Kubernetes is designed for flexibility, providing fine-grained control for automating deployment, scaling, and management of containerized applications. However, the same flexibility that makes Kubernetes so powerful also introduces complexity. Adopting Kubernetes requires that teams invest time to learn new skills and establish new workflows.
Nowhere are these challenges more apparent than in the world of Kubernetes resource management. To help, we’ve put together this guide.
By reading this eBook, you’ll learn:
-
What are the most common Kubernetes resources, and how do they impact the ability to optimize applications?
-
What are Kubernetes resource requests and limits, and how do they impact quality of service for pods?
-
What machine learning techniques can be used in both non-prod and prod to effectively configure applications for optimal performance and cost-efficiency?
Take a look inside...
