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Playgendary Cuts BigQuery Costs by 50%

DoiT's BigQuery Lens gave the mobile game studio granular cost visibility and query-level optimization across Google Cloud.

Meet Playgendary

As a mobile game developer with over 3 billion installs and 250 million monthly players, Playgendary knows a thing or two about user acquisition. A critical component of their user acquisition strategy is Google BigQuery, which they use to evaluate the effectiveness of their marketing campaigns.

The Challenge

Playgendary couldn't easily understand how their BigQuery costs were broken down at a granular level. Managing a team of data engineers and analysts, analyzing job-level data with SQL was too time-consuming. They also faced fluctuation in compute usage due to unpredictable variables like user activity and game popularity, making it difficult to purchase Committed Use Discounts.

The Solution

Playgendary leveraged DoiT's BigQuery Lens to understand cost breakdowns and identify optimization opportunities. They used personalized recommendations to remove unused tables and the Explorer feature to identify expensive queries without writing SQL. They also worked with DoiT's cloud architects to optimize storage costs and implement on-demand compute workloads commitment for Compute Engine savings.

Results

Reduced BigQuery costs by over 50% in just one month
Gained greater visibility into team's BigQuery usage and behavior patterns
Saved 25% on Compute Engine costs without sacrificing on-demand flexibility

BigQuery is a critical component of our cloud infrastructure, but understanding how we could use it more optimally was difficult. Without BigQuery Lens, I wouldn't have been able to achieve any significant results around cost optimization. The easy-to-use drill down into my team's BigQuery usage and personalized recommendations made optimizing how we use it really easy.
Mikhail Artyugin, Director of Business Intelligence, Playgendary

Understanding and Optimizing BigQuery Costs

Mikhail used BigQuery Lens to understand how costs were broken down and identify optimization priorities. He leveraged recommendations to identify large unused tables and removed them. He used the Explorer feature to identify and optimize the most expensive queries per table and user without writing queries himself. After identifying queries, he examined execution flows in the BigQuery console to find issues like bad JOINs or missing predicate filters.

Optimizing Compute Engine Savings

To optimize Compute Engine spend, Playgendary worked with DoiT on their on-demand compute workloads commitment. They reduced overall Compute Engine spend by 25% without sacrificing on-demand pricing flexibility and without operational management effort. Most importantly, they realize these savings without needing to predict future success of new games.

Storage Optimization Strategy

Mikhail worked with DoiT Senior Cloud Architect Rajan Bhave to understand the pros and cons of using BigQuery's new Physical Storage before deciding they'd save money by switching. This collaboration helped them make informed decisions about storage optimization that contributed to their overall cost reduction goals.

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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.

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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.

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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

Attribute™ simplified tracking customer costs in our multi-tenant environments. Customer cost measurement is now clear and standardized, and finance gets the business context they need. Integration was quick and required no changes.

Kfir Lippmann, CFO, Salt Security

Attribute™ translates complex cloud bills into actionable, business-centric insights that empower our engineering teams to take true ownership of their costs.

Balamurugan Mohandossgandhi, Head of IT and Infrastructure, PropertyGuru

This has let us get a better idea of what our cost of goods sold really is. It's not every day you come across something that delivers value as quickly as yours did for us. I was seeing useful insights inside the POC, and we had only deployed it to a couple of real clusters.

Jason Moore, Principal DevOps Engineer, Accrete AI

Eliminating the need to tag thousands of resources has freed up my team and we've invested our efforts in enhancing our platform significantly.

Ziv Sivan, VP of Engineering

PerfectScale by DoiT has become an important part of how we optimize Kubernetes at scale at OneFootball. It gives our platform team the visibility, automation, resiliency insights, and confidence we need to balance cost efficiency with production readiness, especially as we prepare for major global football moments like the 2026 FIFA World Cup.

Andrea Benfatto, Platform/Cloud Runtime Engineering Manager

Cloudflow's new RDS End of Life alerts have allowed us to be more proactive on keeping our database instances up-to-date. The new solution gives us internal visibility ahead of time so that we can prepare for upgrades, instead of having to upgrade under pressure while incurring extended support costs.

Jon Fairbanks, Site Reliability Engineering Manager

PerfectScale cut 40% off our total EKS spend, and the automations handle what used to take our team 20 hours a month. Now we spend that time on reliability and performance instead of chasing cost metrics.

Caio Cristo, Director of Infrastructure/SRE

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

SELECT has made important cost data readily accessible. I will often pull it up during engineering design reviews so we can quickly evaluate cost impact and projections and factor that into our design decisions.

Douglas Zickuhr, Senior Data Platform Engineer at Personio

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Playgendary Cuts BigQuery Costs by 50%

Meet Playgendary

The Challenge

The Solution

Results

Understanding and Optimizing BigQuery Costs

Optimizing Compute Engine Savings

Storage Optimization Strategy

See how DoiT helps cloud teams control spend

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