58. Capturing and Analyzing Energy Usage Metrics

David Morganthaler, an Account Manager at Heroku, interviews two members from Kevala: Emmanuel Levijarvi, its engineering lead, and Teddy Ward, a software engineer. Kevala is building a one-to-one map of a community's energy grid, to identify how power is produced and model how it's consumed. They pull data from public sources and aggregate data to reliably predict when energy will be needed, and what an optimal price to pay for that energy generation.

Balancing the exact amount of energy that people want alongside the amount that is being produced is an incredibly hard problem for the utility sector. If you don't produce enough, electronics won't work and vehicles can't be charged; if you produce too much, it's either wasted or has the potential to fry wiring and infrastructure. Kevala tries to monitor these figures by using machine learning on models they create, as well as tracking usage throughout the day.

The Kevala engineers spend some time also talking about the dependencies used to achieve their goals. These range from hardware, like the IoT devices which consumers install or the access points they tap into to collect accurate data, as well as the software services which make up their app, like Auth0 and Postgres. Because of the unreliable nature of energy consumption, Heroku's autoscaling platform allows Kevala itself to spin up resources in a cost-effective manner.

Links from this episode

• Kevala is a software company focused on analytics for the energy industry

Episode source