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8.深入k8s:资源控制Qos和eviction及其源码分析

wuqi13289 2020-08-29 22:22 260 查看 https://www.cnblogs.com/luozhi

转载请声明出处哦~,本篇文章发布于luozhiyun的博客:https://www.luozhiyun.com,源码版本是1.19

又是一个周末,可以愉快的坐下来静静的品味一段源码,这一篇涉及到资源的回收,工作量是很大的,篇幅会比较长,我们可以看到k8s在资源不够时会怎么做的,k8s在回收资源的时候有哪些考虑,我们的pod为什么会无端端的被干掉等等。

limit&request

在k8s中,CPU和内存的资源主要是通过这limit&request来进行限制的,在yaml文件中的定义如下:

spec.containers[].resources.limits.cpu
spec.containers[].resources.limits.memory
spec.containers[].resources.requests.cpu
spec.containers[].resources.requests.memory

在调度的时候,kube-scheduler 只会按照 requests 的值进行计算,而真正限制资源使用的是limit。

下面我引用一个官方的例子:

apiVersion: v1
kind: Pod
metadata:
name: cpu-demo
namespace: cpu-example
spec:
containers:
- name: cpu-demo-ctr
image: vish/stress
resources:
limits:
cpu: "1"
requests:
cpu: "0.5"
args:
- -cpus
- "2"

在这个例子中,args参数给的是cpus等于2,表示这个container可以使用2个cpu进行压测。但是我们的limits是1,以及requests是0.5。

当我们创建好这个pod之后,然后使用kubectl top去查看资源使用情况的时候会发现cpu使用并不会超过1:

NAME                        CPU(cores)   MEMORY(bytes)
cpu-demo                    974m         <something>

这说明这个pod的cpu资源被限制在了1个cpu,即使container想使用,也是没有办法的。

在容器没有指定 request 的时候,request 的值和 limit 默认相等。

QoS 模型与Eviction

下面说一下由不同的 requests 和 limits 的设置方式引出的不同的 QoS 级别。

kubernetes 中有三种 Qos,分别为:

  1. Guaranteed
    :Pod中所有Container的所有Resource的
    limit
    request
    都相等且不为0;

  2. Burstable
    :pod不满足Guaranteed条件,但是其中至少有一个container设置了requests或limits ;

  3. BestEffort
    :pod的 requests 与 limits 均没有设置;

当宿主机资源紧张的时候,kubelet 对 Pod 进行 Eviction(即资源回收)时会按照Qos的顺序进行回收,回收顺序是:BestEffort>Burstable>Guaranteed

Eviction有两种模式,分为 Soft 和 Hard。Soft Eviction 允许你为 Eviction 过程设置grace period,然后等待一个用户配置的grace period之后,再执行Eviction,而Hard则立即执行。

那么什么时候会发生Eviction呢?我们可以为Eviction 设置threshold,比如设置设定内存的 eviction hard threshold 为 100M,那么当这台机器的内存可用资源不足 100M 时,kubelet 就会根据这台机器上面所有 pod 的 QoS 级别以及他们的内存使用情况,进行一个综合排名,把排名最靠前的 pod 进行迁移,从而释放出足够的内存资源。

thresholds定义方式为

[eviction-signal][operator][quantity]

eviction-signal

eviction-signal按照官方文档的说法分为如下几种:

Eviction Signal Description
memory.available memory.available := node.status.capacity[memory] - node.stats.memory.workingSet
nodefs.available nodefs.available := node.stats.fs.available
nodefs.inodesFree nodefs.inodesFree := node.stats.fs.inodesFree
imagefs.available imagefs.available := node.stats.runtime.imagefs.available
imagefs.inodesFree imagefs.inodesFree := node.stats.runtime.imagefs.inodesFree

nodefs和imagefs表示两种文件系统分区:

nodefs:文件系统,kubelet 将其用于卷和守护程序日志等。

imagefs:文件系统,容器运行时用于保存镜像和容器可写层。

operator

就是所需的关系运算符,如"<"。

quantity

是阈值的大小,可以容量大小,如:1Gi;也可以用百分比来表示:10%。

如果kubelet在节点经历系统 OOM 之前无法回收内存,那么oom_killer将基于它在节点上 使用的内存百分比算出一个oom_score,然后结束得分最高的容器。

Qos源码分析

qos的代码位于pkg\apis\core\v1\helper\qos\包下面:

qos#GetPodQOS

//pkg\apis\core\v1\helper\qos\qos.go
func GetPodQOS(pod *v1.Pod) v1.PodQOSClass {
requests := v1.ResourceList{}
limits := v1.ResourceList{}
zeroQuantity := resource.MustParse("0")
isGuaranteed := true
allContainers := []v1.Container{}
//追加所有的初始化容器
allContainers = append(allContainers, pod.Spec.Containers...)
allContainers = append(allContainers, pod.Spec.InitContainers...)
//遍历container
for _, container := range allContainers {
// process requests
//遍历request 里面的cpu、memory 获取其中的值
for name, quantity := range container.Resources.Requests {
if !isSupportedQoSComputeResource(name) {
continue
}
if quantity.Cmp(zeroQuantity) == 1 {
delta := quantity.DeepCopy()
if _, exists := requests[name]; !exists {
requests[name] = delta
} else {
delta.Add(requests[name])
requests[name] = delta
}
}
}
// process limits
qosLimitsFound := sets.NewString()
//遍历 limit 里面的cpu、memory 获取其中的值
for name, quantity := range container.Resources.Limits {
if !isSupportedQoSComputeResource(name) {
continue
}
if quantity.Cmp(zeroQuantity) == 1 {
qosLimitsFound.Insert(string(name))
delta := quantity.DeepCopy()
if _, exists := limits[name]; !exists {
limits[name] = delta
} else {
delta.Add(limits[name])
limits[name] = delta
}
}
}
//如果limits 没有同时设置cpu 、Memory,那么就不是Guaranteed
if !qosLimitsFound.HasAll(string(v1.ResourceMemory), string(v1.ResourceCPU)) {
isGuaranteed = false
}
}
//如果requests 和 limits都没有设置,那么为BestEffort
if len(requests) == 0 && len(limits) == 0 {
return v1.PodQOSBestEffort
}
// Check is requests match limits for all resources.
if isGuaranteed {
for name, req := range requests {
if lim, exists := limits[name]; !exists || lim.Cmp(req) != 0 {
isGuaranteed = false
break
}
}
}
// 都设置了limits 和 requests,则是Guaranteed
if isGuaranteed &&
len(requests) == len(limits) {
return v1.PodQOSGuaranteed
}
return v1.PodQOSBurstable
}

上面有注释我就不过多介绍,非常的简单。

下面这里是QOS OOM打分机制,通过给不同的pod打分来判断,哪些pod可以被优先kill掉,分数越高的越容易被kill。

policy

//\pkg\kubelet\qos\policy.go
// 分值越高越容易被kill
const (
// KubeletOOMScoreAdj is the OOM score adjustment for Kubelet
KubeletOOMScoreAdj int = -999
// KubeProxyOOMScoreAdj is the OOM score adjustment for kube-proxy
KubeProxyOOMScoreAdj  int = -999
guaranteedOOMScoreAdj int = -998
besteffortOOMScoreAdj int = 1000
)

policy#GetContainerOOMScoreAdjust

//\pkg\kubelet\qos\policy.go
func GetContainerOOMScoreAdjust(pod *v1.Pod, container *v1.Container, memoryCapacity int64) int {
//静态Pod、镜像Pod和高优先级Pod,直接可以是guaranteedOOMScoreAdj
if types.IsCriticalPod(pod) {
// Critical pods should be the last to get killed.
return guaranteedOOMScoreAdj
}
//获取pod的qos等级,这里只处理Guaranteed与BestEffort
switch v1qos.GetPodQOS(pod) {
case v1.PodQOSGuaranteed:
// Guaranteed containers should be the last to get killed.
return guaranteedOOMScoreAdj
case v1.PodQOSBestEffort:
return besteffortOOMScoreAdj
}
memoryRequest := container.Resources.Requests.Memory().Value()
//如果我们占用的内存越少,则打分就越高
oomScoreAdjust := 1000 - (1000*memoryRequest)/memoryCapacity

//这里是为了保证burstable能有个更高的 O
56c
OM score
if int(oomScoreAdjust) < (1000 + guaranteedOOMScoreAdj) {
return (1000 + guaranteedOOMScoreAdj)
}

if int(oomScoreAdjust) == besteffortOOMScoreAdj {
return int(oomScoreAdjust - 1)
}
return int(oomScoreAdjust)
}

这个方法里面给不同的pod进行打分,静态Pod、镜像Pod和高优先级Pod,QOS直接被设置成为guaranteed;

然后调用qos的GetPodQOS方法获取一个pod的评分,但是如果一个pod是burstable,那么需要根据其直接使用的内存来进行评分,占用的内存越少,则打分就越高,如果分数小于1000 + guaranteedOOMScoreAdj,也就是2分,那么被直接设置成2分,避免分数过低。

Eviction Manager源码分析

kubelet在实例化一个kubelet对象的时候,调用

eviction.NewManager
新建了一个evictionManager对象。然后kubelet再Run方法开始工作的时候,创建一个goroutine,每5s执行一次updateRuntimeUp。

在updateRuntimeUp中,待确认runtime启动成功后,会调用initializeRuntimeDependentModules完成runtime依赖模块的初始化工作。

然后在initializeRuntimeDependentModules中会调用evictionManager的start方法进行启动。

代码如下,具体的kubelet流程我们留到以后慢慢分析:

func NewMainKubelet(...){
...
evictionManager, evictionAdmitHandler := eviction.NewManager(klet.resourceAnalyzer, evictionConfig, killPodNow(klet.podWorkers, kubeDeps.Recorder), klet.podManager.GetMirrorPodByPod, klet.imageManager, klet.containerGC, kubeDeps.Recorder, nodeRef, klet.clock, etcHostsPathFunc)

klet.evictionManager = evictionManager
...
}

func (kl *Kubelet) Run(updates <-chan kubetypes.PodUpdate) {
...
go wait.Until(kl.updateRuntimeUp, 5*time.Second, wait.NeverStop)
...
}

func (kl *Kubelet) updateRuntimeUp() {
...
kl.oneTimeInitializer.Do(kl.initializeRuntimeDependentModules)
...
}

func (kl *Kubelet) initializeRuntimeDependentModules() {
...
kl.evictionManager.Start(kl.StatsProvider, kl.GetActivePods, kl.podResourcesAreReclaimed, evictionMonitoringPeriod)
...
}

下面我们来到\pkg\kubelet\eviction\eviction_manager.go去看一下Start方法怎么实现eviction的。

managerImp#Start

// 开启一个控制循环去监视和响应资源过低的情况
func (m *managerImpl) Start(diskInfoProvider DiskInfoProvider, podFunc ActivePodsFunc, podCleanedUpFunc PodCleanedUpFunc, monitoringInterval time.Duration) {
thresholdHandler := func(message string) {
klog.Infof(message)
m.synchronize(diskInfoProvider, podFunc)
}
//是否要利用kernel memcg notification
if m.config.KernelMemcgNotification {
for _, threshold := range m.config.Thresholds {
if threshold.Signal == evictionapi.SignalMemoryAvailable || threshold.Signal == evictionapi.SignalAllocatableMemoryAvailable {
notifier, err := NewMemoryThresholdNotifier(threshold, m.config.PodCgroupRoot, &CgroupNotifierFactory{}, thresholdHandler)
if err != nil {
klog.Warningf("eviction manager: failed to create memory threshold notifier: %v", err)
} else {
go notifier.Start()
m.thresholdNotifiers = append(m.thresholdNotifiers, notifier)
}
}
}
}
// start the eviction manager monitoring
// 启动一个goroutine,for循环里每隔monitoringInterval(10s)执行一次synchronize
go func() {
for {
//synchronize是主要的eviction控制循环,返回被kill的pod,或返回nill
if evictedPods := m.synchronize(diskInfoProvider, podFunc); evictedPods != nil {
klog.Infof("eviction manager: pods %s evicted, waiting for pod to be cleaned up", format.Pods(evictedPods))
m.waitForPodsCleanup(podCleanedUpFunc, evictedPods)
} else {
time.Sleep(monitoringInterval)
}
}
}()
}

下面的synchronize方法会很长,需要点耐心:

managerImpl#synchronize

  1. 根据上面介绍的不同的eviction signal会有不同的排序方法,以及设置节点资源回收方法

    func (m *managerImpl) synchronize(diskInfoProvider DiskInfoProvider, podFunc ActivePodsFunc) []*v1.Pod {
    ...
    if m.dedicatedImageFs == nil {
    hasImageFs, ok := diskInfoProvider.HasDedicatedImageFs()
    if ok != nil {
    return nil
    }
    m.dedicatedImageFs = &hasImageFs
    //注册各个eviction signal所对应的资源排序方法
    m.signalToRankFunc = buildSignalToRankFunc(hasImageFs)
    // 注册节点资源回收方法,例如imagefs.avaliable对应的是删除无用容器和无用镜像
    m.signalToNodeReclaimFuncs = buildSignalToNodeReclaimFuncs(m.imageGC, m.containerGC, hasImageFs)
    }
    ...
    }

    看一下buildSignalToRankFunc方法的实现:

    func buildSignalToRankFunc(withImageFs bool) map[evictionapi.Signal]rankFunc {
    signalToRankFunc := map[evictionapi.Signal]rankFunc{
    evictionapi.SignalMemoryAvailable:            rankMemoryPressure,
    evictionapi.SignalAllocatableMemoryAvailable: rankMemoryPressure,
    evictionapi.SignalPIDAvailable:               rankPIDPressure,
    }
    if withImageFs {
    signalToRankFunc[evictionapi.SignalNodeFsAvailable] = rankDiskPressureFunc([]fsStatsType{fsStatsLogs, fsStatsLocalVolumeSource}, v1.ResourceEphemeralStorage)
    signalToRankFunc[evictionapi.SignalNodeFsInodesFree] = rankDiskPressureFunc([]fsStatsType{fsStatsLogs, fsStatsLocalVolumeSource}, resourceInodes)
    signalToRankFunc[evictionapi.SignalImageFsAvailable] = rankDiskPressureFunc([]fsStatsType{fsStatsRoot}, v1.ResourceEphemeralStorage)
    signalToRankFunc[evictionapi.SignalImageFsInodesFree] = rankDiskPressureFunc([]fsStatsType{fsStatsRoot}, resourceInodes)
    } else {
    signalToRankFunc[evictionapi.SignalNodeFsAvailable] = rankDiskPressureFunc([]fsStatsType{fsStatsRoot, fsStatsLogs, fsStatsLocalVolumeSource}, v1.ResourceEphemeralStorage)
    signalToRankFunc[evictionapi.SignalNodeFsInodesFree] = rankDiskPressureFunc([]fsStatsType{fsStatsRoot, fsStatsLogs, fsStatsLocalVolumeSource}, resourceInodes)
    signalToRankFunc[evictionapi.SignalImageFsAvailable] = rankDiskPressureFunc([]fsStatsType{fsStatsRoot, fsStatsLogs, fsStatsLocalVolumeSource}, v1.ResourceEphemeralStorage)
    signalToRankFunc[evictionapi.SignalImageFsInodesFree] = rankDiskPressureFunc([]fsStatsType{fsStatsRoot, fsStatsLogs, fsStatsLocalVolumeSource}, resourceInodes)
    }
    return signalToRankFunc
    }

    这个方法里面会将各个eviction signal的排序方法放入到一个map中返回,如MemoryAvailable、NodeFsAvailable、ImageFsAvailable等。

  2. 获取所有的活跃的pod,以及整体的stat信息

    func (m *managerImpl) synchronize(diskInfoProvider DiskInfoProvider, podFunc ActivePodsFunc) []*v1.Pod {
    ...
    //获取当前active的pods
    activePods := podFunc()
    updateStats := true
    //获取节点的整体概况,即nodeStsts和podStats
    summary, err := m.summaryProvider.Get(updateStats)
    if err != nil {
    klog.Errorf("eviction manager: failed to get summary stats: %v", err)
    return nil
    }
    //如果Notifiers有超过10s没有刷新,那么更新Notifiers
    if m.clock.Since(m.thresholdsLastUpdated) > notifierRefreshInterval {
    m.thresholdsLastUpdated = m.clock.Now()
    for _, notifier := range m.thresholdNotifiers {
    if err := notifier.UpdateThreshold(summary); err != nil {
    klog.Warningf("eviction manager: failed to update %s: %v", notifier.Description(), err)
    }
    }
    }
    ...
    }
  3. 根据summary信息创建相应的统计信息到observations对象中

    func (m *managerImpl) synchronize(diskInfoProvider DiskInfoProvider, podFunc ActivePodsFunc) []*v1.Pod {
    ...
    //根据summary信息创建相应的统计信息到observations对象中,如SignalMemoryAvailable、SignalNodeFsAvailable等。
    observations, statsFunc := makeSignalObservations(summary)
    ...
    }

    下面抽取部分代码makeSignalObservations

    func makeSignalObservations(summary *statsapi.Summary) (signalObservations, statsFunc) {
    ...
    if memory := summary.Node.Memory; memory != nil && memory.AvailableBytes != nil && memory.WorkingSetBytes != nil {
    result[evictionapi.SignalMemoryAvailable] = signalObservation{
    available: resource.NewQuantity(int64(*memory.AvailableBytes), resource.BinarySI),
    capacity:  resource.NewQuantity(int64(*memory.AvailableBytes+*memory.WorkingSetBytes), resource.BinarySI),
    time:      memory.Time,
    }
    }
    ...
    }

    这个方法主要是将summary里面的资源利用情况根据不同的eviction signal封装到result里面返回。

  4. 根据获取的observations判断是否已到达阈值的thresholds

    func (m *managerImpl) synchronize(diskInfoProvider DiskInfoProvider, podFunc ActivePodsFunc) []*v1.Pod {
    ...
    //根据获取的observations判断是否已到达阈值的thresholds,然后返回
    thresholds = thresholdsMet(thresholds, observations, false)
    
    if len(m.thresholdsMet) > 0 {
    //Minimum eviction reclaim 策略
    thresholdsNotYetResolved := thresholdsMet(m.thresholdsMet, observations, true)
    thresholds = mergeThresholds(thresholds, thresholdsNotYetResolved)
    }
    ...
    }

    thresholdsMet

    func thresholdsMet(thresholds []evictionapi.Threshold, observations signalObservations, enforceMinReclaim bool) []evictionapi.Threshold {
    results := []evictionapi.Threshold{}
    for i := range thresholds {
    threshold := thresholds[i]
    observed, found := observations[threshold.Signal]
    if !found {
    klog.Warningf("eviction manager: no observation found for eviction signal %v", threshold.Signal)
    continue
    }
    thresholdMet := false
    // 根据资源容量获取阈值的资源大小
    quantity := evictionapi.GetThresholdQuantity(threshold.Value, observed.capacity)
    //Minimum eviction reclaim 策略,具体看:https://kubernetes.io/docs/tasks/administer-cluster/out-of-resource/#minimum-eviction-reclaim
    if enforceMinReclaim && threshold.MinReclaim != nil {
    quantity.Add(*evictionapi.GetThresholdQuantity(*threshold.MinReclaim, observed.capacity))
    }
    //如果observed.available比quantity大,那么返回1
    thresholdResult := quantity.Cmp(*observed.available)
    //检查Operator标识符
    switch threshold.Operator {
    //如果是小于号"<",当thresholdResult大于0,返回true
    case evictionapi.OpLessThan:
    thresholdMet = thresholdResult > 0
    }
    //如果append到results,表示已经到达阈值
    if thresholdMet {
    results = append(results, threshold)
    }
    }
    return results
    }

    thresholdsMet会遍历整个thresholds,然后从observations里面获取evictio 2088 n signal对应的资源情况。因为我们上面讲了设置的threshold可以是1Gi,也可以是百分比,所以需要调用GetThresholdQuantity方法换算一下,得到quantity;

    然后根据Minimum eviction reclaim 策略判断一下是否还需要提高这个需要eviction的资源,具体的信息查看文档:https://kubernetes.io/docs/tasks/administer-cluster/out-of-resource/#minimum-eviction-reclaim;

    然后用quantity和available比较一下,如果已达阈值,那么加入到results集合中返回。

  5. 记录eviction signal 第一次的时间,并将Eviction Signals映射到对应的Node Conditions

    func (m *managerImpl) synchronize(diskInfoProvider DiskInfoProvider, podFunc ActivePodsFunc) []*v1.Pod {
    ...
    now := m.clock.Now()
    //主要用来记录 eviction signal 第一次的时间,没有则设置 now 时间
    thresholdsFirstObservedAt := thresholdsFirstObservedAt(thresholds, m.thresholdsFirstObservedAt, now)
    
    // the set of node conditions that are triggered by currently observed thresholds
    // Kubelet会将对应的Eviction Signals映射到对应的Node Conditions
    nodeConditions := nodeConditions(thresholds)
    if len(nodeConditions) > 0 {
    klog.V(3).Infof("eviction manager: node conditions - observed: %v", nodeConditions)
    }
    ...
    }

    nodeConditions

    func nodeConditions(thresholds []evictionapi.Threshold) []v1.NodeConditionType {
    results := []v1.NodeConditionType{}
    for _, threshold := range thresholds {
    if nodeCondition, found := signalToNodeCondition[threshold.Signal]; found {
    //检查results里是否已有nodeCondition
    if !hasNodeCondition(results, nodeCondition) {
    results = append(results, nodeCondition)
    }
    }
    }
    return results
    }

    nodeConditions方法主要就是根据signalToNodeCondition来映射对应的nodeCondition,其中nodeCondition如下:

    signalToNodeCondition = map[evictionapi.Signal]v1.NodeConditionType{}
    signalToNodeCondition[evictionapi.SignalMemoryAvailable] = v1.NodeMemoryPressure
    signalToNodeCondition[evictionapi.SignalAllocatableMemoryAvailable] = v1.NodeMemoryPressure
    signalToNodeCondition[evictionapi.SignalImageFsAvailable] = v1.NodeDiskPressure
    signalToNodeCondition[evictionapi.SignalNodeFsAvailable] = v1.NodeDiskPressure
    signalToNodeCondition[evictionapi.SignalImageFsInodesFree] = v1.NodeDiskPressure
    signalToNodeCondition[evictionapi.SignalNodeFsInodesFree] = v1.NodeDiskPressure
    signalToNodeCondition[evictionapi.SignalPIDAvailable] = v1.NodePIDPressure

    也就是将Eviction Signals分别映射成了MemoryPressure或DiskPressure,整理出来的表格如下:

    Node Condition Eviction Signal Description
    MemoryPressure memory.available Available memory on the node has satisfied an eviction threshold
    DiskPressure nodefs.available, nodefs.inodesFree, imagefs.available, or imagefs.inodesFree Available disk space and inodes on either the node's root filesystem or image filesystem has satisfied an eviction threshold
  6. 本轮 node condition 与上次的observed合并,以最新的为准

    func (m *managerImpl) synchronize(diskInfoProvider DiskInfoProvider, podFunc ActivePodsFunc) []*v1.Pod {
    ...
    //本轮 node condition 与上次的observed合并,以最新的为准
    nodeConditionsLastObservedAt := nodeConditionsLastObservedAt(nodeConditions, m.nodeConditionsLastObservedAt, now)
    ...
    }
  7. 防止Node的资源不断在阈值附近波动,从而不断变动Node Condition值

    func (m *managerImpl) synchronize(diskInfoProvider DiskInfoProvider, podFunc ActivePodsFunc) []*v1.Pod {
    ...
    //PressureTransitionPeriod参数默认为5分钟
    //防止Node的资源不断在阈值附近波动,从而不断变动Node Condition值
    //具体查看文档:https://kubernetes.io/docs/tasks/administer-cluster/out-of-resource/#oscillation-of-node-conditions
    nodeConditions = nodeConditionsObservedSince(nodeConditionsLastObservedAt, m.config.PressureTransitionPeriod, now)
    if len(nodeConditions) > 0 {
    klog.V(3).Infof("eviction manager: node conditions - transition period not met: %v", nodeConditions)
    }
    ...
    }

    nodeConditionsObservedSince

    func nodeConditionsObservedSince(observedAt nodeConditionsObservedAt, period time.Duration, now time.Time) []v1.NodeConditionType {
    results := []v1.NodeConditionType{}
    for nodeCondition, at := range observedAt {
    duration := now.Sub(at)
    if duration < period {
    results = append(results, nodeCondition)
    }
    }
    return results
    }

    如果已经超过了5分钟,那么需要排除。

  8. 对eviction-soft做判断

    func (m *managerImpl) synchronize(diskInfoProvider DiskInfoProvider, podFunc ActivePodsFunc) []*v1.Pod {
    ...
    //设置 eviction-soft-grace-period,默认为90秒,超过该值加入阈值集合
    thresholds = thresholdsMetGracePeriod(thresholdsFirstObservedAt, now)
    ...
    }

    thresholdsMetGracePeriod

    func thresholdsMetGracePeriod(observedAt thresholdsObservedAt, now time.Time) []evictionapi.Threshold {
    results := []evictionapi.Threshold{}
    for threshold, at := range observedAt {
    duration := now.Sub(at)
    //Soft Eviction Thresholds,必须要等一段时间之后才能进行trigger
    if duration < threshold.GracePeriod {
    klog.V(2).Infof("eviction manager: eviction criteria not yet met for %v, duration: %v", formatThreshold(threshold), duration)
    continue
    }
    results = append(results, threshold)
    }
    return results
    }
  9. 设值,然后比较更新

    func (m *managerImpl) synchronize(diskInfoProvider DiskInfoProvider, podFunc ActivePodsFunc) []*v1.Pod {
    ...
    // update internal state
    m.Lock()
    m.nodeConditions = nodeConditions
    m.thresholdsFirstObservedAt = thresholdsFirstObservedAt
    m.nodeConditionsLastObservedAt = nodeConditionsLastObservedAt
    m.thresholdsMet = thresholds
    
    // 阈值集合跟上次比较是否需要更新
    thresholds = thresholdsUpdatedStats(thresholds, observations, m.lastObservations)
    debugLogThresholdsWithObservation("thresholds - updated stats", thresholds, observations)
    
    //将本次的信息设置为上次信息
    m.lastObservations = observations
    m.Unlock()
    ...
    }
  10. 排序之后找到第一个需要释放的threshold,以及对应的resource

    func (m *managerImpl) synchronize(diskInfoProvider DiskInfoProvider, podFunc ActivePodsFunc) []*v1.Pod {
    ...
    //如果没有 eviction signal 集合则本轮结束流程
    if len(thresholds) == 0 {
    klog.V(3).Infof("eviction manager: no resources are starved")
    return nil
    }
    
    //排序之后获取thresholds集合中的第一个元素
    sort.Sort(byEvictionPriority(thresholds))
    thresholdToReclaim, resourceToReclaim, foundAny := getReclaimableThreshold(thresholds)
    if !foundAny {
    return nil
    }
    ...
    }

    getReclaimableThreshold

    func getReclaimableThreshold(thresholds []evictionapi.Threshold) (evictionapi.Threshold, v1.ResourceName, bool) {
    //遍历thresholds,然后根据对应的Eviction Signals找到对应的resource
    for _, thresholdToReclaim := range thresholds {
    if resourceToReclaim, ok := signalToResource[thresholdToReclaim.Signal]; ok {
    return thresholdToReclaim, resourceToReclaim, true
    }
    klog.V(3).Infof("eviction manager: threshold %s was crossed, but reclaim is not implemented for this threshold.", thresholdToReclaim.Signal)
    }
    return evictionapi.Threshold{}, "", false
    }

    下面我们看一下signalToResource的定义:< ad8 /p>

    signalToResource = map[evictionapi.Signal]v1.ResourceName{}
    signalToResource[evictionapi.SignalMemoryAvailable] = v1.ResourceMemory
    signalToResource[evictionapi.SignalAllocatableMemoryAvailable] = v1.ResourceMemory
    signalToResource[evictionapi.SignalImageFsAvailable] = v1.ResourceEphemeralStorage
    signalToResource[evictionapi.SignalImageFsInodesFree] = resourceInodes
    signalToResource[evictionapi.SignalNodeFsAvailable] = v1.ResourceEphemeralStorage
    signalToResource[evictionapi.SignalNodeFsInodesFree] = resourceInodes
    signalToResource[evictionapi.SignalPIDAvailable] = resourcePids
    signalToResource将Eviction Signals分成了memory、ephemeral-storage、inodes、pids几类。

  11. 回收节点级别的资源

```go
func (m *managerImpl) synchronize(diskInfoProvider DiskInfoProvider, podFunc ActivePodsFunc) []*v1.Pod {
...
//回收节点级别的资源
if m.reclaimNodeLevelResources(thresholdToReclaim.Signal, resourceToReclaim) {
klog.Infof("eviction manager: able to reduce %v pressure without evicting pods.", resourceToReclaim)
return nil
}
...
}
```

**reclaimNodeLevelResources**

```go
func (m *managerImpl) reclaimNodeLevelResources(signalToReclaim evictionapi.Signal, resourceToReclaim v1.ResourceName) bool {
//调用buildSignalToNodeReclaimFuncs中设置的方法
nodeReclaimFuncs := m.signalToNodeReclaimFuncs[signalToReclaim]
for _, nodeReclaimFunc := range nodeReclaimFuncs {
// 删除没用使用到的images或 删除已经是dead状态的Pod 和 container
if err := nodeReclaimFunc(); err != nil {
klog.Warningf("eviction manager: unexpected error when attempting to reduce %v pressure: %v", resourceToReclaim, err)
}

}
//回收之后再检查一下资源占用情况,如果没有达到阈值,那么直接结束
if len(nodeReclaimFuncs) > 0 {
summary, err := m.summaryProvider.Get(true)
if err != nil {
klog.Errorf("eviction manager: failed to get summary stats after resource reclaim: %v", err)
return false
}

observations, _ := makeSignalObservations(summary)
debugLogObservations("observations after resource reclaim", observations)

thresholds := thresholdsMet(m.config.Thresholds, observations, false)
debugLogThresholdsWithObservation("thresholds after resource reclaim - ignoring grace period", thresholds, observations)

if len(thresholds) == 0 {
return true
}
}
return false
}
```

首先根据需要释放的signal从signalToNodeReclaimFuncs中找到对应的释放资源的方法,这个方法在上面buildSignalToNodeReclaimFuncs中设置的,如:

```
nodeReclaimFuncs{containerGC.DeleteAllUnusedContainers, imageGC.Del
56c
eteUnusedImages}
```

这个方法会调用相应的GC方法,删除无用的container以及无用的images来释放资源。

然后会检查释放完资源之后是否依然超过阈值,如果没有的话就直接结束了。
  1. 获取相应的排序函数并进行排序

    func (m *managerImpl) synchronize(diskInfoProvider DiskInfoProvider, podFunc ActivePodsFunc) []*v1.Pod {
    ...
    //得到上面的eviction signal 排序函数,在buildSignalToRankFunc方法中设置
    rank, ok := m.signalToRankFunc[thresholdToReclaim.Signal]
    if !ok {
    klog.Errorf("eviction manager: no ranking function for signal %s", thresholdToReclaim.Signal)
    return nil
    }
    
    //如果没有 active pod 直接返回
    if len(activePods) == 0 {
    klog.Errorf("eviction manager: eviction thresholds have been met, but no pods are active to evict")
    return nil
    }
    
    //将pod按照特定资源排序
    rank(activePods, statsFunc)
    ...
    }
  2. 将排好序的pod删除,并返回

    func (m *managerImpl) synchronize(diskInfoProvider DiskInfoProvider, podFunc ActivePodsFunc) []*v1.Pod {
    ...
    for i := range activePods {
    pod := activePods[i]
    gracePeriodOverride := int64(0)
    if !isHardEvictionThreshold(thresholdToReclaim) {
    gracePeriodOverride = m.config
    ad0
    .MaxPodGracePeriodSeconds
    }
    message, annotations := evictionMessage(resourceToReclaim, pod, statsFunc)
    //kill pod
    if m.evictPod(pod, gracePeriodOverride, message, annotations) {
    metrics.Evictions.WithLabelValues(string(thresholdToReclaim.Signal)).Inc()
    return []*v1.Pod{pod}
    }
    }
    ...
    }

    只要有一个pod被删除了,那么就返回~

到这里eviction manager就分析完了~

总结

这一篇讲解了其中资源控制是怎么做的,理解了通过limit和request的设置会影响到pod被删除的优先级,所以我们在设置pod的时候尽量设置合理的limit和request可以不那么容易被kill掉;然后通过分析了源码知道了limit和request会影响到QOS的评分,从而影响到pod被kill掉的优先级。

接下来通过源码分析了k8s中对阈值的设定是怎样的,当资源不够的时候pod是根据什么条件被kill掉的,这一部分花了很大的篇幅来介绍。通过源码也可以知道在eviction发生的时候k8s也是做了很多的考虑,比如说对于节点状态振荡应该怎么处理、首先应该回收什么类型的资源、minimum-reclaim最小回收资源在源码里是怎么做到的等等。

Reference

https://kubernetes.io/docs/tasks/configure-pod-container/assign-cpu-resource/

https://kubernetes.io/docs/tasks/configure-pod-container/assign-memory-resource/

https://kubernetes.io/docs/tasks/configure-pod-container/quality-service-pod/

https://kubernetes.io/docs/tasks/administer-cluster/out-of-resource/

https://zhuanlan.zhihu.com/p/38359775

https://cloud.tencent.com/developer/article/1097431

https://developer.aliyun.com/article/679216

https://www.geek-share.com/detail/2698520254.html

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