Huuuge Games is building a state-of-the-art data and AI platform that serves as a unified data hub for all company needs and for all data and AI business insights.
We built an advanced architecture based on Databricks which is built on top of AWS.
Our Unified data infrastructure handles several billions of records per day in batch and real-time mode, generating players' behavioral profiles, predicting their future behavior, and recommending the best customization of game content for each of our players.
Our data and AI infrastructure is highly scalable and enables our data and AI engineering team and our internal and external studio developers to query data and also to generate it by themselves.
There is also a need to closely monitor the data infrastructure activities with respect to cost in order to make sure that we are continuously aligned with our aggressive budget boundaries.
In pursuit of this goal, we built a real-time cost monitoring infrastructure that enables us to closely monitor the cost boundaries for various dimensions such as the technical area of the data system, specific engineering team, individual, process, and more, all in real-time.

The cost monitoring infrastructure is supported by intuitive tools for the definition of cost monitoring criteria and for the definition of real-time alerts.

In this lecture, we will present several use cases for which our cost monitoring infrastructure enables us to detect problematic code, architecture, and individual use of our infrastructure. Furthermore, we will demonstrate, thanks to this infrastructure, how we’ve been able to save money, facilitate the use of the Databricks platform, increase user satisfaction, and have comprehensive visibility of our data ecosystem.