> ## Documentation Index
> Fetch the complete documentation index at: https://anaconda.com/docs/llms.txt
> Use this file to discover all available pages before exploring further.
# Data storage and memory
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As you produce more notebooks and environments in Anaconda Notebooks, you may begin to run out of storage and find that processes slow down. This topic explains how data storage and memory usage work in Anaconda Notebooks and provides instructions to resolve these issues.
Anaconda Notebooks provides varying levels of cloud storage and CPU "high-compute" seconds based on your subscription plan. See our [pricing page](https://www.anaconda.com/pricing) for further details.
A CPU second is one second of running code on a single CPU core at 100%. We refer to CPU seconds as "high-compute seconds" on our pricing page to clearly distinguish CPU seconds from real-world seconds. Simply running JupyterLab, writing code, and using the interface doesn't really use up your quota (though it has a small impact). Only running Python code from within a notebook and running commands from the terminal counts against your quota, and even then most command functions don't heavily use the CPU.
For example, if your code makes an HTTP request, it will use a tiny amount of CPU time assembling the request and sending it out over the network, but will use no CPU at all while it's waiting for a response. When the response comes back from the other end, it will again use a small amount of CPU to interpret the response and provide your code with the results. So, in general, CPU time is only used while your program is actively making calculations, not while it is waiting for other systems.
**When does the clock on CPU seconds reset?**
Our notebook service accounts have a per-day limit for the maximum number of seconds fully utilizing the CPU. Once an instance hits that limit, it is not shut down, but instead given lower CPU priority and a limit to the amount of compute resources available. This limit is reset every day, so full compute access will be restored the next day.
## Data storage
You can monitor your available cloud storage space with the **Disk Usage** meter at the top of the screen. If you're maxing out your storage space, the most likely culprits are custom environments, which are all the environments you see in the Disk Manager. To gain more storage, delete these custom environments (and optionally download them for later use) or upgrade your subscription.
Anaconda Notebooks uses persistent Elastic Block Store (EBS) storage: a fast, backed-up, SSD storage that supports common data science and machine learning workloads. EBS storage is generally faster and more reliable than most cloud-hosted options.
### Managing disk usage
You can view and manage all your files by clicking anywhere on the **Disk Usage** meter to open the Disk Manager:
Anaconda recommends clearing your cache on a regular basis to save on space.
Restores all selected items to their default state. Select Download items before deleting to ensure you don't lose valuable work.
Downloads selected files. Consider downloading valuable files before deleting.
Deletes selected files.
Hovering over the File Name column header exposes a filter tool to further sort through your files. Clicking File Name orders (and reverses the order of) files alphabetically.
Clicking Size orders (and reverses the order of) files by size.
### Removing custom environments
Creating custom environments consumes a large amount of storage. Free plan users are recommended to avoid complex environment building and to limit this to one environment at a time. Upgrade to work with more custom environments.
1. In a terminal within Anaconda Notebooks, run `conda env list` and see if there are any environments *NOT* in `/opt/conda`.
2. If there are, you can remove those unwanted environments in the Disk Manager as shown in the previous section, or by running:
```sh theme={null}
conda env remove --name
```
Replace \ with the environment name.
3. Further, clear out the cache and other artifacts by clicking **Clear Cache** in the Disk Manager as shown in the previous section, or by running:
```sh theme={null}
conda clean --all
pip cache purge
rm -rf /tmp/*
```
## Memory
If your notebook is running slowly, you might have exceeded your CPU usage limit for the day. You will still be able to work when this happens, but the performance will be affected (for example, loading a `.csv` file with Pandas may take 10 seconds instead of half a second). The limit resets daily.
Anaconda Notebooks limits processes to 6GB of RAM per kernel. Exceeding this limit terminates your process, at which point you will need to restart your kernel. If you need to run larger processes, please contact us at [sales@anaconda.com](mailto:sales@anaconda.com).
To see current progress towards your daily quota, refer to the **CPU Usage** widget at the top of Anaconda Notebooks.
To better manage your CPU usage, regularly check the **Running Terminals and Kernels** tab in the left sidebar and shut down unnecessary kernels when you no longer need them.
You can also completely reset ("factory reset") your instance of Anaconda Notebooks. To perform a reset, click anywhere on the **Disk Usage** meter to open the **Manage Disk Usage** dialog, then click **Reset...**.
## Troubleshooting
### All CPU seconds have been used up in Notebooks
You've used up all your available CPU seconds.
CPU seconds are consumed by active runtimes, which can continue to run in the background even after you've logged out of Notebooks or switched to a different browser tab.
To prevent your CPU seconds from being used while you are not actively using Notebooks, make sure you shut down all runtimes in all open instances of Notebooks before logging off for the day. You can do this from the **Running Terminals and Kernels** tab:
If the problem persists, please raise the issue in the [Anaconda community forums](https://forum.anaconda.com) or [file a support ticket](https://support.anaconda.com/hc/en-us/requests/new?ticket_form_id=360000993773).
You can upgrade your subscription plan to access additional CPU seconds. See our [pricing page](https://www.anaconda.com/pricing) for further details.
### "File load error," "unhandled error," or "unexpected error" message
If you receive a "file load error," "unhandled error," or "unexpected error," like in the following figure, you have most likely exceeded the storage space for your current plan.
Follow the steps in the storage question above to remove items from your Notebooks instance, or upgrade to a higher subscription plan.