Learn about scheduling workloads with Karpenter| karpenter.sh
Node affinity is a property of Pods that attracts them to a set of nodes (either as a preference or a hard requirement). Taints are the opposite -- they allow a node to repel a set of pods. Tolerations are applied to pods. Tolerations allow the scheduler to schedule pods with matching taints. Tolerations allow scheduling but don't guarantee scheduling: the scheduler also evaluates other parameters as part of its function.| Kubernetes
Understand different ways Karpenter disrupts nodes| karpenter.sh
Configure AWS-specific settings with EC2NodeClasses| karpenter.sh
Kubernetes reserves all labels, annotations and taints in the kubernetes.io and k8s.io namespaces. This document serves both as a reference to the values and as a coordination point for assigning values. Labels, annotations and taints used on API objects apf.kubernetes.io/autoupdate-spec Type: Annotation Example: apf.kubernetes.io/autoupdate-spec: "true" Used on: FlowSchema and PriorityLevelConfiguration Objects If this annotation is set to true on a FlowSchema or PriorityLevelConfiguration, ...| Kubernetes
When you specify a Pod, you can optionally specify how much of each resource a container needs. The most common resources to specify are CPU and memory (RAM); there are others. When you specify the resource request for containers in a Pod, the kube-scheduler uses this information to decide which node to place the Pod on. When you specify a resource limit for a container, the kubelet enforces those limits so that the running container is not allowed to use more of that resource than the limit ...| Kubernetes
You can constrain a Pod so that it is restricted to run on particular node(s), or to prefer to run on particular nodes. There are several ways to do this and the recommended approaches all use label selectors to facilitate the selection. Often, you do not need to set any such constraints; the scheduler will automatically do a reasonable placement (for example, spreading your Pods across nodes so as not place Pods on a node with insufficient free resources).| Kubernetes