Predictive load scaling for services

Embodiments are directed to determining an optimal number of concurrently running cloud resource instances and to providing an interactive interface that shows projected operational metric measurements. In one scenario, a computer system accesses metric information which identifies operational metric measurements, and further accesses a second portion of metric information that identifies operational metric measurements for the cloud resource instances over a second period of time. The computer system then calculates projected operational metric measurements based on the identified operational metric measurements over the first period of time (e.g. for reactive tuning) and further based on the identified operational metric measurements over the second period of time (e.g. for predictive tuning). The computer system then determines, based on the projected operational metric measurements, a number of cloud resource instances that are to be concurrently running at a specified future point in time.