Resource scaling is not that tough a problem computationally. The tough aspect of it is the practice of defining the driver of scale needs. Past that it is just

Resource scaling is not that tough a problem computationally. The tough aspect of it is the practice of defining the driver of scale needs. Past that it is just calculating based on triggers a continuous or discrete scale. I have done it for FTEs in a huge mining operation and it worked like a charm (of course the requirement for scaling was not as real-time as in this case.) Use cases I had to also cater for in that case were: - reallocation from pools before scaling out, which is not very complex either, but it adds a bit of complexity, especially if you optimise for cost along the way. - linked scaling requirements, e.g. a team grows but there is a bottom and top limit to team size and when you get a new team you also need a supervisor On oscillations, you can weather them out by the way you treat your driver sampling window (static or variable) and a cost function. Normally oscillation is not bad for the resource allocation scenario, it is the intention of it, but for FTEs the cost can be more difficult to manage than for computational resources.