“Obviously, we want to provide great user experiences, and in order to do so, we want to accurately forecast supply and demand-related metrics in a spatial/temporal, fine-granular fashion,” Bell explained. With the vast number of metrics, paired with the fact that many of these are supply- and demand-driven, it would be impossible to set up those thresholds by humans and keep them up-to-date over time.
Bell discussed how real-time outage detection is crucial to Uber’s business. The company gets hundreds of millions of signals continuously, whether from back end systems it is tracking or marketplace health indicators. Uber needs to know whether the app is not functioning as it should be, if people can’t sign in or sign up, or if people can’t take a trip as expected.
Hardware capacity planning formed the third leg of forecasting, using the platform to monitor closely how much hardware to purchase and provision for. “Particularly tricky is the fact that we have some very high-demand days, such as New Year’s Eve or Halloween,” she explained. “We’re a fairly young company. These are very much day-of-the-week dependent. Again, our forecasting platform and expertise can be leveraged on this front in order to ensure that we’re not over-provisioning, which would be fiscally irresponsible, but also not under-provisioning, which could cause an outage and erode the trust of our rider and driver partners.”
Leveraging its forecasting expertise, Uber has now built a completely automated tool said Bell. “People just have to bring us a list of business metrics they want to track, or backend metrics, and then we automatically and dynamically set these thresholds for them, and also keep them updated.”