First off, thank you for building the platform you have. It is very impressive. I have been searching for a solution like yours that offers live quant trading capabilities and historical data for equities, futures, and cryptocurrencies at a reasonable cost for an individual investor. 

I have written a python-based algorithm that I would like to adapt for use within the platform but am concerned I may run into an optimization roadblock. My algorithm has a handful of parameters that can be combined into thousands of different configurations which I would like to backtest. I would really appreciate it if someone could confirm that I properly understand the platform’s capabilities and limitations.

If I want to run backtests on historical data for equities, futures, and cryptocurrencies, they can only be done so in the terminal, as opposed to on a local version of LEAN. Assuming I chose your prime plan, I will have access to 4 cores which I presume limits me to backtesting 4 parameter combinations in parallel. Is that the case or are there ways to structure my script so I can backtest many more parameter configurations in parallel within the terminal (in order to access the historical data)?