Switch to microservices
The journey began by transitioning the backend from a monolithic structure to a microservices architecture. This new design divided the system into smaller, independent services, each handling specific tasks like game logic, user sessions, and leaderboards. Each microservice now scales independently, allocating resources based on demand. This approach allows critical features to handle high traffic without overwhelming the system.
The modular setup made the system highly adaptable. Developers could update or replace individual components without disrupting the rest of the platform. This flexibility was essential for adding new features or customizing the online casino software platform for B2B partnerships, such as creating tailored white-label solutions for partner businesses.
By isolating functionalities, we eliminated major bottlenecks. For example, leaderboard updates no longer interfere with user session performance. This separation lets high-demand features operate without slowing down other system parts. The result is a faster, more reliable backend that can handle rapid growth and evolving business needs.
Core logic upgrade
The original backend couldn’t handle the client’s expected growth, so we rebuilt the core logic using Java Spring, a framework suited for large-scale systems. Our engineers improved the game spin algorithms so that the platform could process a high number of outcomes without delays. Bonus calculations became faster and more accurate, which made reward distribution quick and reliable during busy periods. For user sessions, we redesigned the system to support thousands of logins and logouts at once without any disruptions.
Load balancing
As user activity increased, managing server loads became critical. To handle this, our team implemented AWS load balancers to evenly split traffic across multiple servers. This setup allows the system to redirect traffic from overloaded or failing servers to healthy ones, preventing interruptions and keeping the platform stable. During peak usage, it keeps response times fast and avoids delays that could frustrate users. The load balancers also adjusted resources automatically to match changes in user demand, maintaining performance during busy periods and conserving resources during quieter times.
Faster data access with caching
Furthermore, since the platform heavily depends on quick data access, our professionals integrated Redis and Couchbase for in-memory storage. Redis stores data that users frequently access, such as scores and game progress, so the system can retrieve it almost immediately. Couchbase manages large datasets across several servers, which helps the platform handle heavy traffic more efficiently. Our well-versed team also reworked the way the system processes database queries, allowing it to handle thousands of requests at once without slowing down. These changes made the platform faster and more responsive, even during peak usage.
Architecture pilotée par les événements
We implemented AWS EventBridge and RabbitMQ to manage real-time events across the platform. These tools let the system take on tasks like referral rewards and leaderboard updates without slowing down or compromising performance. RabbitMQ facilitates communication between services by handling data transfers and keeping information consistent and up-to-date across the platform. This approach helped scale up the system’s responsiveness and maintained its reliability.
Multithreading for heavy traffic
Experts at Innowise used multithreading to handle thousands of simultaneous requests without any interruptions. This approach allows the system to manage multiple tasks at the same time, making features like game results and leaderboard updates much faster. To keep things in check, we introduced tools to monitor the system’s health and performance. Datadog delivers real-time updates and flags any issues, while AWS Kinesis keeps track of user activity and database performance. With these tools in place, we could spot and fix problems early.
