Case Study: Pace Revenue halves compute costs with DoiT International and Google Cloud

How Pace Revenue halved compute costs and bolstered its algorithm with Google Cloud

Pace Revenue, a UK-based travel and hospitality software company, uses machine learning to automate hotel room pricing and help operators maximize revenue. As its business grew, the team needed a lean, scalable cloud infrastructure and wanted to reduce Google Cloud spend while continuing to support a demanding pricing engine.

DoiT International reviewed Pace Revenue’s Google Cloud environment and recommended infrastructure changes, including moving most Google Kubernetes Engine workloads from on-demand nodes to preemptible VMs. Pace Revenue implemented the changes in under a week, cutting compute costs by more than 50% while preserving scalability; the company also gained ongoing access to DoiT International’s cloud expertise, helping it run its algorithm more frequently and build new analytics capabilities on Google BigQuery.

Pace Revenue

Matt Yule-Bennett

Chief Technology Officer