Caching is a common programming practice to speed up performance. If the computer does not have to reload a section of code or variable or file, but can just access directly from a cache this will improve performance.
There is a mechanism to cache your notebook if you are deploying into a Docker space. Docker is a mechanism for virtualizing code over many instances in one machine. It has become common practice to do so in the Java programming world. Luckily, Docker is very flexible and a method has been determined to use Jupyter in Docker as well. Once in Docker, it is a minor adjustment to automatically cache your pages in Docker. The underlying tool used is memcached, yet another widespread common tool for caching anything, in this case Jupyter Notebooks.