Case Study: Pace Revenue achieves 50% lower compute costs with Google Cloud Platform

Making extra room for profit, with a more resource-efficient cloud stack

Pace Revenue, a London-based travel and hospitality tech startup, helps hotels maximize revenue with machine-learning pricing software. As its customer base grew, the company needed a scalable cloud setup to process large data volumes efficiently while cutting infrastructure costs, especially during COVID-19. Pace Revenue used Google Cloud Platform, including Google Kubernetes Engine, to run its workloads.

With help from DoiT International on Google Cloud Platform, Pace Revenue optimized its infrastructure by moving 80% of its on-demand nodes to preemptible VMs and improving cloud best practices. The result was a 50% reduction in compute spend, freeing up resources to enhance its pricing algorithm and build new features faster.

Pace Revenue

Matt Yule-Bennett

Chief Technology Officer