Akamas Information

Akamas is the autonomous optimization platform for Kubernetes and AI infrastructure. It maximizes application performance, service reliability, and infrastructure cost efficiency, from the application runtime down to the GPU. Akamas helps performance engineers, developers, DevOps, platform engineers, and SREs be more productive, prevent incidents, and achieve aggressive optimization goals at enterprise scale. Unlike infrastructure-focused cloud optimization tools, Akamas is application-aware, meaning that it optimizes full-stack configurations (JVM, Node.js, .NET, pods, autoscaling, nodes, and GPUs), taking into account application performance and reliability signals, SLOs, and user-defined constraints. Akamas Vivo continuously optimizes Kubernetes workloads in production, Akamas Studio automates performance testing and tuning in test and pre-production environments, and Akamas Inference Optimizer serves more tokens per GPU for self-hosted LLMs. Using reinforcement learning AI, observability data, and safety constraints, Akamas autonomously identifies and applies the best configurations to achieve performance, reliability, and cost goals. Founded by veterans in performance engineering, Akamas counts AWS, Dynatrace, Google Cloud, Gremlin, Mia-Platform, Micro Focus, RedHat, Tricentis, and Splunk among its technology partners. Akamas customers include leading financial services, SaaS software, and online consumer services brands.