PlayHQ Optimizes Multi-Tenant Kubernetes Costs PerfectScale

Every day across the globe, PlayHQ runs critical digital infrastructure for thousands of community sports competitions. Leading sports organizations including junior Australian rules football clubs, basketball leagues, and local netball and football associations depend on the platform during peak match windows when usage spikes sharply.

These sports organizations use PlayHQ to manage registrations, scoring, payments, and competition operations across hundreds of teams. Demand varies widely by sport, season, and region, which makes scaling infrastructure efficiently and controlling costs a constant challenge.

At the center of this operation is PlayHQ’s platform engineering group that manages the reliability, performance, and cost of the Kubernetes environment. Brad Quinn is the Lead Platform Engineer that implemented PerfectScale.

“Kubernetes is very important to us: It’s the day-to-day workflow of our engineers,” Quinn says.

With about 90 percent of PlayHQ’s compute running on Kubernetes, the team needed a more automated and intelligent approach to Kubernetes cost optimization as their customer base expanded.

Why PlayHQ Prioritized Kubernetes Cost Optimization 

PlayHQ migrated from ECS to Kubernetes to reduce infrastructure costs and speed up tenant deployments. While the move delivered early savings, costs began to rise again as more organizations joined the platform and usage patterns became more unpredictable.

“We moved from ECS to Kubernetes and achieved significant initial savings," Quinn says. "As our customer base expanded and usage patterns became more complex, we needed to evolve our optimization approach to maintain that efficiency.’”

PlayHQ was already using Karpenter to scale nodes efficiently and relied on HPA and KEDA to adjust capacity in response to demand, particularly during peak weekend traffic.

But even with this scaling strategy in place, PlayHQ’s workload demands varied widely between tenants. Infrastructure-level autoscaling ensured capacity, but it did not solve the challenge of accurately right-sizing CPU and memory requests across hundreds of small, variable workloads.

“Every customer has unique usage patterns. Manual resource optimization simply didn't scale—we needed automation to ensure every customer, regardless of size, had right-sized infrastructure without consuming our team's capacity.” Quinn says.

Quinn also evaluated OpenCost but found the operational overhead too high for a lean platform team.

“I set up OpenCost for a little bit, but it was too much effort to run and configure,” Quinn says.

As PlayHQ continued to scale, the platform team recognized that infrastructure autoscaling alone was not enough. They needed continuous, workload-level Kubernetes rightsizing, automated resource optimization, and clearer visibility into Kubernetes cost allocation.

How PerfectScale Helped Automate Kubernetes Optimization

PerfectScale quickly emerged as the ideal solution for automating Kubernetes rightsizing and improving EKS cost efficiency across PlayHQ’s multi-tenant clusters. Speed was an important part of the equation. 

“We had the initial demo, got access to the platform, and had automation set up in a dev cluster within an hour,” Quinn says.

PerfectScale’s capabilities aligned well with PlayHQ’s environment and operational rhythms. The team could automate Kubernetes optimization safely while maintaining full control over when and where changes occurred.

Key capabilities realized included:

• Automated workload rightsizing to continuously adjust CPU and memory requests
• Maintenance windows that prevent changes during high-traffic sports periods such as Saturday game days
• Namespace-level exclusions to avoid modifying sensitive workloads
• Balanced optimization policies for production clusters to ensure stability alongside cost reduction

These capabilities allowed PlayHQ to implement Kubernetes cost optimization without risking performance for the leagues and clubs that depend on the platform for their organizations’ success.

Results: Lower Kubernetes Costs and Faster Issue Resolution

After adopting PerfectScale through DoiT, Quinn says PlayHQ achieved significant improvements across both cost and operational performance.

• 40 percent reduction in non-production Kubernetes costs
• 20 percent reduction in production Kubernetes costs
• Tens of thousands of dollars saved annually
• Improved performance consistency across workloads
• Greater visibility into per-tenant Kubernetes cost allocation

The team also saw faster detection and remediation of resiliency issues. “The resilience stuff, like OOM alerts, makes the time to resolution much faster,” Quinn says.

Having real-time insight into Kubernetes costs per tenant gives Quinn a clearer view of seasonality across different tenants and strengthens how he communicates the value of optimization work to leadership.

“We can quickly get the compute costs per tenant on the fly,” Quinn says. “I can then share the total saved and issues solved with the CTO,” Quinn says.

Building a Cost-Aware Engineering Culture

With automated Kubernetes optimization now in place, PlayHQ plans to extend PerfectScale access beyond the platform team. The goal is to help product engineering squads manage their own SLOs and understand how design decisions influence Kubernetes resource usage and infrastructure costs.

This supports PlayHQ’s long-term goal of aligning engineering practices with sustainable growth, while continuing to deliver reliable digital experiences to clubs, leagues, and families.

Partnering With DoiT for Kubernetes Optimization at Scale

Quinn underscored the value of DoiT and PerfectScale as long-term partners. During onboarding, the teams identified and resolved an issue within hours, further strengthening PlayHQ’s confidence in the solution.

With automated optimization, meaningful cost savings, and improved reliability,  the platform team has the operational efficiency and visibility needed to support PlayHQ's continued expansion.

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