create volumes, check available regions, list existing storage, and clean up unused volumes.
”I need a 500GB volume for my training dataset. What regions are available?”
The agent checks regions and creates the volume:
list_storage_regions — returns available regions with capacity
create_volume — creates the volume in your chosen region
Available storage regions:
| Region | Location |
|---|
| us-east-1 | Virginia, US |
| us-west-2 | Oregon, US |
| eu-central-1 | Frankfurt, DE |
| ap-southeast-1 | Singapore |
Which region do you want? (I’d suggest us-east-1 if your instances are in the US.)
After you reply “us-east-1”:
create_volume — creates training-data (500 GB) in us-east-1
Created volume training-data (500 GB) in us-east-1.
Mount it to any instance in the same region from the dashboard or CLI.
”Show me all my volumes and how much storage I’m using.”
The agent lists your storage:
list_volumes — returns all volumes with sizes, regions, and status
You have 3 volumes:
| Volume | Size | Region | Status | Created |
|---|
| training-data | 500 GB | us-east-1 | available | 2 hours ago |
| model-checkpoints | 200 GB | us-east-1 | attached | 3 days ago |
| old-experiment | 100 GB | eu-central-1 | available | 2 weeks ago |
Total storage: 800 GB.
old-experiment has been idle for 2 weeks and is in a different region from your instances. Want me to delete it?
”Delete old-experiment and create a new 1TB volume for my image dataset.”
The agent handles both operations:
delete_volume — deletes old-experiment (unused credits refunded)
list_storage_regions — confirms region availability for 1TB
create_volume — creates image-dataset (1000 GB) in us-east-1
Deleted old-experiment (100 GB) in eu-central-1. Unused time refunded to your balance.
Created image-dataset (1,000 GB) in us-east-1.
Updated storage summary:
- training-data: 500 GB (us-east-1)
- model-checkpoints: 200 GB (us-east-1)
- image-dataset: 1,000 GB (us-east-1)
Total: 1,700 GB across 3 volumes.
| Tool | Purpose |
|---|
list_storage_regions | Check available regions before creating volumes |
create_volume | Provision new persistent storage |
list_volumes | Audit existing storage and identify waste |
delete_volume | Remove unused volumes and reclaim credits |