Crystal-clear visibility into cloud spend at the workload and tenant level
- Days
- Time to first cost insights after install
- Days
- From install to powerful cost reporting
- Workload & tenant
- Granularity of cost visibility
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.
See how DoiT helps cloud teams control spend
Explore how Cloud Intelligence™ helps teams improve visibility, governance, and unit economics across cloud environments.
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What they say
Attribute™'s platform is truly unique. We now have crystal-clear visibility into our cloud spend at the workload and tenant level, and that insight has already led to actionable savings and powerful insights as we further scale our service.
Paul White, VP of Engineering, Shasta Cloud
We have worked with DoiT for many years, and there has been an increasing number of capabilities and features in DoiT Cloud Intelligence. We've embedded features such as Cloud Analytics and Reports in our own FinOps processes, it's become core to what we do.
Martin Lee, Director of Operations
DoiT gave us the confidence to move from experimentation to production. They helped us understand the right way to build AI for the real world.
Milad Rezazadeh, CTO
Attribute™'s cost grouping technology took our cost visibility and allocation to a whole new level. Now, our teams are fully accountable for their budgets, significantly improving our cloud efficiency and helping us minimize unnecessary costs.
Eli Zilbershtein, Head of DevOps, Hippo
You can't tag a customer in a multi-tenant environment. Attribute™ finally shows us what each customer costs and what's driving those costs.
Omri Cohen, Director of Engineering, Platform
Attribute™'s data is truly unmatched. No other solution on the market could deliver the precise customer cost and usage profiles we needed in such a complex infrastructure. Within weeks, the data from Attribute™ transformed our understanding of cost structures, influencing key strategic decisions in pricing, renegotiations, and market positioning.
Jonathan Langer, COO, Claroty
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