---
title: "Troubleshooting & FAQs"
description: "Common issues and security information"
---

# Troubleshooting & FAQ

## Troubleshooting

### Common Issues

| Issue | Solution |
| :--- | :--- |
| **"Access Denied" when using CLI tools** | Go to your dataset's **Setup** tab to view your access keys. Copy the Access Key and Secret Key, then reconfigure your CLI tool (s3cmd, mc, etc.). |
| **Dataset not visible in notebook** | The dataset wasn't attached after launch. Go to your running instance and attach the dataset from the storage options. |
| **Cannot find uploaded files** | Files may take a few seconds to appear. Refresh the Data Objects tab or list the bucket contents to verify the upload completed successfully. |
| **Slow upload speeds** | For large files, use the MinIO CLI (`mc cp`) or s3cmd instead of the web UI. Uploading compressed archives is faster than uploading many small files individually. |

## Security Overview

### Authentication
*   **Access Keys:** Standard S3-style Access Key and Secret Key pairs (EOS Only).
*   **RBAC:** Project-level access controls determine who can view or delete datasets.

### Data Security
*   **Encryption at Rest:** All data in EOS is encrypted.
    *   *Server-Side Encryption (SSE-S3):* Managed by TIR.
    *   *Server-Side Encryption with Customer Keys (SSE-C):* Managed by you.
*   **Encryption in Transit:** All traffic is secured via TLS/SSL (HTTPS).

### Network Isolation
*   Datasets are logically isolated within your project.
*   Public access is blocked by default; access is only possible via authorized credentials or valid internal mounts.

## Frequently Asked Questions (FAQ)

### General Questions

**Q: What's the difference between EOS Bucket and Disk storage?**

A: EOS Bucket is S3-compatible object storage with virtually unlimited scalability, ideal for storing large datasets, backups, and model artifacts. Disk is PVC-backed block storage with fixed size, offering low latency and high IOPS, best suited for temporary scratch space and high-speed caching.

**Q: Can I change the storage type after creating a dataset?**

A: No, you cannot change the storage type (EOS Bucket or Disk) after a dataset is created. You'll need to create a new dataset with the desired storage type and migrate your data.

**Q: How do I access my dataset from a notebook or training job?**

A: When launching a notebook or training job, simply select the datasets you want to mount. They will automatically appear under the `/datasets/<dataset-name>` directory.

### Storage & Capacity

**Q: What's the maximum size for a dataset?**

A: EOS Bucket storage is virtually unlimited. Disk storage has a fixed size that you specify during creation, but it can be increased later if needed.

**Q: How do I increase the size of my Disk dataset?**

A: You can increase Disk storage size through the resize disk option in the dataset home page. Note that you cannot decrease the size once it's been increased.

### Encryption & Security

**Q: Should I use E2E Managed or User-Managed encryption?**

A: Use **E2E Managed** encryption for ease of use and hassle-free key management. Choose **User-Managed** encryption only if you have strict compliance requirements for key ownership. Remember with User-Managed encryption, key loss means permanent data loss.

**Q: Where can I find my dataset access keys?**

A: Access keys are provided in the **Setup** section of your dataset when you create it. You can view them anytime by navigating to your dataset and clicking on the Setup tab.

**Q: Is encryption free of cost?**

A: Yes, both E2E Managed and User-Managed encryption are provided free of cost. There are no additional charges for encrypting your data at rest.

### Data Management

**Q: How do I delete data from my dataset?**

A: For EOS Buckets, use the web UI's Data Objects tab or the MinIO CLI (`mc rm` command). For Disk storage, access the mounted directory and delete files normally.

**Q: What happens to my data if I delete a dataset?**

A: All data in the dataset is permanently deleted and cannot be recovered. Make sure to backup any important data before deleting a dataset.

**Q: Can I share a dataset with other project members?**

A: Yes, datasets are accessible to all members of your TIR project. You can share access keys with project members, but follow the principle of least privilege for security.

### Lifecycle Rules

**Q: What are lifecycle rules and when should I use them?**

A: Lifecycle rules automatically delete objects after a specified number of days. Use them to manage storage costs by automatically cleaning up temporary data, old logs, or outdated experiment results.

**Q: Can I recover data deleted by lifecycle rules?**

A: No, lifecycle deletion is irreversible. Objects deleted by lifecycle rules cannot be recovered.

**Q: Can I have multiple lifecycle rules on the same dataset?**

A: Yes, you can create multiple lifecycle rules with different prefixes to manage different types of data with different retention periods.





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