Concertio, the leading provider of AI-powered performance optimization toolkit for turning general-purpose systems into high-performant, tailor-made systems, will be presenting its automatic Kubernetes optimization solution at the KubeCon conference, November 19-21, 2019 in San Diego.

 

 

Organizations using Kubernetes face three growing challenges: increasing infrastructure costs, scarcity of qualified performance engineers that can optimize for performance, and the intricacy of tuning live applications. As a result, organizations that use Kubernetes report that performance can drop as much as 10x as they scale up to meet mission-critical use cases. Concertio’s Optimizer Studio tool addresses these challenges by leveraging machine learning techniques and Design of Experiment (DOE) methods, allowing for manyfold improvements in the performance and performance per dollar metrics.

Optimizer Studio automatically tailors the many available system and application settings to work in concert with the running workloads. While these settings, which reside in all layers of the stack (BIOS, processors, firmware, operating systems, cloud resources, application frameworks, applications, and compiler flags), have a significant effect on performance and cost, they are too difficult to tune manually. Optimizer Studio leverages AI techniques to quickly navigate the exponentially ample parameter space and see through the system variability to significantly improve performance and greatly reduce infrastructure spend. By further deploying Optimizer Studio in the CI/CD pipeline, organizations ensure getting the best performance out of every commit and infrastructure change.

To learn more, please visit the Concertio team at the KubeCon conference at booth S49. For more information or to schedule an appointment, please contact glenn.higgins@concertio.com.

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