Meet Pace Revenue
Pace Revenue provides machine learning-powered software that automates hotel pricing decisions to maximize revenues. The software uses algorithms to set optimal room rates based on demand fluctuations and market factors, increasing hotel revenues by 10% on average. Founded in 2017, the company serves forward-thinking hospitality clients who trust the technology to make business-critical pricing decisions.
The Challenge
Pace Revenue needed to optimize their Google Cloud infrastructure costs while maintaining performance of their machine learning pricing engine. The lean IT team lacked time to establish cloud best practices and wanted to identify untapped savings potential. When COVID-19 hit, reducing cloud spend became even more critical for the business.
The Solution
DoiT provided a comprehensive review of Pace Revenue's Google Cloud configuration and identified opportunities to use preemptible VMs instead of on-demand compute nodes. The team implemented DoiT's recommendations to reorganize their architecture for resilience while leveraging lower-cost preemptible instances on Google Kubernetes Engine.
Results
- Cut compute costs by more than 50% with minimal effort
- Swapped 80% of on-demand nodes for preemptible VMs at 20% of the price
- Freed up resources to improve algorithm capability and run frequency
- Gained direct access to cloud engineering experts for ongoing support
We no longer have to spend time understanding how Google Cloud works because DoiT does it for us. Combined with the compute savings, we can use these resources to make our algorithm more capable and run it more frequently. And that adds directly to our customers' bottom line.
Matt Yule-Bennett, Chief Technology Officer
Finding the Right Partner
Matt Yule-Bennett sought a partner that could provide sustainable cloud expertise and affordability. DoiT's business model stood out because consulting and technical support came included at zero cost when purchasing cloud services through them. The team went above and beyond from the start, providing responsive support and demonstrating deep cloud expertise.
Infrastructure Optimization
DoiT conducted a comprehensive review of Pace Revenue's Google Cloud configuration and identified major savings opportunities. The key recommendation involved migrating workloads from on-demand compute nodes to preemptible VMs on Google Kubernetes Engine. DoiT showed the team how to reorganize their architecture for resilience while leveraging these lower-cost instances that operate at 20% of regular pricing.
Implementation and Results
The Pace Revenue team implemented all suggested infrastructure changes in less than a week. By swapping 80% of on-demand nodes for preemptible VMs, they cut their compute bill in half almost immediately. This represented a reduction of more than 50% in overall compute costs with minimal effort, freeing up resources to improve algorithm capability and run frequency.
Ongoing Partnership Value
Beyond cost savings, Pace Revenue gained direct access to reliable cloud engineering experts for any challenges. The partnership enabled the team to build a new analytics platform powered by Google BigQuery, helping hotel operators visualize data for better decision-making. With DoiT's ongoing support, the lean IT team can focus on innovation while staying at the forefront of cloud technology.
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What they say
What I really like about DoiT's approach is that you're very hands-on and proactive. Satyam would ping me a few times a sprint, letting me know about the most current features, checking in on how things are going. When we are going through a peak time, that proactiveness makes a real difference. Satyam always comes through whenever we need support and helps us leverage the right experts to get us where we need to be.
Chiamaka Ibeme, Engineering Manager, Platform
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Ian Fahey, Senior Analytics Engineer at Loop
You guys have the best UI experience that I've had of any software. It's like you just read my mind where, like, oh, I wish I could click there. Oh, I can
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