Hi @jorgenem,
I usually work on my own computer with jupyter notebook. I dont use backend personally, but you can try the hdf5 backend (see mention here Using text backend raises sampler stats error).
If you are using NUTS, the pystan workflow is a good place to start (we also recommend similar checks). In general, I usually start with small model and simulation data with known parameters, and adding more complexity. Relevant information in terms of model fitting and model comparisons are documented within a notebook. For example, @AustinRochford’s recent blog post is an excellent example of a typical pymc3 workflow.