Tracking the progress of experimental campaigns with Atlas 0.0.0 is accomplished by using Olympus 0.0.1b0, a benchmarking framework for Bayesian Optimization. Using Olympus' Campaign object, we can keep track of the search space and previous observations over the course of the optimization. To use the Atlas SiLA2 server The Olympus Campaign object is passed to the optimizer and ultimately to Atlas, which uses the observations attribute of the Campaign as input for suggesting new parameters. Saving the campaign state as a .pkl file is one way to track each successive step of the experiments. The Atlas SiLA2 server returns a parameter vector, which can then be added to the Campaign, and used to automate the next round of experiments.