Kubernetes Best Practices

Chapter 8. Resource Management

In this chapter, we focus on the best practices for managing and optimizing Kubernetes resources. We discuss workload scheduling, cluster management, pod resource management, namespace management, and scaling applications. We also dive into some of the advanced scheduling techniques that Kubernetes provides through affinity, anti-affinity, taints, tolerations, and nodeSelectors.

We show you how to implement resource limits, resource requests, pod Quality of Service, PodDisruptionBudgets, LimitRangers, and anti-affinity policies.

Kubernetes Scheduler

The Kubernetes scheduler is one of the main components that is hosted in the control plane. The scheduler allows Kubernetes to make placement decisions for pods deployed to the cluster. It deals with optimization of resources based on constraints of the cluster as well as user-specified constraints. It uses a scoring algorithm that is based on predicates and priorities.

Predicates

The first function Kubernetes uses to make a scheduling decision is the predicate function, which determines what nodes the pods can be scheduled on. It implies a hard constraint, so it returns a value of true or false. An example would be when a pod requests 4 GB of memory and a node cannot satisfy this requirement. The node would return a false value and would be removed from viable nodes for the pod to be scheduled to. Another example would be if the node is set to unschedulable; it would then be removed from the scheduling ...