Eliminating the Hidden Costs of Kubernetes with ML-powered Optimization

• DevOps teams using Kubernetes
• Engineering and product teams working on cloud-native apps
• CloudOps and FinOps leaders

Running your cloud-native apps efficiently at scale is not easy. Over-provisioning is the norm as you get started with cloud-native, but cloud waste becomes a significant problem as usage grows. Having over-provisioned and idle cloud resources is like throwing money down the drain, but Kubernetes complexity makes it impossible to optimize applications through trial-and-error.

Fortunately, machine learning is well-suited to solving this type of optimization problem. In this webinar you’ll learn how a scientific approach of rapid experimentation with machine learning can be used to optimize Kubernetes apps before deployment, ensuring the best performance at the lowest possible cost.