手记 – 关于Kubernetes(P1)

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资料

 

基础概念

什么是云原生:

先看看官方定义

Cloud native technologies empower organizations to build and run scalable applications in modern, dynamic environments such as public, private, and hybrid clouds. Containers, service meshes, microservices, immutable infrastructure, and declarative APIs exemplify this approach.

These techniques enable loosely coupled systems that are resilient, manageable, and observable. Combined with robust automation, they allow engineers to make high-impact changes frequently and predictably with minimal toil.

The Cloud Native Computing Foundation seeks to drive adoption of this paradigm by fostering and sustaining an ecosystem of open source, vendor-neutral projects. We democratize state-of-the-art patterns to make these innovations accessible for everyone.

简而言之,云原生就是在多种云环境中,构建高可用,弹性伸缩,方便管理和监控的应用。

CNCF(Cloud Native Computing Foundation):

云原生计算基金会,Linux旗下非盈利基金会。谷歌容器编排技术Borg(k8s前身)开源后与Linux共同成立了CNCF。致力于推动云原生相关技术的发展。

云原生的技术:

参考CNCF的路线图(trail map),主要和代表技术为:

  1. 容器化:docker
  2. CI/CD(Continuous Integration / Delivery):Argo
  3. 编排:k8s+helm
  4. 监控&分析:Prometheus for monitoring, Fluentd for logging, Jaeger for tracing
  5. 服务代理(proxy),发现(discovery),治理(mesh):CoreDNS, Envoy, Linkerd
  6. 网络和安全:Calico, Flannel, OPA, Falco
  7. 分布式数据库和存储:Vitess(可分片的mysql),etcd, TiKV
  8. 流处理&消息处理
  9. 容器镜像库和运行环境:Harbor(私有镜像仓库)
  10. 软件发布

参考CNCF的全景图(landscape),可以了解更多的项目,包括已经毕业的,孵化中的,CNCF成员自己的项目。。。等等。

云原生应用的特性(什么是云原生应用)

TBD

 

回顾容器化发展:

物理机部署的缺点是:资源不存在边界,隔离性差,扩展费用昂贵。

虚拟机部署:解决物理机部署的缺点

容器化部署:共享OS,相比VM更轻量级

k8s发展背景:

Kubernetes(k8s): 希腊语舵手(helmsman)所以logo是一个舵哈哈

可以看出K8s只是云原生版图中的一部分,是一个容器编排系统(Container Ochestration):

无论是基于云架构,还是基于企业内部的物理机/虚机资源池,容器化已经成为广泛采纳的部署技术,但是容器资源的管理,调度,编排是复杂的问题,所以出现了一些解决方案,譬如Mesos,K8s,Swarm。

例如我司中间件云服务的就是基于就是在IaaS上的一个k8s集群,用户的请求会通过我们的控制层传达到k8s集群,进行相关资源的管理调度和编排。

K8s特性:

  1. Automated rollouts and rollbacks
  2. Service discovery and load balancing
  3. Storage orchestration
  4. Secret and configuration management
  5. Resource Management for Pods and Containers
  6. Batch Execution(基于jobs)
  7. IPv4 & IPv6 dual-stack
  8. Horizontal Scaling
  9. Self-healing
  10. Designed for Extensibility

K8s架构:

K8s采用了Master-Worker架构,master就是指图中的control plane控制平面,为了高可用通常也是一个集群。负责管理worker节点和上面的pods。Worker指上图的node节点,pod会部署在上面。

Control-plane的组件:

  1. Kube-api-server:暴露Kubernetes API,是对外的frontend;支持水平扩展。只有它与控制平面的各个组件通信。
  2. Etcd:高可用分布式键值数据库,存储集群信息;基于http+raft协议。
  3. Kube-Scheduler:负责调度pod到某个node上面;考虑的因素包括: individual and collective resource requirements, hardware/software/policy constraints, affinity and anti-affinity specifications, data locality, inter-workload interference, and deadlines
  4. Kube-Controller-manager: 用来执行controller协程;后者是一个控制回路,通过api-server监控pod状态,并使其向期望状态发展
  5. Cloud-controller-manager:The cloud-controller-manager only runs controllers that are specific to your cloud provider;通过上图的 cloud provider’s API进行控制。

Node上的组件:

  1. Kubelet: 负责管理node上的pod(a set of containers)
  2. Kube-proxy: 负责网络请求转发;譬如,一系列的pod是通过service向外界提供服务,kube-proxy就是实现service的基础。

还有一些组件可以借助上述组件和k8s的机制进行安装,并且属于kube-system的名称空间下,为集群提供服务,例如CoreDNS。完整可询 https://kubernetes.io/docs/concepts/cluster-administration/addons/

K8s vs istio

TBD

GKE (Google Kubernetes Engine) vs K8S :

GKE是托管的k8s服务,out-of-box,多租户,类似的产品包括AWS的 Amazon Elastic Kubernetes Service (EKS)

K8s vs Mesos vs Swarm

TBD

Why etcd?

  • 数据一致性
  • 支持持久化
  • 高可用
  • 高性能

相关核心概念:

  • Pod:k8s管理的最小单元,可以包括一至多个容器。
  • 资源清单: 定义资源的yaml文件
  • Controller:类似一个控制回路Control Loop,监控资源状态并向理想状态方向调整,例如ReplicaSet, StatefulSet, DaemonSet等等controllers。
  • Operator: k8s的扩展性的体现,自定义资源类型(CRD)及开发对应的自定义controller。
  • Service & Ingress:如何将一组pod以服务形式对外暴露
  • Volume & PV:存储
  • ConfigMap & Secret: 配置和密钥
  • Scheduler: 如何进行pod的调度,故障域,亲和性,污点等概念
  • Authentication & Authorization: 认证 与 鉴权。

工具:

  • Helm:
  • K9s:

关于API Server:

API Server暴露的HTTP接口,使用户与k8s集群,组件与组件之间得以相互通信。

用户有几个常用工具管理集群:restful api, kubectl,kubeadm,k9s。

Restful api是一切的基础,例如我们使用kubectl + yml时,实际上kubectl底层将信息转化为api+json的形式与api server进行通信。

其中restful api是基于OpenAPI规范设计的后者是一个基于Yaml/json的Restful API设计规范同时方便用户/机器理解遵循OpenAPI规范设计的API可以利用工具校验生成文档生成多语言客户端等等

关于k8s中的对象(object,也可以叫资源):

K8s中的一切资源都是对象,包括:pod, rs, deployment, job, service, ingress, volume, configmap, secrete,Namespace, node, role, clusterRole等等

有两个东西用来描述k8s中的实体:spec(资源清单)和status(状态);The Kubernetes control plane continually and actively manages every object’s actual state to match the desired state you supplied.

Namespace-名称空间:

保证对象(object)的隔离性:In Kubernetes, namespaces provides a mechanism for isolating groups of resources within a single cluster. 

但是有些资源是跨namespace的,譬如role。

GVK vs GVR

GVK = GroupVersionKind,GVR = GroupVersionResource。

apiVersion:这个就是 GV 。

kind:这个就是 K。根据 GVK K8s 就能找到你到底要创建什么类型的资源,根据你定义的 Spec 创建好资源之后就成为了 Resource,也就是 GVR。GVK/GVR 就是 K8s 资源的坐标,是我们创建/删除/修改/读取资源的基础。

关于pods

pod是最小部署单元,实际上是一组容器的集合,共享存储和网络资源。可以将pod理解成一个逻辑主机(logical host);pod中的容器共享存储(fs volumes)、网络和命名空间(namespaces)

如何通过kubectl启动一个pod:

apiVersion: v1
kind: Pod
metadata:
  name: nginx
spec:
  containers:
  - name: nginx
    image: nginx:1.14.2
    ports:
- containerPort: 80
kubectl apply -f xxx.yaml

通常不会直接创建一个pod(创建之后无人管理),而是通过controller,譬如deployment, ReplicaSet, statefulSet, job 等等。

一个pod可以包括多个containers,这些container可以共享资源(网络,存储),相互通信,例如sidecar pattern;当然必须要有合理的理由将这些containers结合在一起;否则就应该将他们部署在不同的pod中。

注:一个container内应当尽量只有一个进程。

pod中的共享资源:

Pause container:

之所以pod中的容器能够共享网络,是因为在创建pod之后,首先有一个隐藏的容器被创建了,pause container,之后的容器都会复用它的网络栈。

The ‘pause’ container is a container which holds the network namespace for the pod.

pod之间通信:

通过IP可以直接访问;每个pod(pause 容器)都有全局唯一的IP地址,并且构成一个扁平化的虚拟网络。所有的pod的IP地址资源和真实物理主机的路由关系是存储在etcd中的。

同一个node上pod间通信:走内部docker网桥

不同node上pod间通信有所不同:走物理网卡(src pod ip + src node ip -> dst pod ip + dst node ip)通过flannel实现

容器探针:

pod中的容器可以定义探针,可以周期性的被kubelet进行健康诊断,支持的探针类型:

  1. 容器操作
  2. Tcp socket请求
  3. http get 请求

静态pod:

Static Pods are always bound to one Kubelet on a specific node。kubelet直接管理的pod(而不是controller)。

容器&pod的生命周期:

pod的phase阶段:

  1. Pending:还在schedule,下载image等等
  2. Running:至少一个容器启动
  3. Succeeded:所有容器都成功停止
  4. Failed:所有容器都停止,而且至少一个是以失败状态停止的
  5. Unknown:For some reason the state of the Pod could not be obtained. This phase typically occurs due to an error in communicating with the node where the Pod should be running.

一个pod一旦被创建,就一定遵循上述几个阶段,不会出现类似reschedule到另一个node的状态。

Container的阶段:

Waiting, Running, and Terminated

Status

Pod启动之后更详尽的状态记录在它spec中的status下面,里面有资源在运行时的一些信息;

有下面一些内置的status:

  • PodScheduled: the Pod has been scheduled to a node.
  • ContainersReady: all containers in the Pod are ready.
  • Initialized: all init containers have completed successfully.
  • Ready: the Pod is able to serve requests and should be added to the load balancing pools of all matching Services.

Pod readiness:

在spec中设置readinessGates;允许用户向 Pod Status 中注入额外的自定义反馈或者信号;pod 中的所有 container 都ready并且所有 readinessGates 中定义的状态都是 ‘True’ 之后 Pod 才会被标记为 ready.

kind: Pod
...
spec:
  readinessGates:
    - conditionType: "www.example.com/feature-1"
status:
  conditions:
    - type: Ready                              # 内置的 Pod 状况
      status: "False"
      lastProbeTime: null
      lastTransitionTime: 2018-01-01T00:00:00Z
    - type: "www.example.com/feature-1"        # 额外的 Pod 状况
      status: "False"
      lastProbeTime: null
      lastTransitionTime: 2018-01-01T00:00:00Z
  containerStatuses:
    - containerID: docker://abcd...
      ready: true

When a Pod’s containers are Ready but at least one custom condition is missing or False, the kubelet sets the Pod’s condition to ContainersReady.

探针机制:

A probe is a diagnostic performed periodically by the kubelet on a container

探针的形式:

  • exec
  • grpc
  • httpGet
  • tcpSocket

Readiness Probe -就绪探针

检测是否ready,只有ready才会被驾到Service后面的pod列表里并提供对外服务

Liveness Probe-生存探针

检测容器是否存活

Startup Probe – 启动探针

其他探针不会在startup探针成功之前启动。

Init 容器

A Pod can have multiple containers running apps within it, but it can also have one or more init containers, which are run before the app containers are started.

Init containers are exactly like regular containers, except:

  • Init containers always run to completion.
  • Each init container must complete successfully before the next one starts.

Init 容器有一些牛逼的地方,譬如:

  • 包含一些运行时镜像中没有的依赖
  • 权限可以与应用程序容器不同

例如,可以在init容器中循环检查一个外部依赖是否ready,ready才启动pod;如果超时则exit 1;

Container Lifecycle Hooks

容器在启动后和结束前都有一个hook:PostStart/PreStop

 

控制器

所谓控制器就是一个control loop-控制回路,官方给了一个调温器的例子来说明:

When you set the temperature, that’s telling the thermostat about your desired state. The actual room temperature is the current state. The thermostat acts to bring the current state closer to the desired state, by turning equipment on or off.

contollers都运行在kube-controller-manager上。

A Kubernetes Controller is a routine;一个控制器本质上是一个go 协程;

控制器获取信息,发送指令都是通过API Server间接完成。

CRI: Container Runtime Interface

一个非常重要的模块。Container Runtime是从容器系统中剥离出来专门运行容器的软件功能。K8s为了兼容多种container runtime,抽象出了一层CRI;kubelet 通过cri直接管理容器的运行。

标签和注解

pod上的label标签用于selector进行选择;

pod上的annotation注解用于为pod提供更多的信息。

Owner reference

Owner reference 告诉控制平面某一个对象依赖另外的哪一个对象。Kubernetes uses owner references to give the control plane, and other API clients, the opportunity to clean up related resources before deleting an object. In most cases, Kubernetes manages owner references automatically.

例如,一个RS创建的pod,如果用yaml格式查看:

apiVersion: v1
kind: Pod
metadata:
  creationTimestamp: "2020-02-12T07:06:16Z"
  generateName: frontend-
  labels:
    tier: frontend
  name: frontend-b2zdv
  namespace: default
  ownerReferences:
  - apiVersion: apps/v1
    blockOwnerDeletion: true
    controller: true
    kind: ReplicaSet
    name: frontend
    uid: f391f6db-bb9b-4c09-ae74-6a1f77f3d5cf
...

RC-ReplicationController(deprecated)

A ReplicationController ensures that a specified number of pod replicas are running at any one time

Example:
apiVersion: v1
kind: ReplicationController
metadata:
  name: nginx
spec:
  replicas: 3
  selector:
    app: nginx
  template:
    metadata:
      name: nginx
      labels:
        app: nginx
    spec:
      containers:
      - name: nginx
        image: nginx
        ports:
        - containerPort: 80

保证label selector匹配的pod数量和replicas中的一样

RS-ReplicaSet

增强版本的RC,selector 的表达能力更起强,譬如支持:匹配缺少某个label的pod,包含某个特定label的pod而不管其值如何。

apiVersion: apps/v1
kind: ReplicaSet
metadata:
  name: frontend
  labels:
    app: guestbook
    tier: frontend
spec:
  # modify replicas according to your case
  replicas: 3
  selector:
    matchLabels:
      tier: frontend
  template:
    metadata:
      labels:
        tier: frontend
    spec:
      containers:
      - name: php-redis
        image: gcr.io/google_samples/gb-frontend:v3

Deployment

不直接管理pod,而是管理RS,方便滚动更新/部署,回滚,扩缩容。滚动更新时,实际上是创建一个新的RS来间接控制新的pod的创建。

实现零停机升级的手段包括蓝绿部署,滚动部署;

早期的滚动部署可以通过kubectl来直接执行

Kubectl rolling-update xx-pod ….

但是这种由客户端发起的包含多条命令的流程有明显的缺点,及一旦中间client和master之间的网络出现问题,集群相关的对象可能会陷入一个中间状态;所以更理想的方式是‘声明’一个状态,交给k8s集群,让集群自己去完成工作。

声明式/命令式

声明式,告诉系统,系统会自主去实现;隐藏了底层的复杂逻辑。

例子
apiVersion: apps/v1
kind: Deployment
metadata:
  name: nginx-deployment
  labels:
    app: nginx
spec:
  replicas: 3
  selector:
    matchLabels:
      app: nginx
  template:
    metadata:
      labels:
        app: nginx
    spec:
      containers:
      - name: nginx
        image: nginx:1.14.2
        ports:
        - containerPort: 80

HPA:horizontal pod autoscaling

支持按照cpu,内存等使用率来自动扩缩容。底层通过RS间接控制Pod的数量

StatefulSet:

与Deployment和RS不同;它是针对有状态服务的pod管理。譬如一个pod要挂PVC则需要使用StatefulSet;支持按照顺序的扩缩容(pod按照0,1,2,3…的顺序扩容,相反顺序缩容);Pod重新调度后网络标志不变(主机域名不会变换,ip会变)。

STS中的pod的名称为 “container名称+序号”;例如:xx-0, xx-1, xx-3

STS中的每个pod都有自己的域名,可通过DNS解析,不需要直接通过IP地址调用;地址格式为’pod_name.headless_svc_name’;pod飘移时IP会变,但是域名不会变;

STS必须配合无头服务来使用;直接访问无头服务(dig),可以拿到所有pod的IP地址;

典型的例子,ES的集群就需要用Sts进行管理。

DaemonSet:

在node上运行一个守护pod。比如每个node上都要收集日志,就可以通过这个pod来执行。

Job/Cron Job

批处理/定时任务

 

此条目发表在云原生分类目录。将固定链接加入收藏夹。

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