Sisal Case Study: Pioneering innovation in resource optimization with AI

Explore how Sisal, a leading gaming operator with 35 million customers, achieved a 58% cost reduction for critical Kubernetes microservices using Akamas’ AI-powered optimization platform.

The Challenge: Sisal needed to optimize Kubernetes microservices for maximum cost savings without impacting application performance. Efficient resource management and scaling across containers and services were crucial.

Why Akamas? The AI-powered platform offered unique full-stack, dynamic, context-aware optimization capabilities, supporting live production and pre-production testing. Akamas provided risk-free exploration of configuration spaces and safety policies for gradual changes.

The Result: Akamas achieved a 58% cost reduction in just two weeks of live optimization, addressing JVM memory usage oversizing. Simultaneously optimizing Kubernetes pod sizing, JVM heap size and garbage collector, the platform demonstrated its ability to support multi-layer optimizations and adapt to customer needs.

Long-term Savings: Akamas’ full-stack approach delivered immediate value and long-term benefits. By refining configurations and adapting to shifting demands, the platform proved its capacity for meeting the needs of a rapidly changing industry.

Experience the unmatched benefits of full-stack, application-aware optimization with Akamas, and join industry leaders like Sisal in harnessing the power of cutting-edge technology. Start a free trial now.