滑窗迭代算法图解(一文读懂SuperEdge拓扑算法)
作者杜杨浩,腾讯云高级工程师,热衷于开源、容器和kubernetes。目前主要从事镜像仓库、Kubernetes集群高可用&备份还原,以及边缘计算相关研发工作。
前言SuperEdge 介绍SuperEdge 是基于原生 Kubernetes 的边缘容器管理系统。该系统把云原生能力扩展到边缘侧,很好地实现了云端对边缘端的管理和控制。同时 superedge 自研了 service group 实现了基于边缘计算的服务访问控制,极大简化了应用从云端部署到边缘端的过程。
SuperEdge service group拓扑感知特性
SuperEdge service group 利用 application-grid-wrapper 实现拓扑感知,完成了同一个任务 nodeunit 内服务的闭环访问。
在深入分析 application-grid-wrapper 之前,这里先简单介绍一下社区 Kubernetes 原生支持的拓扑感知特性[1]
Kubernetes service topology awareness 特性于v1.17发布 alpha 版本,用于实现路由拓扑以及就近访问的特性。用户需要在service 中添加 topologyKeys 字段标示拓扑key类型,只有具有相同拓扑域的 endpoint 会被访问到,目前有三种情况 topologyKeys 可供选择:
- "kubernetes.io/hostname":访问本节点内(kubernetes.io/hostname label value相同)的endpoint,如果没有则service访问失败
- "topology.kubernetes.io/zone":访问相同zone域内(topology.kubernetes.io/zone label value相同)的endpoint,如果没有则service访问失败
- "topology.kubernetes.io/region":访问相同region域内(topology.kubernetes.io/region label value 相同)的 endpoint,如果没有则 service 访问失败
除了单独填写如上某一个拓扑key之外,还可以将这些key构造成列表进行填写,例如:["kubernetes.io/hostname", "topology.kubernetes.io/zone", "topology.kubernetes.io/region"],这表示:优先访问本节点内地 endpoint;如果不存在,则访问同一个 zone 内的 endpoint;如果再不存在,则会访问同一个 region 内地 endpoint,如果都不存在则访问失败。
另外,还可以在列表最后(只能最后一项)添加"*"表示:如果前面拓扑域都失败,则访问任何有效的 endpoint,也即没有限制拓扑了,示例如下:
# A Service that prefers node local, zonal, then regional endpoints but falls back to cluster wide endpoints.
apiVersion: v1
kind: Service
metadata:
name: my-service
spec:
selector:
app: my-app
ports:
- protocol: TCP
port: 80
targetPort: 9376
topologyKeys:
- "kubernetes.io/hostname"
- "topology.kubernetes.io/zone"
- "topology.kubernetes.io/region"
- "*"
而service group 实现的拓扑感知和社区对比,有如下区别:
- service group 拓扑 key 可以自定义,也可以为 gridUniqKey,使用起来更加灵活;而社区实现目前只有三种选择:"kubernetes.io/hostname","topology.kubernetes.io/zone"以及"topology.kubernetes.io/region"。
- service group 只能填写一个拓扑 key,也即只能访问本拓扑域内有效的 endpoint,无法访问其它拓扑域的 endpoint;而社区可以通过 topologyKey 列表以及"*"实现其它备选拓扑域 endpoint 的访问。
service group 实现的拓扑感知,service 配置如下:
# A Service that only prefers node zone1al endpoints.
apiVersion: v1
kind: Service
metadata:
annotations:
topologyKeys: '["zone1"]'
labels:
superedge.io/grid-selector: servicegrid-demo
name: servicegrid-demo-svc
spec:
ports:
- port: 80
protocol: TCP
targetPort: 8080
selector:
appGrid: echo
在介绍完 service group 实现的拓扑感知后,我们深入到源码分析实现细节。同样的,这里以一个使用示例开始分析:
# step1: labels edge nodes
$ kubectl get nodes
NAME STATUS ROLES AGE VERSIO
Nnode0 Ready <none> 16d v1.16.7
node1 Ready <none> 16d v1.16.7
node2 Ready <none> 16d v1.16.7
# nodeunit1(nodegroup and servicegroup zone1)
$ kubectl --kubeconfig config label nodes node0 zone1=nodeunit1
# nodeunit2(nodegroup and servicegroup zone1)
$ kubectl --kubeconfig config label nodes node1 zone1=nodeunit2
$ kubectl --kubeconfig config label nodes node2 zone1=nodeunit2
...
# step3: deploy echo ServiceGrid
$ cat <<EOF | kubectl --kubeconfig config apply -f -
apiVersion: superedge.io/v1
kind: ServiceGrid
metadata:
name: servicegrid-demo
namespace: default
spec:
gridUniqKey: zone1
template:
selector:
appGrid: echo
ports:
- protocol: TCP
port: 80
targetPort: 8080
EOF
servicegrid.superedge.io/servicegrid-demo created
# note that there is only one relevant service generated
$ kubectl get svc
NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE
kubernetes ClusterIP 192.168.0.1 <none> 443/TCP 16d
servicegrid-demo-svc ClusterIP 192.168.6.139 <none> 80/TCP 10m
# step4: access servicegrid-demo-svc(service topology and closed-looped)
# execute on node0
$ curl 192.168.6.139|grep "node name" node name: node0
# execute on node1 and node2
$ curl 192.168.6.139|grep "node name"
node name: node2
$ curl 192.168.6.139|grep "node name"
node name: node1
在创建完 ServiceGrid CR 后,ServiceGrid Controller 负责根据 ServiceGrid产生对应的 service (包含由 serviceGrid.Spec.GridUniqKey 构成的 topologyKeys annotations);而 application-grid-wrapper 根据 service 实现拓扑感知,下面依次分析。
ServiceGrid Controller 分析ServiceGrid Controller 逻辑和 DeploymentGrid Controller 整体一致,如下:
- 1、创建并维护 service group 需要的若干 CRDs(包括:ServiceGrid)
- 2、监听 ServiceGrid event,并填充 ServiceGrid 到工作队列中;循环从队列中取出 ServiceGrid 进行解析,创建并且维护对应的系统 service
- 3、监听 service event,并将相关的 ServiceGrid 塞到工作队列中进行上述处理,协助上述逻辑达到整体 reconcile 逻辑
注意这里区别于 DeploymentGrid Controller:
- 一个 ServiceGrid 对象只产生一个 service
- 只需额外监听 service event,无需监听 node 事件。因为 node 的CRUD与 ServiceGrid 无关
- ServiceGrid 对应产生的 service,命名为:{ServiceGrid}-svc
func (sgc *ServiceGridController) syncServiceGrid(key string) error {
startTime := time.Now()
klog.V(4).Infof("Started syncing service grid %q (%v)", key, startTime)
defer func() {
klog.V(4).Infof("Finished syncing service grid %q (%v)", key, time.Since(startTime))
}()
namespace, name, err := cache.SplitMetaNamespaceKey(key)
if err != nil {
return err
}
sg, err := sgc.svcGridLister.ServiceGrids(namespace).Get(name)
if errors.IsNotFound(err) {
klog.V(2).Infof("service grid %v has been deleted", key)
return nil
}
if err != nil {
return err
}
if sg.Spec.GridUniqKey == "" {
sgc.eventRecorder.Eventf(sg, corev1.EventTypeWarning, "Empty", "This service grid has an empty grid key")
return nil
}
// get service workload list of this grid
svcList, err := sgc.getServiceForGrid(sg)
if err != nil {
return err
}
if sg.DeletionTimestamp != nil {
return nil
}
// sync service grid relevant services workload
return sgc.reconcile(sg, svcList)
}
func (sgc *ServiceGridController) getServiceForGrid(sg *crdv1.ServiceGrid) ([]*corev1.Service, error) {
svcList, err := sgc.svcLister.Services(sg.Namespace).List(labels.Everything())
if err != nil {
return nil, err
}
labelSelector, err := common.GetDefaultSelector(sg.Name)
if err != nil {
return nil, err
}
canAdoptFunc := controller.RecheckDeletionTimestamp(func() (metav1.Object, error)
{
fresh, err :=
sgc.crdClient.SuperedgeV1().ServiceGrids(sg.Namespace).Get(context.TODO(), sg.Name, metav1.GetOptions{})
if err != nil {
return nil, err
}
if fresh.UID != sg.UID {
return nil, fmt.Errorf("orignal service grid %v/%v is gone: got uid %v, wanted %v", sg.Namespace,
sg.Name, fresh.UID, sg.UID)
}
return fresh, nil
})
cm := controller.NewServiceControllerRefManager(sgc.svcClient, sg, labelSelector, util.ControllerKind, canAdoptFunc)
return cm.ClaimService(svcList)
}
func (sgc *ServiceGridController) reconcile(g *crdv1.ServiceGrid, svcList
[]*corev1.Service) error {
var (
adds []*corev1.Service
updates []*corev1.Service
deletes []*corev1.Service
)
sgTargetSvcName := util.GetServiceName(g)
isExistingSvc := false
for _, svc := range svcList {
if svc.Name == sgTargetSvcName {
isExistingSvc = true
template := util.KeepConsistence(g, svc)
if !apiequality.Semantic.DeepEqual(template, svc) {
updates = append(updates, template)
}
} else {
deletes = append(deletes, svc)
}
}
if !isExistingSvc {
adds = append(adds, util.CreateService(g))
}
return sgc.syncService(adds, updates, deletes)
}
func CreateService(sg *crdv1.ServiceGrid) *corev1.Service {
svc := &corev1.Service{
ObjectMeta: metav1.ObjectMeta{
Name: GetServiceName(sg),
Namespace: sg.Namespace,
// Append existed ServiceGrid labels to service to be created
Labels: func() map[string]string {
if sg.Labels != nil {
newLabels := sg.Labels
newLabels[common.GridSelectorName] = sg.Name
newLabels[common.GridSelectorUniqKeyName] = sg.Spec.GridUniqKey
return newLabels
} else {
return map[string]string{
common.GridSelectorName: sg.Name,
common.GridSelectorUniqKeyName: sg.Spec.GridUniqKey,
}
}
}(),
Annotations: make(map[string]string),
},
Spec: sg.Spec.Template,
}
keys := make([]string, 1)
keys[0] = sg.Spec.GridUniqKey
keyData, _ := json.Marshal(keys)
svc.Annotations[common.TopologyAnnotationsKey] = string(keyData)
return svc
}
由于逻辑与 DeploymentGrid 类似,这里不展开细节,重点关注 application-grid-wrapper 部分。
application-grid-wrapper 分析在 ServiceGrid Controller 创建完 service 之后,application-grid-wrapper 的作用就开始启动了:
apiVersion: v1
kind: Service
metadata:
annotations:
topologyKeys: '["zone1"]'
creationTimestamp: "2021-03-03T07:33:30Z"
labels:
superedge.io/grid-selector: servicegrid-demo
name: servicegrid-demo-svc
namespace: default
ownerReferences:
- apiVersion: superedge.io/v1
blockOwnerDeletion: true
controller: true
kind: ServiceGrid
name: servicegrid-demo
uid: 78c74d3c-72ac-4e68-8c79-f1396af5a581
resourceVersion: "127987090"
selfLink: /api/v1/namespaces/default/services/servicegrid-demo-svc
uid: 8130ba7b-c27e-4c3a-8ceb-4f6dd0178dfc
spec:
clusterIP: 192.168.161.1
ports:
- port: 80
protocol: TCP
targetPort: 8080
selector:
appGrid: echo
sessionAffinity: None
type: ClusterIP
status:
loadBalancer: {}
为了实现 Kubernetes 零侵入,需要在 kube-proxy 与 apiserver 通信之间添加一层 wrapper,架构如下:
调用链路如下:
kube-proxy -> application-grid-wrapper -> lite-apiserver -> kube-apiserver
因此 application-grid-wrapper 会起服务,接受来自 kube-proxy 的请求,如下:
func (s *interceptorServer) Run(debug bool, bindAddress string, insecure bool, caFile, certFile, keyFile string) error {
...
klog.Infof("Start to run interceptor server")
/* filter
*/
server := &http.Server{Addr: bindAddress, Handler: s.buildFilterChains(debug)}
if insecure {
return server.ListenAndServe()
}
...
server.TLSConfig = tlsConfig
return server.ListenAndServeTLS("", "")
}
func (s *interceptorServer) buildFilterChains(debug bool) http.Handler {
handler := http.Handler(http.NewServeMux())
handler = s.interceptEndpointsRequest(handler)
handler = s.interceptServiceRequest(handler)
handler = s.interceptEventRequest(handler)
handler = s.interceptNodeRequest(handler)
handler = s.logger(handler)
if debug {
handler = s.debugger(handler)
}
return handler
}
这里会首先创建 interceptorServer,然后注册处理函数,由外到内依次如下:
- debug:接受 debug 请求,返回 wrapper pprof 运行信息
- logger:打印请求日志
- node:接受 kube-proxy node GET(/api/v1/nodes/{node})请求,并返回 node信息
- event:接受 kube-proxy events POST(/events)请求,并将请求转发给 lite-apiserver
func (s *interceptorServer) interceptEventRequest(handler http.Handler) http.Handler {
return http.HandlerFunc(func(w http.ResponseWriter, r *http.Request) { if r.Method != http.MethodPost || !strings.HasSuffix(r.URL.Path, "/events") {
handler.ServeHTTP(w, r)
return
}
targetURL, _ := url.Parse(s.restConfig.Host)
reverseProxy := httputil.NewSingleHostReverseProxy(targetURL)
reverseProxy.Transport, _ = rest.TransportFor(s.restConfig)
reverseProxy.ServeHTTP(w, r)
})
}
- service:接受 kube-proxy service List&Watch(/api/v1/services)请求,并根据 storageCache 内容返回(GetServices)
- endpoint:接受 kube-proxy endpoint List&Watch (/api/v1/endpoints)请求,并根据 storageCache 内容返回(GetEndpoints)
下面先重点分析 cache 部分的逻辑,然后再回过头来分析具体的 http handler List&Watch 处理逻辑。
wrapper 为了实现拓扑感知,自己维护了一个 cache,包括:node,service,endpoint。可以看到在 setupInformers 中注册了这三类资源的处理函数:
type storageCache struct {
// hostName is the nodeName of node which application-grid-wrapper deploys on
hostName string
wrapperInCluster bool
// mu lock protect the following map structure
mu sync.RWMutex
servicesMap map[types.NamespacedName]*serviceContainer
endpointsMap map[types.NamespacedName]*endpointsContainer
nodesMap map[types.NamespacedName]*nodeContainer
// service watch channel
serviceChan chan<- watch.Event
// endpoints watch channel
endpointsChan chan<- watch.Event
}
...
func NewStorageCache(hostName string, wrapperInCluster bool, serviceNotifier, endpointsNotifier chan watch.Event) *storageCache {
msc := &storageCache{
hostName: hostName,
wrapperInCluster: wrapperInCluster,
servicesMap: make(map[types.NamespacedName]*serviceContainer),
endpointsMap: make(map[types.NamespacedName]*endpointsContainer),
nodesMap: make(map[types.NamespacedName]*nodeContainer),
serviceChan: serviceNotifier,
endpointsChan: endpointsNotifier,
}
return msc
}
...
func (s *interceptorServer) Run(debug bool, bindAddress string, insecure bool, caFile, certFile, keyFile string) error {
...
if err := s.setupInformers(ctx.Done()); err != nil {
return err
}
klog.Infof("Start to run interceptor server")
/* filter
*/
server := &http.Server{Addr: bindAddress, Handler: s.buildFilterChains(debug)}
...
return server.ListenAndServeTLS("", "")
}
func (s *interceptorServer) setupInformers(stop <-chan struct{}) error {
klog.Infof("Start to run service and endpoints informers")
noProxyName, err := labels.NewRequirement(apis.LabelServiceProxyName, selection.DoesNotExist, nil)
if err != nil {
klog.Errorf("can't parse proxy label, %v", err)
return err
}
noHeadlessEndpoints, err := labels.NewRequirement(v1.IsHeadlessService, selection.DoesNotExist, nil)
if err != nil {
klog.Errorf("can't parse headless label, %v", err)
return err
}
labelSelector := labels.NewSelector()
labelSelector = labelSelector.Add(*noProxyName, *noHeadlessEndpoints)
resyncPeriod := time.Minute * 5
client := kubernetes.NewForConfigOrDie(s.restConfig)
nodeInformerFactory := informers.NewSharedInformerFactory(client, resyncPeriod)
informerFactory := informers.NewSharedInformerFactoryWithOptions(client, resyncPeriod,
informers.WithTweakListOptions(func(options *metav1.ListOptions) {
options.LabelSelector = labelSelector.String()
}))
nodeInformer := nodeInformerFactory.Core().V1().Nodes().Informer()
serviceInformer := informerFactory.Core().V1().Services().Informer()
endpointsInformer := informerFactory.Core().V1().Endpoints().Informer()
/*
*/
nodeInformer.AddEventHandlerWithResyncPeriod(s.cache.NodeEventHandler(), resyncPeriod)
serviceInformer.AddEventHandlerWithResyncPeriod(s.cache.ServiceEventHandler(), resyncPeriod)
endpointsInformer.AddEventHandlerWithResyncPeriod(s.cache.EndpointsEventHandler(), resyncPeriod)
go nodeInformer.Run(stop)
go serviceInformer.Run(stop)
go endpointsInformer.Run(stop)
if !cache.WaitForNamedCacheSync("node", stop,
nodeInformer.HasSynced,
serviceInformer.HasSynced,
endpointsInformer.HasSynced) {
return fmt.Errorf("can't sync informers")
}
return nil
}
func (sc *storageCache) NodeEventHandler() cache.ResourceEventHandler {
return &nodeHandler{cache: sc}
}
func (sc *storageCache) ServiceEventHandler() cache.ResourceEventHandler {
return &serviceHandler{cache: sc}
}
func (sc *storageCache) EndpointsEventHandler() cache.ResourceEventHandler {
return &endpointsHandler{cache: sc}
}
这里依次分析 NodeEventHandler,ServiceEventHandler 以及 EndpointsEventHandler,如下:
1、NodeEventHandler
NodeEventHandler 负责监听 node 资源相关 event,并将 node 以及 node Labels 添加到 storageCache.nodesMap 中(key为nodeName,value为node以及node labels)。
func (nh *nodeHandler) add(node *v1.Node) {
sc := nh.cache
sc.mu.Lock()
nodeKey := types.NamespacedName{Namespace: node.Namespace, Name: node.Name}
klog.Infof("Adding node %v", nodeKey)
sc.nodesMap[nodeKey] = &nodeContainer{
node: node,
labels: node.Labels,
}
// update endpoints
changedEps := sc.rebuildEndpointsMap()
sc.mu.Unlock()
for _, eps := range changedEps {
sc.endpointsChan <- eps
}
}
func (nh *nodeHandler) update(node *v1.Node) {
sc := nh.cache
sc.mu.Lock()
nodeKey := types.NamespacedName{Namespace: node.Namespace, Name: node.Name}
klog.Infof("Updating node %v", nodeKey)
nodeContainer, found := sc.nodesMap[nodeKey]
if !found {
sc.mu.Unlock()
klog.Errorf("Updating non-existed node %v", nodeKey)
return
}
nodeContainer.node = node
// return directly when labels of node stay unchanged
if reflect.DeepEqual(node.Labels, nodeContainer.labels) {
sc.mu.Unlock()
return
}
nodeContainer.labels = node.Labels
// update endpoints
changedEps := sc.rebuildEndpointsMap()
sc.mu.Unlock()
for _, eps := range changedEps {
sc.endpointsChan <- eps
}
}
...
同时由于 node 的改变会影响 endpoint,因此会调用 rebuildEndpointsMap 刷新 storageCache.endpointsMap。
// rebuildEndpointsMap updates all endpoints stored in storageCache.endpointsMap dynamically and constructs relevant modified events
func (sc *storageCache) rebuildEndpointsMap() []watch.Event {
evts := make([]watch.Event, 0)
for name, endpointsContainer := range sc.endpointsMap {
newEps := pruneEndpoints(sc.hostName, sc.nodesMap, sc.servicesMap, endpointsContainer.endpoints, sc.wrapperInCluster)
if apiequality.Semantic.DeepEqual(newEps, endpointsContainer.modified) {
continue
}
sc.endpointsMap[name].modified = newEps
evts = append(evts, watch.Event{
Type: watch.Modified,
Object: newEps,
})
}
return evts
}
rebuildEndpointsMap 是 cache 的核心函数,同时也是拓扑感知的算法实现:
// pruneEndpoints filters endpoints using serviceTopology rules combined by services topologyKeys and node labels
func pruneEndpoints(hostName string,
nodes map[types.NamespacedName]*nodeContainer,
services map[types.NamespacedName]*serviceContainer,
eps *v1.Endpoints, wrapperInCluster bool) *v1.Endpoints {
epsKey := types.NamespacedName{Namespace: eps.Namespace, Name: eps.Name}
if wrapperInCluster {
eps = genLocalEndpoints(eps)
}
// dangling endpoints
svc, ok := services[epsKey]
if !ok {
klog.V(4).Infof("Dangling endpoints %s, % #v", eps.Name, eps.Subsets)
return eps
}
// normal service
if len(svc.keys) == 0 {
klog.V(4).Infof("Normal endpoints %s, % #v", eps.Name, eps.Subsets)
return eps
}
// topology endpoints
newEps := eps.DeepCopy()
for si := range newEps.Subsets {
subnet := &newEps.Subsets[si]
subnet.Addresses = filterConcernedAddresses(svc.keys, hostName, nodes, subnet.Addresses)
subnet.NotReadyAddresses = filterConcernedAddresses(svc.keys, hostName, nodes, subnet.NotReadyAddresses)
}
klog.V(4).Infof("Topology endpoints %s: subnets from % #v to % #v", eps.Name, eps.Subsets, newEps.Subsets)
return newEps
}
// filterConcernedAddresses aims to filter out endpoints addresses within the same node unit
func filterConcernedAddresses(topologyKeys []string, hostName string, nodes
map[types.NamespacedName]*nodeContainer,
addresses []v1.EndpointAddress) []v1.EndpointAddress {
hostNode, found := nodes[types.NamespacedName{Name: hostName}]
if !found {
return nil
}
filteredEndpointAddresses := make([]v1.EndpointAddress, 0)
for i := range addresses {
addr := addresses[i]
if nodeName := addr.NodeName; nodeName != nil {
epsNode, found := nodes[types.NamespacedName{Name: *nodeName}]
if !found {
continue
}
if hasIntersectionLabel(topologyKeys, hostNode.labels, epsNode.labels) {
filteredEndpointAddresses = append(filteredEndpointAddresses, addr)
}
}
}
return filteredEndpointAddresses
}
func hasIntersectionLabel(keys []string, n1, n2 map[string]string) bool {
if n1 == nil || n2 == nil {
return false
}
for _, key := range keys {
val1, v1found := n1[key]
val2, v2found := n2[key]
if v1found && v2found && val1 == val2 {
return true
}
}
return false
}
算法逻辑如下:
- 判断 endpoint 是否为 default kubernetes service,如果是,则将该 endpoint 转化为 wrapper 所在边缘节点的 lite-apiserver 地址(127.0.0.1)和端口(51003)。
apiVersion: v1
kind: Endpoints
metadata:
annotations:
superedge.io/local-endpoint: 127.0.0.1
superedge.io/local-port: "51003"
name: kubernetes
namespace: default
subsets:
- addresses:
- ip: 172.31.0.60
ports:
- name: https
port: xxx
protocol: TCP
func genLocalEndpoints(eps *v1.Endpoints) *v1.Endpoints {
if eps.Namespace != metav1.NamespaceDefault || eps.Name != MasterEndpointName {
return eps
}
klog.V(4).Infof("begin to gen local ep %v", eps)
ipAddress, e := eps.Annotations[EdgeLocalEndpoint]
if !e {
return eps
}
portStr, e := eps.Annotations[EdgeLocalPort]
if !e {
return eps
}
klog.V(4).Infof("get local endpoint %s:%s", ipAddress, portStr)
port, err := strconv.ParseInt(portStr, 10, 32)
if err != nil {
klog.Errorf("parse int %s err %v", portStr, err)
return eps
}
ip := net.ParseIP(ipAddress)
if ip == nil {
klog.Warningf("parse ip %s nil", ipAddress)
return eps
}
nep := eps.DeepCopy()
nep.Subsets = []v1.EndpointSubset{
{
Addresses: []v1.EndpointAddress{
{
IP: ipAddress,
},
},
Ports: []v1.EndpointPort{
{
Protocol: v1.ProtocolTCP,
Port: int32(port),
Name: "https",
},
},
},
}
klog.V(4).Infof("gen new endpoint complete %v", nep)
return nep
}
这样做的目的是使边缘节点上的服务采用集群内 (InCluster) 方式访问的 apiserver 为本地的 lite-apiserver,而不是云端的 apiserver。
- 从 storageCache.servicesMap cache 中根据 endpoint 名称(namespace/name) 取出对应 service,如果该 service 没有 topologyKeys 则无需做拓扑转化(非 service group)。
func getTopologyKeys(objectMeta *metav1.ObjectMeta) []string {
if !hasTopologyKey(objectMeta) {
return nil
}
var keys []string
keyData := objectMeta.Annotations[TopologyAnnotationsKey]
if err := json.Unmarshal([]byte(keyData), &keys); err != nil {
klog.Errorf("can't parse topology keys %s, %v", keyData, err)
return nil
}
return keys
}
- 调用 filterConcernedAddresses 过滤 endpoint.Subsets Addresses 以及 NotReadyAddresses,只保留同一个 service topologyKeys 中的 endpoint。
// filterConcernedAddresses aims to filter out endpoints addresses within the same node unit
func filterConcernedAddresses(topologyKeys []string, hostName string, nodes
map[types.NamespacedName]*nodeContainer,
addresses []v1.EndpointAddress) []v1.EndpointAddress {
hostNode, found := nodes[types.NamespacedName{Name: hostName}]
if !found {
return nil
}
filteredEndpointAddresses := make([]v1.EndpointAddress, 0)
for i := range addresses {
addr := addresses[i]
if nodeName := addr.NodeName; nodeName != nil {
epsNode, found := nodes[types.NamespacedName{Name: *nodeName}]
if !found {
continue
}
if hasIntersectionLabel(topologyKeys, hostNode.labels, epsNode.labels) {
filteredEndpointAddresses = append(filteredEndpointAddresses, addr)
}
}
}
return filteredEndpointAddresses
}
func hasIntersectionLabel(keys []string, n1, n2 map[string]string) bool {
if n1 == nil || n2 == nil {
return false
}
for _, key := range keys {
val1, v1found := n1[key]
val2, v2found := n2[key]
if v1found && v2found && val1 == val2 {
return true
}
}
return false
}
注意:如果 wrapper 所在边缘节点没有 service topologyKeys 标签,则也无法访问该 service。
回到 rebuildEndpointsMap,在调用 pruneEndpoints 刷新了同一个拓扑域内的 endpoint 后,会将修改后的 endpoints 赋值给 storageCache .endpointsMap [endpoint]. modified (该字段记录了拓扑感知后修改的endpoints)。
func (nh *nodeHandler) add(node *v1.Node) {
sc := nh.cache
sc.mu.Lock()
nodeKey := types.NamespacedName{Namespace: node.Namespace, Name: node.Name}
klog.Infof("Adding node %v", nodeKey)
sc.nodesMap[nodeKey] = &nodeContainer{
node: node,
labels: node.Labels,
}
// update endpoints
changedEps := sc.rebuildEndpointsMap()
sc.mu.Unlock()
for _, eps := range changedEps {
sc.endpointsChan <- eps
}
}
// rebuildEndpointsMap updates all endpoints stored in storageCache.endpointsMap dynamically and constructs relevant modified events
func (sc *storageCache) rebuildEndpointsMap() []watch.Event {
evts := make([]watch.Event, 0)
for name, endpointsContainer := range sc.endpointsMap {
newEps := pruneEndpoints(sc.hostName, sc.nodesMap, sc.servicesMap, endpointsContainer.endpoints, sc.wrapperInCluster)
if apiequality.Semantic.DeepEqual(newEps, endpointsContainer.modified) {
continue
}
sc.endpointsMap[name].modified = newEps
evts = append(evts, watch.Event{
Type: watch.Modified,
Object: newEps,
})
}
return evts
}
另外,如果 endpoints (拓扑感知后修改的 endpoints)发生改变,会构建 watch event,传递给 endpoints handler (interceptEndpointsRequest)处理。
2、ServiceEventHandler
storageCache.servicesMap 结构体 key 为 service 名称(namespace/name),value 为 serviceContainer,包含如下数据:
- svc:service对象
- keys:service topologyKeys
对于 service 资源的改动,这里用 Update event 说明:
func (sh *serviceHandler) update(service *v1.Service) {
sc := sh.cache
sc.mu.Lock()
serviceKey := types.NamespacedName{Namespace: service.Namespace, Name: service.Name}
klog.Infof("Updating service %v", serviceKey)
newTopologyKeys := getTopologyKeys(&service.ObjectMeta)
serviceContainer, found := sc.servicesMap[serviceKey]
if !found {
sc.mu.Unlock()
klog.Errorf("update non-existed service, %v", serviceKey)
return
}
sc.serviceChan <- watch.Event{
Type: watch.Modified,
Object: service,
}
serviceContainer.svc = service
// return directly when topologyKeys of service stay unchanged
if reflect.DeepEqual(serviceContainer.keys, newTopologyKeys) {
sc.mu.Unlock()
return
}
serviceContainer.keys = newTopologyKeys
// update endpoints
changedEps := sc.rebuildEndpointsMap()
sc.mu.Unlock()
for _, eps := range changedEps {
sc.endpointsChan <- eps
}
}
逻辑如下:
- 获取 service topologyKeys
- 构建 service event.Modified event
- 比较 service topologyKeys 与已经存在的是否有差异
- 如果有差异则更新 topologyKeys,且调用 rebuildEndpointsMap 刷新该 service 对应的endpoints,如果 endpoints 发生变化,则构建 endpoints watch event,传递给 endpoints handler (interceptEndpointsRequest)处理。
3、EndpointsEventHandler
storageCache.endpointsMap 结构体 key 为 endpoints 名称(namespace/name),value 为 endpointsContainer,包含如下数据:
- endpoints:拓扑修改前的 endpoints
- modified:拓扑修改后的 endpoints
对于 endpoints 资源的改动,这里用 Update event 说明:
func (eh *endpointsHandler) update(endpoints *v1.Endpoints) {
sc := eh.cache
sc.mu.Lock()
endpointsKey := types.NamespacedName{Namespace: endpoints.Namespace, Name: endpoints.Name}
klog.Infof("Updating endpoints %v", endpointsKey)
endpointsContainer, found := sc.endpointsMap[endpointsKey]
if !found {
sc.mu.Unlock()
klog.Errorf("Updating non-existed endpoints %v", endpointsKey)
return
}
endpointsContainer.endpoints = endpoints
newEps := pruneEndpoints(sc.hostName, sc.nodesMap, sc.servicesMap, endpoints, sc.wrapperInCluster)
changed := !apiequality.Semantic.DeepEqual(endpointsContainer.modified, newEps)
if changed {
endpointsContainer.modified = newEps
}
sc.mu.Unlock()
if changed {
sc.endpointsChan <- watch.Event{
Type: watch.Modified,
Object: newEps,
}
}
}
逻辑如下:
- 更新 endpointsContainer.endpoint 为新的 endpoints 对象
- 调用 pruneEndpoints 获取拓扑刷新后的 endpoints
- 比较 endpointsContainer.modified 与新刷新后的 endpoints
- 如果有差异则更新 endpointsContainer.modified,则构建 endpoints watch event,传递给 endpoints handler (interceptEndpointsRequest)处理。
在分析完 NodeEventHandler,ServiceEventHandler 以及 EndpointsEventHandler 之后,我们回到具体的 http handler List&Watch 处理逻辑上,这里以 endpoints 为例:
func (s *interceptorServer) interceptEndpointsRequest(handler http.Handler) http.Handler {
return http.HandlerFunc(func(w http.ResponseWriter, r *http.Request) {
if r.Method != http.MethodGet ||
!strings.HasPrefix(r.URL.Path, "/api/v1/endpoints") {
handler.ServeHTTP(w, r)
return
}
queries := r.URL.Query()
acceptType := r.Header.Get("Accept")
info, found := s.parseAccept(acceptType, s.mediaSerializer)
if !found {
klog.Errorf("can't find %s serializer", acceptType)
w.WriteHeader(http.StatusBadRequest)
return
}
encoder :=
scheme.Codecs.EncoderForVersion(info.Serializer, v1.SchemeGroupVersion)
// list request
if queries.Get("watch") == "" {
w.Header().Set("Content-Type", info.MediaType)
allEndpoints := s.cache.GetEndpoints()
epsItems := make([]v1.Endpoints, 0, len(allEndpoints))
for _, eps := range allEndpoints {
epsItems = append(epsItems, *eps)
}
epsList := &v1.EndpointsList{
Items: epsItems,
}
err := encoder.Encode(epsList, w)
if err != nil {
klog.Errorf("can't marshal endpoints list, %v", err)
w.WriteHeader(http.StatusInternalServerError)
return
}
return
}
// watch request
timeoutSecondsStr := r.URL.Query().Get("timeoutSeconds")
timeout := time.Minute
if timeoutSecondsStr != "" {
timeout, _ = time.ParseDuration(fmt.Sprintf("%ss", timeoutSecondsStr))
}
timer := time.NewTimer(timeout)
defer timer.Stop()
flusher, ok := w.(http.Flusher)
if !ok {
klog.Errorf("unable to start watch - can't get http.Flusher: %#v", w)
w.WriteHeader(http.StatusMethodNotAllowed)
return
}
e := restclientwatch.NewEncoder(
streaming.NewEncoder(info.StreamSerializer.Framer.NewFrameWriter(w),
scheme.Codecs.EncoderForVersion(info.StreamSerializer, v1.SchemeGroupVersion)),
encoder)
if info.MediaType == runtime.ContentTypeProtobuf {
w.Header().Set("Content-Type",
runtime.ContentTypeProtobuf ";stream=watch")
} else {
w.Header().Set("Content-Type", runtime.ContentTypeJSON)
}
w.Header().Set("Transfer-Encoding", "chunked")
w.WriteHeader(http.StatusOK)
flusher.Flush()
for {
select {
case <-r.Context().Done():
return
case <-timer.C:
return
case evt := <-s.endpointsWatchCh:
klog.V(4).Infof("Send endpoint watch event: % #v", evt)
err := e.Encode(&evt)
if err != nil {
klog.Errorf("can't encode watch event, %v", err)
return
}
if len(s.endpointsWatchCh) == 0 {
flusher.Flush()
}
}
}
})
}
逻辑如下:
- 如果为 List请求,则调用 GetEndpoints 获取拓扑修改后的 endpoints 列表,并返回
func (sc *storageCache) GetEndpoints() []*v1.Endpoints {
sc.mu.RLock()
defer sc.mu.RUnlock()
epList := make([]*v1.Endpoints, 0,
len(sc.endpointsMap))
for _, v := range sc.endpointsMap {
epList = append(epList, v.modified)
}
return epList
}
- 如果为 Watch 请求,则不断从 storageCache.endpointsWatchCh 管道中接受 watch event,并返回 interceptServiceRequest 逻辑与 interceptEndpointsRequest 一致,这里不再赘述 。
- SuperEdge service group 利用 application-grid-wrapper 实现拓扑感知,完成了同一个 nodeunit 内服务的闭环访问
- service group 实现的拓扑感知和 Kubernetes 社区原生实现对比,有如下区别:
- service group 拓扑 key 可以自定义,也即为 gridUniqKey,使用起来更加灵活;而社区实现目前只有三种选择:"kubernetes.io/hostname","topology.kubernetes.io/zone"以及"topology.kubernetes.io/region"
- service group 只能填写一个拓扑 key,也即只能访问本拓扑域内有效的 endpoint,无法访问其它拓扑域的 endpoint;而社区可以通过 topologyKey 列表以及"*"实现其它备选拓扑域 endpoint的访问
- ServiceGrid Controller 负责根据 ServiceGrid 产生对应的 service(包含由serviceGrid.Spec.GridUniqKey 构成的 topologyKeys annotations),逻辑和 DeploymentGrid Controller 整体一致,如下:
- 创建并维护 service group 需要的若干CRDs(包括:ServiceGrid)
- 监听 ServiceGrid event,并填充 ServiceGrid到工作队列中;循环从队列中取出 ServiceGrid 进行解析,创建并且维护对应的 service
- 监听 service event,并将相关的 ServiceGrid 塞到工作队列中进行上述处理,协助上述逻辑达到整体 reconcile 逻辑
- 为了实现 Kubernetes 零侵入,需要在 kube-proxy 与 apiserver 通信之间添加一层 wrapper,调用链路如下:kube-proxy -> application-grid-wrapper -> lite-apiserver -> kube-apiserver
- application-grid-wrapper 是一个 http server,接受来自 kube-proxy 的请求,同时维护一个资源缓存,处理函数由外到内依次如下:
- debug:接受 debug 请求,返回 wrapper pprof 运行信息
- logger:打印请求日志
- node:接受 kube-proxy node GET (/api/v1/nodes/{node}) 请求,并返回 node 信息
- event:接受 kube-proxy events POST (/events) 请求,并将请求转发给 lite-apiserver
- service:接受 kube-proxy service List&Watch (/api/v1/services) 请求,并根据 storageCache 内容返回 (GetServices)
- endpoint:接受 kube-proxy endpoint List&Watch (/api/v1/endpoints) 请求,并根据 storageCache 内容返回(GetEndpoints)
- wrapper 为了实现拓扑感知,维护了一个资源 cache,包括:node,service,endpoint,同时注册了相关 event 处理函数。核心拓扑算法逻辑为:调用 filterConcernedAddresses 过滤 endpoint.Subsets Addresses 以及 NotReadyAddresses,只保留同一个 service topologyKeys 中的 endpoint。另外,如果 wrapper 所在边缘节点没有 service topologyKeys 标签,则也无法访问该service
- wrapper 接受来自 kube-proxy 对 endpoints 以及 service 的 List&Watch 请求,以endpoints 为例:如果为List 请求,则调用 GetEndpoints 获取拓扑修改后的 endpoints 列表,并返回;如果为 Watch 请求,则不断从storageCache.endpointsWatchCh 管道中接受 watch event,并返回。service 逻辑与 endpoints 一致
目前 SuperEdge service group 实现的拓扑算法功能更加灵活方便,如何处理与 Kubernetes 社区 service topology awareness 之间的关系值得探索,建议将 SuperEdge 拓扑算法推到社区。
【参考资料】
[1] 拓扑感知特性:【 https://kubernetes.io/docs/concepts/services-networking/service-topology/】
[2] duyanghao kubernetes-reading-notes: 【https://github.com/duyanghao/kubernetes-reading-notes/blob/master/superedge/service-group/README.md】
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