按标签和策略调度
Arbiter-Scheduler 支持动态使用不同的调度策略，因此我们可以根据各种场景将 pod 调度到不同的节点。
例如，用户在一个集群上(甚至是在同一个 namespace 上也支持)有开发和生产类型的 pod，他们可能希望使用 MostAllocated 策略来安排开发类型的 pod，以更好地使用资源使用，并使用 LeastAllocated 策略调度生产类型的 pod 来提高性能和稳定性。
用户可以定义一个生产类型的 Score CR，专门调度生产类型 pod，我们假定生产类型的 pod 带有 label app.kubernetes.io/type: prod：
apiVersion: arbiter.k8s.com.cn/v1alpha1
kind: Score
metadata:
name: least-allocated
spec:
weight: 100
logic: |
// Feel free to modify Score.spec.logic to suit your needs.
// Must include a function named `score`, this score function replaces the
// default score function in the scheduling framework. It inputs the pod and
// node to be scheduled, and outputs a number (0 to 100). The higher the
// number, the more the pod tends to be scheduled to this node.
// The following example shows the JS version of default parameter of the
// algorithm `LeastAllocated` in kubernetes scheduling.
function getPodCpuMemReq() {
const DefaultCPUReq = 100; // 0.1 core
const DefaultMemReq = 200 * 1024 * 1024; // 200MB
var podContainer = pod.raw.spec.containers;
if (podContainer == undefined) {
return [DefaultCPUReq, DefaultMemReq];
}
var cpuReq = 0;
var memReq = 0;
for (var i = 0; i < podContainer.length; i++) {
var resources = podContainer[i].resources;
if (resources.requests == undefined) {
cpuReq += DefaultCPUReq;
memReq += DefaultMemReq;
continue
}
cpuReq += cpuParser(resources.requests.cpu);
memReq += memParser(resources.requests.memory);
}
var podInitContainers = pod.raw.spec.initContainers;
if (podInitContainers == undefined) {
return [cpuReq, memReq];
}
var initCPUReq = 0;
var initMemReq = 0;
for (var i = 0; i < podInitContainers.length; i++) {
var resources = podInitContainers[i].resources;
if (resources.requests == undefined) {
initCPUReq = DefaultCPUReq;
initMemReq = DefaultMemReq;
} else {
initCPUReq = cpuParser(resources.requests.cpu);
}
if (initCPUReq > cpuReq) {
cpuReq = initCPUReq;
}
if (initMemReq > memReq) {
memReq = initMemReq;
}
}
return [cpuReq, memReq];
}
function cpuParser(input) {
const milliMatch = input.match(/^([0-9]+)m$/);
if (milliMatch) {
return parseInt(milliMatch[1]);
}
return parseFloat(input) * 1000;
}
function memParser(input) {
const memoryMultipliers = {
k: 1000, M: 1000 ** 2, G: 1000 ** 3, Ki: 1024, Mi: 1024 ** 2, Gi: 1024 ** 3,
};
const unitMatch = input.match(/^([0-9]+)([A-Za-z]{1,2})$/);
if (unitMatch) {
return parseInt(unitMatch[1], 10) * memoryMultipliers[unitMatch[2]];
}
return parseInt(input, 10);
}
function score() {
var podLabels = pod.raw.metadata.labels;
if (podLabels['app.kubernetes.io/type'] != 'prod') {
return 0;
}
var podReq = getPodCpuMemReq();
var podName = pod.raw.metadata.name;
var podNS = pod.raw.metadata.namespace;
var podCPUReq = podReq[0];
var podMemReq = podReq[1];
var nodeName = node.raw.metadata.name;
var nodeCapacity = node.raw.status.allocatable;
var nodeCPUCap = cpuParser(nodeCapacity.cpu);
var nodeMemCap = memParser(nodeCapacity.memory);
var nodeCPUReq = parseInt(node.cpuReq);
var nodeMemReq = parseInt(node.memReq);
// LeastAllocated
var cpuScore = (nodeCPUCap - nodeCPUReq - podCPUReq) / nodeCPUCap;
console.log('[arbiter-js] podName:', podNS+'/'+podName, 'nodeName', nodeName, 'cpuScore:', cpuScore, 'nodeCPUCap', nodeCPUCap, 'nodeCPUReq', nodeCPUReq, 'podCPUReq', podCPUReq);
var memScore = (nodeMemCap - nodeMemReq - podMemReq) / nodeMemCap;
console.log('[arbiter-js] podName:', podNS+'/'+podName, 'nodeName', nodeName, 'memScore:', memScore, 'nodeMemCap', nodeMemCap, 'nodeMemReq', nodeMemReq, 'podMemReq', podMemReq);
return (cpuScore + memScore) / 2 * 100;
}
用户还可以定义一个开发类型的 Score CR，专门调度开发类型的 pod，我们假定开发类型的 pod 带有 label app.kubernetes.io/type: dev：
apiVersion: arbiter.k8s.com.cn/v1alpha1
kind: Score
metadata:
name: most-allocated
spec:
weight: 100
logic: |
// Feel free to modify Score.spec.logic to suit your needs.
// Must include a function named `score`, this score function replaces the
// default score function in the scheduling framework. It inputs the pod and
// node to be scheduled, and outputs a number (0 to 100). The higher the
// number, the more the pod tends to be scheduled to this node.
// The following example shows the JS version of default parameter of the
// algorithm `LeastAllocated` in kubernetes scheduling.
function getPodCpuMemReq() {
const DefaultCPUReq = 100; // 0.1 core
const DefaultMemReq = 200 * 1024 * 1024; // 200MB
var podContainer = pod.raw.spec.containers;
if (podContainer == undefined) {
return [DefaultCPUReq, DefaultMemReq];
}
var cpuReq = 0;
var memReq = 0;
for (var i = 0; i < podContainer.length; i++) {
var resources = podContainer[i].resources;
if (resources.requests == undefined) {
cpuReq += DefaultCPUReq;
memReq += DefaultMemReq;
continue
}
cpuReq += cpuParser(resources.requests.cpu);
memReq += memParser(resources.requests.memory);
}
var podInitContainers = pod.raw.spec.initContainers;
if (podInitContainers == undefined) {
return [cpuReq, memReq];
}
var initCPUReq = 0;
var initMemReq = 0;
for (var i = 0; i < podInitContainers.length; i++) {
var resources = podInitContainers[i].resources;
if (resources.requests == undefined) {
initCPUReq = DefaultCPUReq;
initMemReq = DefaultMemReq;
} else {
initCPUReq = cpuParser(resources.requests.cpu);
}
if (initCPUReq > cpuReq) {
cpuReq = initCPUReq;
}
if (initMemReq > memReq) {
memReq = initMemReq;
}
}
return [cpuReq, memReq];
}
function cpuParser(input) {
const milliMatch = input.match(/^([0-9]+)m$/);
if (milliMatch) {
return parseInt(milliMatch[1]);
}
return parseFloat(input) * 1000;
}
function memParser(input) {
const memoryMultipliers = {
k: 1000, M: 1000 ** 2, G: 1000 ** 3, Ki: 1024, Mi: 1024 ** 2, Gi: 1024 ** 3,
};
const unitMatch = input.match(/^([0-9]+)([A-Za-z]{1,2})$/);
if (unitMatch) {
return parseInt(unitMatch[1], 10) * memoryMultipliers[unitMatch[2]];
}
return parseInt(input, 10);
}
function score() {
var podLabels = pod.raw.metadata.labels;
if (podLabels['app.kubernetes.io/type'] != 'dev') {
return 0;
}
var podReq = getPodCpuMemReq();
var podName = pod.raw.metadata.name;
var podNS = pod.raw.metadata.namespace;
var podCPUReq = podReq[0];
var podMemReq = podReq[1];
var nodeName = node.raw.metadata.name;
var nodeCapacity = node.raw.status.allocatable;
var nodeCPUCap = cpuParser(nodeCapacity.cpu);
var nodeMemCap = memParser(nodeCapacity.memory);
var nodeCPUReq = parseInt(node.cpuReq);
var nodeMemReq = parseInt(node.memReq);
// MostAllocated
var cpuScore = (nodeCPUReq + podCPUReq) / nodeCPUCap;
console.log('[arbiter-js] podName:', podNS+'/'+podName, 'nodeName', nodeName, 'cpuScore:', cpuScore, 'nodeCPUCap', nodeCPUCap, 'nodeCPUReq', nodeCPUReq, 'podCPUReq', podCPUReq);
var memScore = (nodeMemReq + podMemReq) / nodeMemCap;
console.log('[arbiter-js] podName:', podNS+'/'+podName, 'nodeName', nodeName, 'memScore:', memScore, 'nodeMemCap', nodeMemCap, 'nodeMemReq', nodeMemReq, 'podMemReq', podMemReq);
return (cpuScore + memScore) / 2 * 100;
}
同时使用这两个 Score CR，即可实现对不同类型的 pod 采取不同的调度策略。