> Markdown version of https://yucca.app/en/docs/guides/SystemRequirements/. Documentation index: [llms.txt](https://yucca.app/en/llms.txt), full text in one file: [llms-full.txt](https://yucca.app/en/llms-full.txt). Any page is available as Markdown: append `.md` to its URL without the trailing slash.

# System requirements

The following resources are enough to run Yucca:

1. CPU (processor) - 1 core
2. RAM (memory) - 512Mb.
3. DISK (free disk space) - 1Gb.

These are the minimum requirements just for running the server; for what the consumption will be when adding cameras, read [here](https://yucca.app/en/docs/guides/SystemRequirements/HardwareSelection.md) and [here](https://yucca.app/en/docs/guides/SystemRequirements/RunOnRaspberryPi4.md).

## Camera requirements

The camera must stream via the **RTSP** protocol, and the video must be in the **h264** or **h265** codec.

## Maximum server capacity

Based on our customers' experience, we've concluded that on average the ideal ratio is **10 cameras per 1 CPU core**. So, say on a server with 24 cores and a processor frequency of *2.5-3.0 Ghz*, you can park 240-250 cameras without any problems. At higher values, [LA](https://www.google.com/search?q=what+is+load+average+linux) starts growing significantly, and you may notice artifacts and instability.

## Disk space calculation

Suppose we have 150 identical cameras with a stream bitrate of 2M, and we want to write an archive with a depth of 14 days for them:

* 2 megabits per second, that's 2/8 = 0.25 megabytes
* 0.25 \* 60 \* 60 = 900 megabytes per hour
* 900 \* 24 = 21600 megabytes => 21.6 gigabytes per day per camera
* 21.6 \* 14(days) = 302.4 gigabytes in 14 days per camera
* 302.4 \* 150 = 45360 gigabytes => 45.36 terabytes

This simple calculation lets you roughly estimate how much space our archive will take up. It's also worth noting that arrays shouldn't be filled up to 99% capacity, and it's better to keep at least 5-10% free.