Akamas provides a single platform to optimize applications both in pre-production environments, for example to anticipate planned changes, cloud migration or chaos engineering scenarios, and directly live in production while applications are running under dynamically varying workloads.
This video series illustrates Akamas AI-powered optimization in action:
- Video 1 – “Minimize Kubernetes cost while ensuring service quality“: How Akamas AI optimizes a Java-based microservices application running on Kubernetes in production environment, under a dynamic workload, with the goal of reducing cost and matching performance SLOs.
- Video 2 – “Supporting human experts in optimizing Kubernetes apps“: How Akamas provides AI-recommended configurations (both K8s and Golang parameters) to human experts for review, enabling them to keep a Go-based microservices application optimized.
- Video 3 – “Application-aware optimization delivers higher cost efficiency“: How Akamas achieves higher levels of cost optimization for a microservices application running on Kubernetes, thanks to its ability to reduce resource demand by live-tuning both K8s and JVM parameters.
Find out more about Akamas Kubernetes Optimization here.
