GDG Cloud Southlake no 20 Stefano Doni Kubernetes performance tuning dilemma Solve it with AI
The Kubernetes performance tuning dilemma: How to solve it with AI
There is a “dark side” to Kubernetes that makes it difficult to ensure the desired performance and resilience of cloud-native applications, while also keeping their costs under control. Indeed, the combined effect of Kubernetes resource management mechanisms and application runtime heuristics may cause serious performance and resilience risks.
There are also significant potential improvements, both in terms of performance and efficiency, that can be achieved by properly tuning Kubernetes and application runtime (e.g. JVM, Golang) configuration settings.
In this webinar, we illustrate how the Akamas AI-powered optimizations platform addresses these challenges by making it possible to set the optimization goals (e.g. cost reduction) and constraints (e.g. performance SLOs) and get recommendations on how to adjust configuration settings dynamically under varying workloads.
Stefano Doni, Co-Founder & CTO, Akamas
Stefano is obsessed with performance optimization and, as CTO at Akamas, he drives its vision of autonomous performance optimization. Stefano has more than 15 years of experience in Performance Engineering. Prior to co-founding Akamas, he led the R&D business unit at Akamas’s parent Moviri, working on critical projects for major international corporations. Stefano speaks regularly at international conferences, and in 2015 won the Computer Measurement Group Best Paper Award for his contribution to Java applications’ capacity planning and performance optimization.
#k8s #kubernetes #performanceengineering #sabre #google #akamas #gdg #gdgcloudsouthlake
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