Faster Apps, Lower Bills: Optimizing Travel Search in the Cloud is a worldwide leader in online travel booking service. With €2,35 bn in worldwide bookings in 35 countries and 1200 employees. runs on a modern software architecture based on Java microservices, built on Kubernetes in an on-premise environment. 

To ensure scalability and availability during the peak-demand season, and to materialize the cost savings enabled by elasticity, planned to migrate most of its core business applications and microservices to the public cloud. 

The challenge that launched to Akamas was to reconcile two competing goals in JVM and container resource configuration for each of its microservices: maximize service throughput, while minimizing resource allocation. 

Traditional performance management approaches and tools do not lend themselves to optimize the cost-efficiency of Java and Kubernetes-based services. 

On the other hand, Akamas’ AI-driven technology was created precisely to address this type of challenge.  By using its autonomous performance optimization approach, Akamas managed to meet’s requirements and to exceed their expectations. A sneak peek of the results:

  • A 20% reduction in operating costs due to the rightsizing of cloud infrastructure; 
  • A reduction in average search response time of 2 seconds under load, from 7,5 seconds to 5,5 seconds;
  • Peak transaction volume was increased by 23%.

Learn more about’s unique challenges, the approach we took, and how Akamas delivered unexpected performance and cost results in less than 2 weeks.

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