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Kubernetes Resource QoS机制解读

摘要：本文对Kubernetes Resource QoS介绍，机制解析和简单的源码分析。

Kubernetes Resource QoS Classes介绍

Kubernetes根据Pod中Containers Resource的 request 和 limit 的值来定义Pod的QoS Class。

对于每一种Resource都可以将容器分为3中QoS Classes: Guaranteed , Burstable , and Best-Effort ，它们的QoS级别依次递减。

Guaranteed 如果Pod中所有Container的所有Resource的 limit 和 request 都相等且不为0，则这个Pod的QoS Class就是Guaranteed。

注意，如果一个容器只指明了limit，而未指明request，则表明request的值等于limit的值。

Examples:

containers:
    name: foo
        resources:
            limits:
                cpu: 10m
                memory: 1Gi
    name: bar
        resources:
            limits:
                cpu: 100m
                memory: 100Mi

containers:
    name: foo
        resources:
            limits:
                cpu: 10m
                memory: 1Gi
            requests:
                cpu: 10m
                memory: 1Gi

    name: bar
        resources:
            limits:
                cpu: 100m
                memory: 100Mi
            requests:
                cpu: 100m
                memory: 100Mi

Best-Effort 如果Pod中所有容器的所有Resource的request和limit都没有赋值，则这个Pod的QoS Class就是Best-Effort.

Examples:

containers:
    name: foo
        resources:
    name: bar
        resources:

Burstable 除了符合Guaranteed和Best-Effort的场景，其他场景的Pod QoS Class都属于Burstable。

当limit值未指定时，其有效值其实是对应Node Resource的Capacity。

Examples:

容器 bar 没有对Resource进行指定。

containers:
    name: foo
        resources:
            limits:
                cpu: 10m
                memory: 1Gi
            requests:
                cpu: 10m
                memory: 1Gi

    name: bar

容器 foo 和 bar 对不同的Resource进行了指定。

containers:
    name: foo
        resources:
            limits:
                memory: 1Gi

    name: bar
        resources:
            limits:
                cpu: 100m

容器 foo 未指定limit，容器 bar 未指定request和limit。

containers:
    name: foo
        resources:
            requests:
                cpu: 10m
                memory: 1Gi

    name: bar

可压缩/不可压缩资源的区别

kube-scheduler调度时，是基于Pod的 request 值进行Node Select完成调度的。Pod和它的所有Container都不允许Consume limit指定的有效值(if have)。

How the request and limit are enforced depends on whether the resource is compressible or incompressible .

Compressible Resource Guarantees

For now, we are only supporting CPU .
Pods are guaranteed to get the amount of CPU they request, they may or may not get additional CPU time (depending on the other jobs running). This isn’t fully guaranteed today because cpu isolation is at the container level. Pod level cgroups will be introduced soon to achieve this goal.
Excess CPU resources will be distributed based on the amount of CPU requested. For example, suppose container A requests for 600 milli CPUs, and container B requests for 300 milli CPUs. Suppose that both containers are trying to use as much CPU as they can. Then the extra 10 milli CPUs will be distributed to A and B in a 2:1 ratio (implementation discussed in later sections).
Pods will be throttled if they exceed their limit. If limit is unspecified, then the pods can use excess CPU when available.

Incompressible Resource Guarantees

For now, we are only supporting memory .
Pods will get the amount of memory they request, if they exceed their memory request, they could be killed (if some other pod needs memory), but if pods consume less memory than requested, they will not be killed (except in cases where system tasks or daemons need more memory).
When Pods use more memory than their limit, a process that is using the most amount of memory, inside one of the pod’s containers, will be killed by the kernel.

Admission/Scheduling Policy

Pods will be admitted by Kubelet & scheduled by the scheduler based on the sum of requests of its containers. The scheduler & kubelet will ensure that sum of requests of all containers is within the node’sallocatable capacity (for both memory and CPU).

如何根据不同的QoS回收Resources

CPUPods will not be killed if CPU guarantees cannot be met (for example if system tasks or daemons take up lots of CPU), they will be temporarily throttled.
MemoryMemory is an incompressible resource and so let’s discuss the semantics of memory management a bit.
- Best-Effort pods will be treated as lowest priority. Processes in these pods are the first to get killed if the system runs out of memory.
  
  These containers can use any amount of free memory in the node though.
- Guaranteed pods are considered top-priority and are guaranteed to not be killed until they exceed their limits, or if the system is under memory pressure and there are no lower priority containers that can be evicted.
- Burstable pods have some form of minimal resource guarantee, but can use more resources when available.
  
  Under system memory pressure, these containers are more likely to be killed once they exceed their requests and no Best-Effort pods exist.

OOM Score configuration at the Nodes

Pod OOM score configuration

Note that the OOM score of a process is 10 times the % of memory the process consumes, adjusted by OOM_SCORE_ADJ, barring exceptions (e.g. process is launched by root). Processes with higher OOM scores are killed.
The base OOM score is between 0 and 1000, so if process A’s OOM_SCORE_ADJ - process B’s OOM_SCORE_ADJ is over a 1000, then process A will always be OOM killed before B.
The final OOM score of a process is also between 0 and 1000

Best-effort

Set OOM_SCORE_ADJ: 1000
So processes in best-effort containers will have an OOM_SCORE of 1000

Guaranteed

Set OOM_SCORE_ADJ: -998
So processes in guaranteed containers will have an OOM_SCORE of 0 or 1

Burstable

If total memory request > 99.8% of available memory, OOM_SCORE_ADJ: 2
Otherwise, set OOM_SCORE_ADJ to 1000 - 10 * (% of memory requested)
This ensures that the OOM_SCORE of burstable pod is > 1
If memory request is 0 , OOM_SCORE_ADJ is set to 999 .
So burstable pods will be killed if they conflict with guaranteed pods
If a burstable pod uses less memory than requested, its OOM_SCORE < 1000
So best-effort pods will be killed if they conflict with burstable pods using less than requested memory
If a process in burstable pod’s container uses more memory than what the container had requested, its OOM_SCORE will be 1000, if not its OOM_SCORE will be < 1000
Assuming that a container typically has a single big process, if a burstable pod’s container that uses more memory than requested conflicts with another burstable pod’s container using less memory than requested, the former will be killed
If burstable pod’s containers with multiple processes conflict, then the formula for OOM scores is a heuristic, it will not ensure “Request and Limit” guarantees.

Pod infra containers or Special Pod init process

OOM_SCORE_ADJ : -998

Kubelet, Docker

OOM_SCORE_ADJ : -999 (won’t be OOM killed)
Hack, because these critical tasks might die if they conflict with guaranteed containers. In the future, we should place all user-pods into a separate cgroup, and set a limit on the memory they can consume.

源码分析

QoS的源码位于： pkg/kubelet/qos ，代码非常简单，主要就两个文件 pkg/kubelet/qos/policy.go , pkg/kubelet/qos/qos.go 。

上面讨论的各个QoS Class对应的 OOM_SCORE_ADJ 定义在：

pkg/kubelet/qos/policy.go:21

const (
    PodInfraOOMAdj        int = -998
    KubeletOOMScoreAdj    int = -999
    DockerOOMScoreAdj     int = -999
    KubeProxyOOMScoreAdj  int = -999
    guaranteedOOMScoreAdj int = -998
    besteffortOOMScoreAdj int = 1000
)

容器的OOM_SCORE_ADJ的计算方法定义在：

pkg/kubelet/qos/policy.go:40

func GetContainerOOMScoreAdjust(pod *v1.Pod, container *v1.Container, memoryCapacity int64) int {
    switch GetPodQOS(pod) {
    case Guaranteed:
        // Guaranteed containers should be the last to get killed.
        return guaranteedOOMScoreAdj
    case BestEffort:
        return besteffortOOMScoreAdj
    }

    // Burstable containers are a middle tier, between Guaranteed and Best-Effort. Ideally,
    // we want to protect Burstable containers that consume less memory than requested.
    // The formula below is a heuristic. A container requesting for 10% of a system's
    // memory will have an OOM score adjust of 900. If a process in container Y
    // uses over 10% of memory, its OOM score will be 1000. The idea is that containers
    // which use more than their request will have an OOM score of 1000 and will be prime
    // targets for OOM kills.
    // Note that this is a heuristic, it won't work if a container has many small processes.
    memoryRequest := container.Resources.Requests.Memory().Value()
    oomScoreAdjust := 1000 - (1000*memoryRequest)/memoryCapacity
    // A guaranteed pod using 100% of memory can have an OOM score of 10. Ensure
    // that burstable pods have a higher OOM score adjustment.
    if int(oomScoreAdjust) < (1000 + guaranteedOOMScoreAdj) {
        return (1000 + guaranteedOOMScoreAdj)
    }
    // Give burstable pods a higher chance of survival over besteffort pods.
    if int(oomScoreAdjust) == besteffortOOMScoreAdj {
        return int(oomScoreAdjust - 1)
    }
    return int(oomScoreAdjust)
}

获取Pod的QoS Class的方法为：

pkg/kubelet/qos/qos.go:50

// GetPodQOS returns the QoS class of a pod.
// A pod is besteffort if none of its containers have specified any requests or limits.
// A pod is guaranteed only when requests and limits are specified for all the containers and they are equal.
// A pod is burstable if limits and requests do not match across all containers.
func GetPodQOS(pod *v1.Pod) QOSClass {
    requests := v1.ResourceList{}
    limits := v1.ResourceList{}
    zeroQuantity := resource.MustParse("0")
    isGuaranteed := true
    for _, container := range pod.Spec.Containers {
        // process requests
        for name, quantity := range container.Resources.Requests {
            if !supportedQoSComputeResources.Has(string(name)) {
                continue
            }
            if quantity.Cmp(zeroQuantity) == 1 {
                delta := quantity.Copy()
                if _, exists := requests[name]; !exists {
                    requests[name] = *delta
                } else {
                    delta.Add(requests[name])
                    requests[name] = *delta
                }
            }
        }
        // process limits
        qosLimitsFound := sets.NewString()
        for name, quantity := range container.Resources.Limits {
            if !supportedQoSComputeResources.Has(string(name)) {
                continue
            }
            if quantity.Cmp(zeroQuantity) == 1 {
                qosLimitsFound.Insert(string(name))
                delta := quantity.Copy()
                if _, exists := limits[name]; !exists {
                    limits[name] = *delta
                } else {
                    delta.Add(limits[name])
                    limits[name] = *delta
                }
            }
        }

        if len(qosLimitsFound) != len(supportedQoSComputeResources) {
            isGuaranteed = false
        }
    }
    if len(requests) == 0 && len(limits) == 0 {
        return BestEffort
    }
    // 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
            }
        }
    }
    if isGuaranteed &&
        len(requests) == len(limits) {
        return Guaranteed
    }
    return Burstable
}

PodQoS会在eviction_manager和scheduler的Predicates阶段被调用，也就说会在k8s处理超配和调度预选阶段中被使用。

Kubernetes Resource QoS机制解读