Getting the optimal service efficiency that autoscalers won’t give you

Leverage machine learning techniques to find the best configurations for service cost and performance.

Mauro Pessina, Manager Performance Engineering Manager at Moviri, talked during KubeCon + CloudNativeCon Europe 2022 conference.

Over the years, the conference became a reference point for the enterprise open source community and software vendors. Being accepted as a speaker confirms Moviri’s expertise in open-source and cloud-native technologies such as Kubernetes. 

Mauro’s talk “Getting the optimal service efficiency that autoscalers won’t give you” explained the complexity of Kubernetes resource management, with a focus on the main parameters that impact Kubernetes application performance, stability, and cost-efficiency.

Watch the video recording to discover more about Kubernetes resource management, autoscalers, and how to tune Kubernetes applications using machine learning techniques.

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Watch the recording of the speech to learn more about:

Kubernetes resource management

Why Kubernetes resource management is complex and the six main key factors that are fundamental to understanding how it works.

AI-powered optimization

Overcome the challenges of Kubernetes tuning, using an AI-powered optimization platform, that automatically identifies the best configuration.

A real-world case study

The results achieved for a SaaS provider of financial services after leveraging Akamas, AI-powered optimization platform .

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