PREDICTIVE LOAD SCALING FOR SERVICES

摘要

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.

主权项

1. At a computer system including at least one processor and a memory, a computer-implemented method for determining an optimal number of concurrently running cloud resource instances, the method comprising:
an act of accessing a first portion of metric information which identifies operational metric measurements for one or more cloud resource instances over a first period of time prior to a present time; an act of accessing a second portion of metric information that identifies operational metric measurements for the one or more cloud resource instances over at least a second period of time, the second period of time comprising a period of time that occurred in the past but which corresponds to a specified future period of time; an act of calculating one or more projected operational metric measurements based on the identified operational metric measurements over the first period of time and further based on the identified operational metric measurements over the second period of time; and an act of determining, based on the one or more projected operational metric measurements, a number of cloud resource instances that are to be concurrently running at one or more specified future points in time.