Autonomous optimization
for modern applications

Akamas application-aware AI maximizes performance, cloud savings, and service reliability, helping developers, SREs, and performance engineers move fast without breaking things.

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Watch the video tour to learn how Akamas autonomous workload optimization works and discover its capabilities and features.

THE PLATFORM

Application-aware.
Autonomous.
AI-powered.

Akamas uses reinforcement learning, telemetry and user-defined goals to autonomously optimize full-stack configurations of enterprise applications, both live in production and offline in testing environments.

REDUCE CLOUD COSTS -60%

Cut your applications’ demand for compute and infrastructure resources.

IMPROVE EXPERIENCE QUALITY +30%

Increase throughput, and reduce response time, with lower fluctuations and peaks.

ENSURE SERVICE RESILIENCE zero

Ensure that apps and microservices work smoothly through workload peaks and anomalies.

INCREASETEAM PRODUCTIVITY 5X

Automate application tuning, cutting entirely time spent on manual configuration.

“Akamas helped us to rapidly mature on the performance tuning front, by allowing us to find an optimal configuration for our application. This resulted in significant cost savings as well as removing barriers to replatforming.“

Thanks to Akamas, TeamSystem has improved the efficiency of our critical microservices as we would never be able to do manually. The ability to consistently deliver the highest level of quality to our end-users at the lowest possible cost is an important differentiator for us.

Akamas ease of integration with our CI/CD pipelines enabled us to automate the configuration deployment to quickly find optimized configurations that had not been previously found with our manual approach.