How to Improve Your Kubernetes Experience with Service Mesh and MLOps

In this session, speakers will talk about using a machine learning approach to optimize application performance in Kubernetes clusters in a large private cloud (50+ On-Premise Kubernetes Clusters in a Private Cloud, 500+ Compute Nodes, 10+ Istio Meshes.

In this session, speakers will talk about using a machine learning approach to optimize application performance in Kubernetes clusters in a large private cloud (50+ On-Premise Kubernetes Clusters in a Private Cloud, 500+ Compute Nodes, 10+ Istio Meshes. The speech from Sberbank will cover concrete practical cases and tell in detail about the experience of using machine learning models, consider in detail the architecture of the models, as well as the process of preparing training data, which is based on service mesh telemetry.