> For the complete documentation index, see [llms.txt](https://support.hivo.co/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://support.hivo.co/~/changes/eaCuYFhybbREuBouwZp6/upload/upload-queue-and-errors.md).
# Upload Queue and Errors
This page explains how assets are queued once users have clicked submit on uploading new assets into HIVO via the Upload tool
### Upload queue
Once you’ve started the upload, you’ll be brought to the Upload Queue, where you’ll be able to manage the upload and view its progress. **You don’t have to stay on this page within HIVO, but do have to leave HIVO open in the browser whilst the upload is ongoing**. The Upload Queue can be accessed by clicking the progress indicator next to your company name in the top right (shown within the red rectangle in the below image).
Under the ‘Queue’ tab, you’ll see sections for ‘In Progress’ and ‘Queue’. You can **pause/resume the upload** by clicking the icon next to the ‘In Progress’ heading.
The ‘Queue’ section will show the order in which Assets will start uploading (Assets at the top of the queue will be added to ‘In Progress’ next). You can click the up arrow next to Assets to **push them to the front of the queue**.
You can **remove Assets from the upload** by clicking the ‘X’ icon - use the icon next to an Asset name for just that Asset, or next to the ‘Queue’ heading for all remaining Assets.
Assets queue
### Upload Errors
The ‘Errored’ tab will show Assets that failed to upload. This can be for a number of reasons, most commonly due the Asset being empty (had a file size of 0), or a weak internet connection. You can **add these Assets back to the Upload Queue** by clicking the ‘Retry’ arrow icon.
In the ‘Successful’ tab, you’ll see a list of Assets that have now been added to the Library. You can click the Asset name to navigate to that Asset’s detail page. Note: Some Versions / properties of the Asset may still be in progress. E.g. Adding automated tags and facial recognition can take several minutes.
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