Kubernetes (k8s) is a popular container orchestration platform that allows developers to deploy, manage, and automate containerized applications in a cloud environment. In Kubernetes, CPU resource allocation is a critical issue that directly affects the performance and reliability of applications. In this article, we will introduce the CPU resource allocation mechanism in Kubernetes, including CPU requests and limits, the CPU Share mechanism, and CPU schedulers and other related concepts, to help developers better control the CPU allocation of containers, so as to improve the performance and reliability of applications.
CPU Allocation Units
In Kubernetes, CPU is allocated in millicpu, with one CPU resource equal to 1000 millicores. For example, a Pod requesting 0.5 CPU resources can be expressed as 500 millicores. It is realized based on the CPU allocation mechanism in the Linux kernel. In the Linux kernel, CPU time is allocated in time slices, each of which is typically a few milliseconds, and Kubernetes takes advantage of this feature by converting the CPU time slice allocation to millicores.
CPU Resource Allocation Mechanism
In Kubernetes, CPU resources are allocated in two ways: CPU requests, which tell the Kubernetes scheduler how much CPU resources the Pod needs to function properly, and CPU limits, which tell Kubernetes how much CPU resources the Pod can use. If there are not enough CPU resources available on a node to satisfy a Pod’s CPU requests, the Pod cannot be scheduled to run on that node. If there are not enough CPU resources available on the node to meet the Pod’s CPU limit, the Pod can still run, but it may be limited by its CPU resources, causing it to run slowly or have other problems.
Note that CPU requests and limits are two separate concepts in Kubernetes. In general, CPU requests and limits should be set according to the actual needs of the application. If the CPU request is set too low, the Pod may not run properly or may run slowly; if the CPU limit is set too high, other Pods on the node may not have enough CPU resources, affecting the performance and availability of the entire cluster.
CPU Share Mechanism
In addition, in Kubernetes, CPU Share is a mechanism for controlling the allocation of container CPU resources. It controls the proportion of CPU allocation between containers by assigning each container a relative weight value.The CPU Share mechanism is a feature of the Linux kernel that is used to control the allocation of CPU time between processes, and is utilized by Kubernetes to allocate CPU resources to containers.
CPU Share is an integer value that represents CPU usage relative to other containers. For example, if one container has a CPU Share of 1024 and another container has a CPU Share of 512, the former will get more CPU time, about twice as much as the latter. If two containers have equal CPU Share values, they will share CPU resources in a time-slice rotation.
In Kubernetes, you can control a container’s CPU Share value by setting the container’s CPU request and limit. A container’s CPU request is used to tell the Kubernetes scheduler the minimum amount of CPU resources that the container needs, and a container’s CPU limit is used to tell Kubernetes the maximum amount of CPU resources that the container can use.The Kubernetes scheduler calculates a container’s CPU Share value. If multiple containers have equal CPU requests and limits, they receive equal CPU Share values, which means that they share CPU resources in a time-slice rotation.
In Kubernetes, the CPU scheduler is one of the components responsible for scheduling Pods to nodes. It makes scheduling decisions based on the available CPU resources on the node and the CPU requests from the Pod.The CPU scheduler also takes into account other factors on the node, such as the usage of resources like memory, disk, network, etc. The CPU scheduler also takes into account the usage of resources on the node, such as memory, disk, network, and so on.
When a Pod is scheduled on a node, Kubernetes assigns the Pod a CPU Cgroup, a Linux kernel feature that groups processes (or containers) and limits their resource usage. In Kubernetes, each Pod has its own CPU Cgroup, which limits the CPU resources used by the Pod.
In short, CPU resource allocation is a key issue in Kubernetes. By setting CPU requests and limits, using the CPU Share mechanism, and features such as the CPU scheduler, you can better control the CPU allocation of containers and improve the performance and reliability of your applications.