Finlex cuts cloud costs 50% and ships production AI with DoiT
- Over 65%
- reduction in cloud infrastructure costs from 2024 - present
- 40%
- cost savings achieved through improved visibility and efficient AI architecture
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.
See how DoiT helps cloud teams control spend
Explore how DoiT Cloud Intelligence helps teams improve visibility, governance, and unit economics across cloud environments.
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Finlex cuts cloud costs 50% and ships production AI with DoiT
- Over 65%
- reduction in cloud infrastructure costs from 2024 - present
- 40%
- cost savings achieved through improved visibility and efficient AI architecture
How Raptive proactively prevents AWS RDS extended support costs
- 37 databases
- automatically covered across all AWS regions, and counting
- ~$10k/year
- annual extended support costs prevented
Luxury Escapes Saves $10K+ /month on AWS
Promptly saves $600K and ships AI in weeks
- $600K
- Annual cloud cost savings
- 3 months
- of engineering time saved
Extenda Retail Cuts SSD Waste, Speeds AI
Wicked Reports Ships GenAI 3 Months Faster
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- 25% faster
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- $0 additional spend
- zero additional infrastructure spend during prototype build thanks to AWS credits and DoiT's optimization
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What they say
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
PerfectScale by DoiT has become an mportant 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
I love clicking through SELECT to understand how our environment and workloads are evolving. I probably check it every day. It's coffee and SELECT for me every morning.
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
Diana Koshy, Sr. Director of Data Engineering at Kargo
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Devin McGee, Data Engineering Lead at Home Chef
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Blake Baggett, Head of Data Operations at Entain
One of the most helpful cost rituals we've setup from SELECT is the weekly spend digest sent to Slack. I can start high level and ensure things are in check. If not, I can very quickly drill down into specific workloads which may have driven the cost spike and remediate them before they become a bigger issue.
Michael Revelo, Manager of data and analytics engineering at ClickUp
Through SELECT's automated savings feature and deep cost visibility, we were able to instantly lower our Snowflake spend by over 40% and achieve a 20X ROI on our SELECT investment.
Skyler Chi, SVP, GTM Productivity & Excellence at Exiger
Our costs had jumped up 3X as we scaled, so we're talking about 60% savings in Snowflake spend after adopting SELECT.
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