Optimize your live applications for performance and cost
Read this white paper also to learn more about how Akamas compares to solutions that:
Only provide simple indicators of how SLOs (e.g. response time) have been impacted after applied changes, but are unable to automatically identify optimal configurations and ensure defined SLOs are matched once applied.
Rely on simplistic AI models operating at the infrastructure layer and do not take into account the interplay between application and infrastructure layers, thus adversely impacting the overall cost efficiency, resilience and end-to-end performance.
Only focus on recommendations on the Kubernetes configuration without taking into account the dynamics of the application runtime (e.g. JVM), thus causing configuration mismatches, missed efficiency opportunities and serious business risks.