今天分享的是我们组的一个实习生写的一篇源码解析文章,小伙子实习期间在社区Nacos2.0的基础上对灰度发布的能力进行了增强,并完成了MSE Nacos2.0上从管控到内核的灰度发布能力的研发。以下是他对配置发布流程的代码解析,相信看完之后你会感叹:现在的实习生都有这个水平了吗?
说到灰度发布,就不得不提到阿里的安全生产三板斧:可监控、可灰度、可回滚。在阿里内部,对于安全生产是高度重视的,灰度可以说是发布之前的必备流程。因此,作为阿里的配置中心,Nacos同样支持了配置灰度的功能,可以通过控制台进行配置的灰度推送、回滚,从而实现安全的配置发布。一般来说,我们按照下图所示流程进行配置的安全修改。只有在小规模机器上验证配置按预期生效之后才会正式发布配置,否则就回滚灰度配置。
发布流程
配置灰度发布流程
社区Nacos的灰度是基于IP的方式进行的,用户需要在控制台,选择需要灰度的配置,然后新建灰度配置,选择灰度机器的IP进行配置推送。整个交互流程如下图所示。
IP灰度机制
具体的使用方法,如果使用的是自建的社区Nacos,可以访问http://ip:port/nacos进入控制台,在配置管理的编辑页面进行配置灰度发布,如下图。
社区Nacos控制台
如果使用的是阿里云的MSE微服务引擎,可以查看MSE配置灰度发布帮助文档了解使用方法,目前在Nacos2.0专业版上已经支持灰度功能,在MSE控制台打开Beta按钮即可,如下图所示。
MSE Beta发布
Nacos灰度原理
Nacos的灰度发布原理其实并不复杂,本质就如同下面这张流程图。
灰度原理
乍一看,这个流程好复杂,实际上定睛一看,好像也没啥。整个过程就是Client、Server和Console之间的交互。Client端监听Server上的配置,建立长连接并上报自己的客户端信息,例如IP地址。Console负责进行配置灰度的调用,将用户所需要的灰度配置请求发送到Server端。然后Server端根据用户的灰度配置请求中的IP地址,过滤与客户端的长连接,然后将灰度配置定向推送到对应IP的客户端中即可。下面笔者从长连接的建立到配置灰度,进行详细的源码分析。
长连接建立
在Nacos2.0版本之前,Nacos主要采用长轮询的方式在客户端拉取服务端的配置信息。而在Nacos2.0版本中,引入了基于gRPC的长连接模型来提升配置监听的性能,客户端和服务端会建立长连接来监听配置的变更,一旦服务端有配置变更,就会将配置信息推送到客户端中。在Nacos源码中,这一过程主要涉及到两个组件之间的交互,即com.alibaba.nacos.common.remote.client.grpc包下的GrpcSdkClient类和com.alibaba.nacos.core.remote.grpc包下的GrpcBiStreamRequestAcceptor类。然而,GrpcSdkClient中没有定义具体的连接逻辑,其主要逻辑在其父类GrpcClient中。下面这段代码就是客户端连接服务端的核心代码,位于GrpcClient的connectToServer方法。
@Overridepublic Connection connectToServer(ServerInfo serverInfo) {try {// ......int port = serverInfo.getServerPort() + rpcPortOffset();// 创建一个Grpc的StubRequestGrpc.RequestFutureStub newChannelStubTemp = createNewChannelStub(serverInfo.getServerIp(), port);if (newChannelStubTemp != null) {// 检查服务端是否可用Response response = serverCheck(serverInfo.getServerIp(), port, newChannelStubTemp);if (response == null || !(response instanceof ServerCheckResponse)) {shuntDownChannel((ManagedChannel) newChannelStubTemp.getChannel());return null;}// 创建一个Grpc的StreamBiRequestStreamGrpc.BiRequestStreamStub biRequestStreamStub = BiRequestStreamGrpc.newStub(newChannelStubTemp.getChannel());// 创建连接信息,保存Grpc的连接信息,也就是长连接的一个holderGrpcConnection grpcConn = new GrpcConnection(serverInfo, grpcExecutor);grpcConn.setConnectionId(((ServerCheckResponse) response).getConnectionId());// 创建stream请求同时绑定到当前连接中StreamObserver<Payload> payloadStreamObserver = bindRequestStream(biRequestStreamStub, grpcConn);// 绑定Grpc相关连接信息grpcConn.setPayloadStreamObserver(payloadStreamObserver);grpcConn.setGrpcFutureServiceStub(newChannelStubTemp);grpcConn.setChannel((ManagedChannel) newChannelStubTemp.getChannel());// 发送一个初始化连接请求,用于上报客户端的一些信息,例如标签、客户端版本等ConnectionSetupRequest conSetupRequest = new ConnectionSetupRequest();conSetupRequest.setClientVersion(VersionUtils.getFullClientVersion());conSetupRequest.setLabels(super.getLabels());conSetupRequest.setAbilities(super.clientAbilities);conSetupRequest.setTenant(super.getTenant());grpcConn.sendRequest(conSetupRequest);// 等待连接建立成功Thread.sleep(100L);return grpcConn;}return null;} catch (Exception e) {LOGGER.error("[{}]Fail to connect to server!,error={}", GrpcClient.this.getName(), e);}return null;}
上面这段代码主要功能有两个,一个是与服务端建立gRPC的长连接,另一个功能主要是初始化连接,后者是实现配置灰度发布的前提。在上文中有提到,配置灰度发布的过程中,需要根据控制台的灰度配置请求中的IP信息过滤长连接,在服务端就是根据连接建立初始化时上报的信息实现的过滤。从上面的代码中可以看到,ConnectionSetupRequest作为一个初始化请求,携带着客户端版本、标签等信息,但是好像并没有携带IP地址的信息。实际上,ConnectionSetupRequest也确实没有携带IP地址信息。因为在Nacos设计中,采用Request来表明客户端的请求信息,而IP地址更像是属于连接层的信息,应该属于连接的元信息,因此并没有放在Request中进行显式的设置,而是在发送请求时自动的作为Metadata信息发送到服务端中。可以看一下com.alibaba.nacos.common.remote.client.grpc包下的GrpcConnection的sendRequest方法,该方法接收一个Request请求作为参数,将请求发送给服务端。
public void sendRequest(Request request) {// 将request转换为Grpc的PayloadPayload convert = GrpcUtils.convert(request);// 通过Grpc的流发送请求payloadStreamObserver.onNext(convert);}
IP地址的设置,就在com.alibaba.nacos.common.remote.client.grpc包下的GrpcUtils的convert方法中,该方法主要将一个Request转换为gRPC的Payload。
/*** convert request to payload.** @param request request.* @return payload.*/public static Payload convert(Request request) {// 设置元信息Metadata newMeta = Metadata.newBuilder().setType(request.getClass().getSimpleName()).setClientIp(NetUtils.localIP()).putAllHeaders(request.getHeaders()).build();request.clearHeaders();// 转换为jsonString jsonString = toJson(request);Payload.Builder builder = Payload.newBuilder();// 创建Payloadreturn builder.setBody(Any.newBuilder().setValue(ByteString.copyFrom(jsonString, Charset.forName(Constants.ENCODE)))).setMetadata(newMeta).build();}
可以看到,这里通过NetUtils.localIP()方法获取客户端的IP信息,并存入到Metadata中,跟随Payload一起上报给服务端。到这里,客户端这里的连接过程就暂时完成了,下面介绍一下服务端接收到连接请求的响应过程。
在服务端,主要通过GrpcBiStreamRequestAcceptor的requestBiStream方法接收客户端请求,如下所示。
@Overridepublic StreamObserver<Payload> requestBiStream(StreamObserver<Payload> responseObserver) {StreamObserver<Payload> streamObserver = new StreamObserver<Payload>() {final String connectionId = CONTEXT_KEY_CONN_ID.get();final Integer localPort = CONTEXT_KEY_CONN_LOCAL_PORT.get();final int remotePort = CONTEXT_KEY_CONN_REMOTE_PORT.get();String remoteIp = CONTEXT_KEY_CONN_REMOTE_IP.get();String clientIp = "";@Overridepublic void onNext(Payload payload) {// 获取客户端IPclientIp = payload.getMetadata().getClientIp();traceDetailIfNecessary(payload);Object parseObj;try {parseObj = GrpcUtils.parse(payload);} catch (Throwable throwable) {Loggers.REMOTE_DIGEST.warn("[{}]Grpc request bi stream,payload parse error={}", connectionId, throwable);return;}if (parseObj == null) {Loggers.REMOTE_DIGEST.warn("[{}]Grpc request bi stream,payload parse null ,body={},meta={}", connectionId,payload.getBody().getValue().toStringUtf8(), payload.getMetadata());return;}// 处理初始化请求if (parseObj instanceof ConnectionSetupRequest) {ConnectionSetupRequest setUpRequest = (ConnectionSetupRequest) parseObj;Map<String, String> labels = setUpRequest.getLabels();String appName = "-";if (labels != null && labels.containsKey(Constants.APPNAME)) {appName = labels.get(Constants.APPNAME);}ConnectionMeta metaInfo = new ConnectionMeta(connectionId, payload.getMetadata().getClientIp(),remoteIp, remotePort, localPort, ConnectionType.GRPC.getType(),setUpRequest.getClientVersion(), appName, setUpRequest.getLabels());metaInfo.setTenant(setUpRequest.getTenant());// 服务端的长连接信息holderConnection connection = new GrpcConnection(metaInfo, responseObserver, CONTEXT_KEY_CHANNEL.get());connection.setAbilities(setUpRequest.getAbilities());boolean rejectSdkOnStarting = metaInfo.isSdkSource() && !ApplicationUtils.isStarted();// 注册connection到connectionManager中if (rejectSdkOnStarting || !connectionManager.register(connectionId, connection)) {//Not register to the connection manager if current server is over limit or server is starting.try {Loggers.REMOTE_DIGEST.warn("[{}]Connection register fail,reason:{}", connectionId,rejectSdkOnStarting ? " server is not started" : " server is over limited.");connection.request(new ConnectResetRequest(), 3000L);connection.close();} catch (Exception e) {//Do nothing.if (connectionManager.traced(clientIp)) {Loggers.REMOTE_DIGEST.warn("[{}]Send connect reset request error,error={}", connectionId, e);}}}} else if (parseObj instanceof Response) {Response response = (Response) parseObj;if (connectionManager.traced(clientIp)) {Loggers.REMOTE_DIGEST.warn("[{}]Receive response of server request ,response={}", connectionId, response);}RpcAckCallbackSynchronizer.ackNotify(connectionId, response);connectionManager.refreshActiveTime(connectionId);} else {Loggers.REMOTE_DIGEST.warn("[{}]Grpc request bi stream,unknown payload receive ,parseObj={}", connectionId,parseObj);}}// ......};return streamObserver;}
这里我们主要看onNext方法,其负责处理客户端的请求信息,即Payload信息。如果是初始化连接的请求ConnectionSetupRequest,就会记录与客户端之间的长连接信息,并注册到ConnectionManager中。ConnectionManager是服务端维护所有客户端连接信息的类,持有所有的长连接信息,后续的配置推送等都需要通过ConnectionManager获取长连接信息。可以简单看一下ConnectionManager的源码,在com.alibaba.nacos.core.remote包下,如下所示。
/*** connect manager.** @author liuzunfei* @version $Id: ConnectionManager.java, v 0.1 2020年07月13日 7:07 PM liuzunfei Exp $*/@Servicepublic class ConnectionManager extends Subscriber<ConnectionLimitRuleChangeEvent> {// ......Map<String, Connection> connections = new ConcurrentHashMap<String, Connection>();// ....../*** register a new connect.** @param connectionId connectionId* @param connection connection*/public synchronized boolean register(String connectionId, Connection connection) {if (connection.isConnected()) {if (connections.containsKey(connectionId)) {return true;}if (!checkLimit(connection)) {return false;}if (traced(connection.getMetaInfo().clientIp)) {connection.setTraced(true);}// 注册connectionconnections.put(connectionId, connection);connectionForClientIp.get(connection.getMetaInfo().clientIp).getAndIncrement();clientConnectionEventListenerRegistry.notifyClientConnected(connection);Loggers.REMOTE_DIGEST.info("new connection registered successfully, connectionId = {},connection={} ", connectionId,connection);return true;}return false;}// ......}
可以看到,在ConnectionManager中,维护了一个Map。在调用register方法时,将Connection注册到Map中,以供后续的逻辑使用。这里有一个细节,注册到ConnectionManager中的GrpcConnection与客户端持有的GrpcConnection不是一个类。这里的GrpcConnection位于com.alibaba.nacos.core.remote.grpc包,而客户端的GrpcConnection位于com.alibaba.nacos.common.remote.client.grpc包。事实上与客户端有关的gRPC相关的类都在com.alibaba.nacos.common.remote.client.grpc。com.alibaba.nacos.core.remote.grpc则是服务端的相关实现。
到这里,长连接建立的核心流程已经介绍完了,接下来笔者将详细介绍一下配置灰度的推送过程,由于Nacos在这里使用了发布订阅模式以及异步的方法调用,理解起来可能稍微要麻烦一点。
灰度推送
在Nacos中,提供了一组OpenAPI进行配置的管理,配置灰度发布也是其中一个功能,可以在com.alibaba.nacos.config.server.controller包下的ConfigController中查看,包括了BetaConfig的发布、停止和查询,接下来笔者将会一一介绍他们的原理。
创建BetaConfig
创建BetaConfig的API代码如下,一个简单的Web的API。
/*** Adds or updates non-aggregated data.** @throws NacosException NacosException.*/@PostMapping@Secured(action = ActionTypes.WRITE, parser = ConfigResourceParser.class)public Boolean publishConfig(HttpServletRequest request, HttpServletResponse response,@RequestParam(value = "dataId") String dataId, @RequestParam(value = "group") String group,@RequestParam(value = "tenant", required = false, defaultValue = StringUtils.EMPTY) String tenant,@RequestParam(value = "content") String content, @RequestParam(value = "tag", required = false) String tag,@RequestParam(value = "appName", required = false) String appName,@RequestParam(value = "src_user", required = false) String srcUser,@RequestParam(value = "config_tags", required = false) String configTags,@RequestParam(value = "desc", required = false) String desc,@RequestParam(value = "use", required = false) String use,@RequestParam(value = "effect", required = false) String effect,@RequestParam(value = "type", required = false) String type,@RequestParam(value = "schema", required = false) String schema) throws NacosException {final String srcIp = RequestUtil.getRemoteIp(request);final String requestIpApp = RequestUtil.getAppName(request);srcUser = RequestUtil.getSrcUserName(request);//check typeif (!ConfigType.isValidType(type)) {type = ConfigType.getDefaultType().getType();}// check tenantParamUtils.checkTenant(tenant);ParamUtils.checkParam(dataId, group, "datumId", content);ParamUtils.checkParam(tag);Map<String, Object> configAdvanceInfo = new HashMap<String, Object>(10);MapUtil.putIfValNoNull(configAdvanceInfo, "config_tags", configTags);MapUtil.putIfValNoNull(configAdvanceInfo, "desc", desc);MapUtil.putIfValNoNull(configAdvanceInfo, "use", use);MapUtil.putIfValNoNull(configAdvanceInfo, "effect", effect);MapUtil.putIfValNoNull(configAdvanceInfo, "type", type);MapUtil.putIfValNoNull(configAdvanceInfo, "schema", schema);ParamUtils.checkParam(configAdvanceInfo);if (AggrWhitelist.isAggrDataId(dataId)) {LOGGER.warn("[aggr-conflict] {} attempt to publish single data, {}, {}", RequestUtil.getRemoteIp(request),dataId, group);throw new NacosException(NacosException.NO_RIGHT, "dataId:" + dataId + " is aggr");}final Timestamp time = TimeUtils.getCurrentTime();// 目标灰度机器的IP地址。String betaIps = request.getHeader("betaIps");ConfigInfo configInfo = new ConfigInfo(dataId, group, tenant, appName, content);configInfo.setType(type);if (StringUtils.isBlank(betaIps)) {if (StringUtils.isBlank(tag)) {persistService.insertOrUpdate(srcIp, srcUser, configInfo, time, configAdvanceInfo, false);ConfigChangePublisher.notifyConfigChange(new ConfigDataChangeEvent(false, dataId, group, tenant, time.getTime()));} else {persistService.insertOrUpdateTag(configInfo, tag, srcIp, srcUser, time, false);ConfigChangePublisher.notifyConfigChange(new ConfigDataChangeEvent(false, dataId, group, tenant, tag, time.getTime()));}} else {// 发布Beta 配置persistService.insertOrUpdateBeta(configInfo, betaIps, srcIp, srcUser, time, false);// 通知配置变更ConfigChangePublisher.notifyConfigChange(new ConfigDataChangeEvent(true, dataId, group, tenant, time.getTime()));}ConfigTraceService.logPersistenceEvent(dataId, group, tenant, requestIpApp, time.getTime(), InetUtils.getSelfIP(),ConfigTraceService.PERSISTENCE_EVENT_PUB, content);return true;}
该方法接收一个创建配置的请求,包括配置的data-id、content等信息。从代码中可以看出,该方法是通过判断请求的Header中有无betaIps的值来确定是发布正式配置还是Beta配置的。如果betaIps的值不为空,则表明待发布的配置是一个Beta配置。而配置发布的过程,实际上就是把配置插入或者更新到数据库中。在Nacos中,正式配置和灰度配置是分别存储在不同的表中的,一旦发布就会通过ConfigChangePublisher发布一个ConfigDataChangeEvent事件,然后由订阅了该事件的监听者推送配置信息到客户端。ConfigDataChangeEvent的监听者是AsyncNotifyService类,位于com.alibaba.nacos.config.server.service.notify包下,该类主要用作执行集群之间的数据Dump操作。该类在初始化的时候,会向事件中心NotifyCenter注册一个监听者,用以监听数据变更事件并异步执行数据的Dump操作,如下所示。
/*** Async notify service.** @author Nacos*/@Servicepublic class AsyncNotifyService {private static final Logger LOGGER = LoggerFactory.getLogger(AsyncNotifyService.class);private final NacosAsyncRestTemplate nacosAsyncRestTemplate = HttpClientManager.getNacosAsyncRestTemplate();private static final int MIN_RETRY_INTERVAL = 500;private static final int INCREASE_STEPS = 1000;private static final int MAX_COUNT = 6;@Autowiredprivate DumpService dumpService;@Autowiredprivate ConfigClusterRpcClientProxy configClusterRpcClientProxy;private ServerMemberManager memberManager;@Autowiredpublic AsyncNotifyService(ServerMemberManager memberManager) {this.memberManager = memberManager;// Register ConfigDataChangeEvent to NotifyCenter.NotifyCenter.registerToPublisher(ConfigDataChangeEvent.class, NotifyCenter.ringBufferSize);// Register A Subscriber to subscribe ConfigDataChangeEvent.NotifyCenter.registerSubscriber(new Subscriber() {@Overridepublic void onEvent(Event event) {// Generate ConfigDataChangeEvent concurrentlyif (event instanceof ConfigDataChangeEvent) {ConfigDataChangeEvent evt = (ConfigDataChangeEvent) event;long dumpTs = evt.lastModifiedTs;String dataId = evt.dataId;String group = evt.group;String tenant = evt.tenant;String tag = evt.tag;Collection<Member> ipList = memberManager.allMembers();// In fact, any type of queue here can beQueue<NotifySingleTask> httpQueue = new LinkedList<NotifySingleTask>();Queue<NotifySingleRpcTask> rpcQueue = new LinkedList<NotifySingleRpcTask>();for (Member member : ipList) {// 判断是否是长轮询if (!MemberUtil.isSupportedLongCon(member)) {// 添加一个长轮询的异步dump任务httpQueue.add(new NotifySingleTask(dataId, group, tenant, tag, dumpTs, member.getAddress(),evt.isBeta));} else {// 添加一个长连接的异步dump任务rpcQueue.add(new NotifySingleRpcTask(dataId, group, tenant, tag, dumpTs, evt.isBeta, member));}}// 判断并执行长轮询的异步dump任务if (!httpQueue.isEmpty()) {ConfigExecutor.executeAsyncNotify(new AsyncTask(nacosAsyncRestTemplate, httpQueue));}// 判断并执行长连接的异步dump任务if (!rpcQueue.isEmpty()) {ConfigExecutor.executeAsyncNotify(new AsyncRpcTask(rpcQueue));}}}@Overridepublic Class<? extends Event> subscribeType() {return ConfigDataChangeEvent.class;}});}}
在接收到ConfigDataChangeEvent之后,如果Nacos2.0以上的版本,会创建一个RpcTask用以执行配置变更的通知,由内部类AsyncRpcTask执行,AsyncRpcTask具体逻辑如下所示。
class AsyncRpcTask implements Runnable {private Queue<NotifySingleRpcTask> queue;public AsyncRpcTask(Queue<NotifySingleRpcTask> queue) {this.queue = queue;}@Overridepublic void run() {while (!queue.isEmpty()) {NotifySingleRpcTask task = queue.poll();// 创建配置变更请求ConfigChangeClusterSyncRequest syncRequest = new ConfigChangeClusterSyncRequest();syncRequest.setDataId(task.getDataId());syncRequest.setGroup(task.getGroup());syncRequest.setBeta(task.isBeta);syncRequest.setLastModified(task.getLastModified());syncRequest.setTag(task.tag);syncRequest.setTenant(task.getTenant());Member member = task.member;// 如果是自身的数据变更,直接执行dump操作if (memberManager.getSelf().equals(member)) {if (syncRequest.isBeta()) {// 同步Beta配置dumpService.dump(syncRequest.getDataId(), syncRequest.getGroup(), syncRequest.getTenant(),syncRequest.getLastModified(), NetUtils.localIP(), true);} else {// 同步正式配置dumpService.dump(syncRequest.getDataId(), syncRequest.getGroup(), syncRequest.getTenant(),syncRequest.getTag(), syncRequest.getLastModified(), NetUtils.localIP());}continue;}// 通知其他服务端进行dumpif (memberManager.hasMember(member.getAddress())) {// start the health check and there are ips that are not monitored, put them directly in the notification queue, otherwise notifyboolean unHealthNeedDelay = memberManager.isUnHealth(member.getAddress());if (unHealthNeedDelay) {// target ip is unhealthy, then put it in the notification listConfigTraceService.logNotifyEvent(task.getDataId(), task.getGroup(), task.getTenant(), null,task.getLastModified(), InetUtils.getSelfIP(), ConfigTraceService.NOTIFY_EVENT_UNHEALTH,0, member.getAddress());// get delay time and set fail count to the taskasyncTaskExecute(task);} else {if (!MemberUtil.isSupportedLongCon(member)) {asyncTaskExecute(new NotifySingleTask(task.getDataId(), task.getGroup(), task.getTenant(), task.tag,task.getLastModified(), member.getAddress(), task.isBeta));} else {try {configClusterRpcClientProxy.syncConfigChange(member, syncRequest, new AsyncRpcNotifyCallBack(task));} catch (Exception e) {MetricsMonitor.getConfigNotifyException().increment();asyncTaskExecute(task);}}}} else {//No nothig if member has offline.}}}}
这里首先创建了一个ConfigChangeClusterSyncRequest,并将配置信息写入。然后获取集群信息,通知相应的Server处理的数据同步请求。同步配置变更信息的核心逻辑由DumpService来执行。我们主要查看同步Beta配置的操作,DumpService的dump方法如下所示。
/*** Add DumpTask to TaskManager, it will execute asynchronously.*/public void dump(String dataId, String group, String tenant, long lastModified, String handleIp, boolean isBeta) {String groupKey = GroupKey2.getKey(dataId, group, tenant);String taskKey = String.join("+", dataId, group, tenant, String.valueOf(isBeta));dumpTaskMgr.addTask(taskKey, new DumpTask(groupKey, lastModified, handleIp, isBeta));DUMP_LOG.info("[dump-task] add task. groupKey={}, taskKey={}", groupKey, taskKey);}
在该方法中,这里会根据配置变更信息,提交一个异步的DumpTask任务,后续会由DumpProcessor类的process方法进行处理,该方法如下所示。
/*** dump processor.** @author Nacos* @date 2020/7/5 12:19 PM*/public class DumpProcessor implements NacosTaskProcessor {final DumpService dumpService;public DumpProcessor(DumpService dumpService) {this.dumpService = dumpService;}@Overridepublic boolean process(NacosTask task) {final PersistService persistService = dumpService.getPersistService();DumpTask dumpTask = (DumpTask) task;String[] pair = GroupKey2.parseKey(dumpTask.getGroupKey());String dataId = pair[0];String group = pair[1];String tenant = pair[2];long lastModified = dumpTask.getLastModified();String handleIp = dumpTask.getHandleIp();boolean isBeta = dumpTask.isBeta();String tag = dumpTask.getTag();ConfigDumpEvent.ConfigDumpEventBuilder build = ConfigDumpEvent.builder().namespaceId(tenant).dataId(dataId).group(group).isBeta(isBeta).tag(tag).lastModifiedTs(lastModified).handleIp(handleIp);if (isBeta) {// 更新Beta配置的缓存ConfigInfo4Beta cf = persistService.findConfigInfo4Beta(dataId, group, tenant);build.remove(Objects.isNull(cf));build.betaIps(Objects.isNull(cf) ? null : cf.getBetaIps());build.content(Objects.isNull(cf) ? null : cf.getContent());return DumpConfigHandler.configDump(build.build());}if (StringUtils.isBlank(tag)) {ConfigInfo cf = persistService.findConfigInfo(dataId, group, tenant);build.remove(Objects.isNull(cf));build.content(Objects.isNull(cf) ? null : cf.getContent());build.type(Objects.isNull(cf) ? null : cf.getType());} else {ConfigInfo4Tag cf = persistService.findConfigInfo4Tag(dataId, group, tenant, tag);build.remove(Objects.isNull(cf));build.content(Objects.isNull(cf) ? null : cf.getContent());}return DumpConfigHandler.configDump(build.build());}}
可以看到,如果是Beta配置,则获取最新的Beta配置信息,然后触发DumpConfigHandler的configDump方法。进入configDump可以看到,该方法主要用来更新缓存的配置信息,调用ConfigCacheService的相关操作进行配置的更新。
/*** Dump config subscriber.** @author <a href="mailto:liaochuntao@live.com">liaochuntao</a>*/public class DumpConfigHandler extends Subscriber<ConfigDumpEvent> {/*** trigger config dump event.** @param event {@link ConfigDumpEvent}* @return {@code true} if the config dump task success , else {@code false}*/public static boolean configDump(ConfigDumpEvent event) {final String dataId = event.getDataId();final String group = event.getGroup();final String namespaceId = event.getNamespaceId();final String content = event.getContent();final String type = event.getType();final long lastModified = event.getLastModifiedTs();if (event.isBeta()) {boolean result = false;// 删除操作if (event.isRemove()) {result = ConfigCacheService.removeBeta(dataId, group, namespaceId);if (result) {ConfigTraceService.logDumpEvent(dataId, group, namespaceId, null, lastModified, event.getHandleIp(),ConfigTraceService.DUMP_EVENT_REMOVE_OK, System.currentTimeMillis() - lastModified, 0);}return result;} else {// 更新或者发布result = ConfigCacheService.dumpBeta(dataId, group, namespaceId, content, lastModified, event.getBetaIps());if (result) {ConfigTraceService.logDumpEvent(dataId, group, namespaceId, null, lastModified, event.getHandleIp(),ConfigTraceService.DUMP_EVENT_OK, System.currentTimeMillis() - lastModified,content.length());}}return result;}// ......}@Overridepublic void onEvent(ConfigDumpEvent event) {configDump(event);}@Overridepublic Class<? extends Event> subscribeType() {return ConfigDumpEvent.class;}}
在ConfigCacheService中,会对比配置信息,如果配置有变化,则发布事件LocalDataChangeEvent,触发RpcConfigChangeNotifier的configDataChanged方法来推送配置,configDataChanged方法代码如下。
/*** ConfigChangeNotifier.** @author liuzunfei* @version $Id: ConfigChangeNotifier.java, v 0.1 2020年07月20日 3:00 PM liuzunfei Exp $*/@Component(value = "rpcConfigChangeNotifier")public class RpcConfigChangeNotifier extends Subscriber<LocalDataChangeEvent> {// ......@AutowiredConfigChangeListenContext configChangeListenContext;@Autowiredprivate RpcPushService rpcPushService;@Autowiredprivate ConnectionManager connectionManager;/*** adaptor to config module ,when server side config change ,invoke this method.** @param groupKey groupKey*/public void configDataChanged(String groupKey, String dataId, String group, String tenant, boolean isBeta,List<String> betaIps, String tag) {// 获取配置的所有监听者Set<String> listeners = configChangeListenContext.getListeners(groupKey);if (CollectionUtils.isEmpty(listeners)) {return;}int notifyClientCount = 0;// 遍历所有监听者for (final String client : listeners) {// 获取长连接信息Connection connection = connectionManager.getConnection(client);if (connection == null) {continue;}String clientIp = connection.getMetaInfo().getClientIp();String clientTag = connection.getMetaInfo().getTag();// 判断是否是Beta的Ipif (isBeta && betaIps != null && !betaIps.contains(clientIp)) {continue;}// tag checkif (StringUtils.isNotBlank(tag) && !tag.equals(clientTag)) {continue;}// 配置变更推送请求ConfigChangeNotifyRequest notifyRequest = ConfigChangeNotifyRequest.build(dataId, group, tenant);// 执行推送任务RpcPushTask rpcPushRetryTask = new RpcPushTask(notifyRequest, 50, client, clientIp,connection.getMetaInfo().getAppName());push(rpcPushRetryTask);notifyClientCount++;}Loggers.REMOTE_PUSH.info("push [{}] clients ,groupKey=[{}]", notifyClientCount, groupKey);}@Overridepublic void onEvent(LocalDataChangeEvent event) {String groupKey = event.groupKey;boolean isBeta = event.isBeta;List<String> betaIps = event.betaIps;String[] strings = GroupKey.parseKey(groupKey);String dataId = strings[0];String group = strings[1];String tenant = strings.length > 2 ? strings[2] : "";String tag = event.tag;configDataChanged(groupKey, dataId, group, tenant, isBeta, betaIps, tag);}// ......}
到这里,基本上就是配置变更推送的最后一个步骤了,如代码中注释所示,通过调用ConnectionManager的getConnection方法,遍历所有监听者的连接,根据其中的Meta信息判断是否是Beta推送的目标,然后执行推送任务,也就是执行push方法,如下所示。
private void push(RpcPushTask retryTask) {ConfigChangeNotifyRequest notifyRequest = retryTask.notifyRequest;// 判断是否重试次数达到限制if (retryTask.isOverTimes()) {Loggers.REMOTE_PUSH.warn("push callback retry fail over times .dataId={},group={},tenant={},clientId={},will unregister client.",notifyRequest.getDataId(), notifyRequest.getGroup(), notifyRequest.getTenant(),retryTask.connectionId);// 主动注销连接connectionManager.unregister(retryTask.connectionId);} else if (connectionManager.getConnection(retryTask.connectionId) != null) {// first time :delay 0s; sencond time:delay 2s ;third time :delay 4s// 尝试执行配置推送ConfigExecutor.getClientConfigNotifierServiceExecutor().schedule(retryTask, retryTask.tryTimes * 2, TimeUnit.SECONDS);} else {// client is already offline,ingnore task.}}
这里实际上也是一个异步执行的过程,推送任务RpcPushTask会被提交到ClientConfigNotifierServiceExecutor来计划执行,第一次会立即推送配置,即调用RpcPushTask的run方法,如果失败则延迟重试次数x2的秒数再次执行,直到超过重试次数,主动注销当前连接。其中,RpcPushTask的定义如下。
class RpcPushTask implements Runnable {ConfigChangeNotifyRequest notifyRequest;int maxRetryTimes = -1;int tryTimes = 0;String connectionId;String clientIp;String appName;public RpcPushTask(ConfigChangeNotifyRequest notifyRequest, int maxRetryTimes, String connectionId,String clientIp, String appName) {this.notifyRequest = notifyRequest;this.maxRetryTimes = maxRetryTimes;this.connectionId = connectionId;this.clientIp = clientIp;this.appName = appName;}public boolean isOverTimes() {return maxRetryTimes > 0 && this.tryTimes >= maxRetryTimes;}@Overridepublic void run() {tryTimes++;if (!tpsMonitorManager.applyTpsForClientIp(POINT_CONFIG_PUSH, connectionId, clientIp)) {push(this);} else {// 推送配置rpcPushService.pushWithCallback(connectionId, notifyRequest, new AbstractPushCallBack(3000L) {@Overridepublic void onSuccess() {tpsMonitorManager.applyTpsForClientIp(POINT_CONFIG_PUSH_SUCCESS, connectionId, clientIp);}@Overridepublic void onFail(Throwable e) {tpsMonitorManager.applyTpsForClientIp(POINT_CONFIG_PUSH_FAIL, connectionId, clientIp);Loggers.REMOTE_PUSH.warn("Push fail", e);push(RpcPushTask.this);}}, ConfigExecutor.getClientConfigNotifierServiceExecutor());}}}
可以看到,在RpcPushTask的run方法中,调用了RpcPushService的pushWithCallback方法,如下所示。
/*** push response to clients.** @author liuzunfei* @version $Id: PushService.java, v 0.1 2020年07月20日 1:12 PM liuzunfei Exp $*/@Servicepublic class RpcPushService {@Autowiredprivate ConnectionManager connectionManager;/*** push response with no ack.** @param connectionId connectionId.* @param request request.* @param requestCallBack requestCallBack.*/public void pushWithCallback(String connectionId, ServerRequest request, PushCallBack requestCallBack,Executor executor) {Connection connection = connectionManager.getConnection(connectionId);if (connection != null) {try {// 执行配置推送connection.asyncRequest(request, new AbstractRequestCallBack(requestCallBack.getTimeout()) {@Overridepublic Executor getExecutor() {return executor;}@Overridepublic void onResponse(Response response) {if (response.isSuccess()) {requestCallBack.onSuccess();} else {requestCallBack.onFail(new NacosException(response.getErrorCode(), response.getMessage()));}}@Overridepublic void onException(Throwable e) {requestCallBack.onFail(e);}});} catch (ConnectionAlreadyClosedException e) {connectionManager.unregister(connectionId);requestCallBack.onSuccess();} catch (Exception e) {Loggers.REMOTE_DIGEST.error("error to send push response to connectionId ={},push response={}", connectionId,request, e);requestCallBack.onFail(e);}} else {requestCallBack.onSuccess();}}}
其持有ConnectionManager对象,当需要推送配置到客户端时,会获取相应的Connection,然后执行asyncRequest将配置推送到客户端中。如果连接已经关闭,则注销连接。在asyncRequest底层即是调用Grpc建立的Stream的onNext方法,将配置推送给客户端,如下。
/*** grpc connection.** @author liuzunfei* @version $Id: GrpcConnection.java, v 0.1 2020年07月13日 7:26 PM liuzunfei Exp $*/public class GrpcConnection extends Connection {private StreamObserver streamObserver;private Channel channel;public GrpcConnection(ConnectionMeta metaInfo, StreamObserver streamObserver, Channel channel) {super(metaInfo);this.streamObserver = streamObserver;this.channel = channel;}@Overridepublic void asyncRequest(Request request, RequestCallBack requestCallBack) throws NacosException {sendRequestInner(request, requestCallBack);}private DefaultRequestFuture sendRequestInner(Request request, RequestCallBack callBack) throws NacosException {final String requestId = String.valueOf(PushAckIdGenerator.getNextId());request.setRequestId(requestId);DefaultRequestFuture defaultPushFuture = new DefaultRequestFuture(getMetaInfo().getConnectionId(), requestId,callBack, () -> RpcAckCallbackSynchronizer.clearFuture(getMetaInfo().getConnectionId(), requestId));RpcAckCallbackSynchronizer.syncCallback(getMetaInfo().getConnectionId(), requestId, defaultPushFuture);sendRequestNoAck(request);return defaultPushFuture;}private void sendRequestNoAck(Request request) throws NacosException {try {//StreamObserver#onNext() is not thread-safe,synchronized is required to avoid direct memory leak.synchronized (streamObserver) {Payload payload = GrpcUtils.convert(request);traceIfNecessary(payload);streamObserver.onNext(payload);}} catch (Exception e) {if (e instanceof StatusRuntimeException) {throw new ConnectionAlreadyClosedException(e);}throw e;}}}
主要推送逻辑的代码如上所示,调用asyncRequest之后,会将请求交给sendRequestInner处理,sendRequestInner又会调用sendRequestNoAck将推送请求推入gRPC的流中,客户端收到配置更新的请求,就会更新客户端的配置了。至此,一个灰度配置就发布成功了。
删除/查询BetaConfig
删除和查询BetaConfig的方法都很简单,都是简单的操作数据库即可。如果是删除配置,则会触发ConfigDataChangeEvent来告知客户端更新配置,这里笔者就不多加赘述了。
/*** Execute to remove beta operation.** @param dataId dataId string value.* @param group group string value.* @param tenant tenant string value.* @return Execute to operate result.*/@DeleteMapping(params = "beta=true")@Secured(action = ActionTypes.WRITE, parser = ConfigResourceParser.class)public RestResult<Boolean> stopBeta(@RequestParam(value = "dataId") String dataId,@RequestParam(value = "group") String group,@RequestParam(value = "tenant", required = false, defaultValue = StringUtils.EMPTY) String tenant) {try {persistService.removeConfigInfo4Beta(dataId, group, tenant);} catch (Throwable e) {LOGGER.error("remove beta data error", e);return RestResultUtils.failed(500, false, "remove beta data error");}ConfigChangePublisher.notifyConfigChange(new ConfigDataChangeEvent(true, dataId, group, tenant, System.currentTimeMillis()));return RestResultUtils.success("stop beta ok", true);}/*** Execute to query beta operation.** @param dataId dataId string value.* @param group group string value.* @param tenant tenant string value.* @return RestResult for ConfigInfo4Beta.*/@GetMapping(params = "beta=true")@Secured(action = ActionTypes.READ, parser = ConfigResourceParser.class)public RestResult<ConfigInfo4Beta> queryBeta(@RequestParam(value = "dataId") String dataId,@RequestParam(value = "group") String group,@RequestParam(value = "tenant", required = false, defaultValue = StringUtils.EMPTY) String tenant) {try {ConfigInfo4Beta ci = persistService.findConfigInfo4Beta(dataId, group, tenant);return RestResultUtils.success("stop beta ok", ci);} catch (Throwable e) {LOGGER.error("remove beta data error", e);return RestResultUtils.failed("remove beta data error");}}
总结
Nacos2.0使用长连接代替了短连接的长轮询,性能几乎提升了10倍。在阿里内部,也在逐渐推进Nacos2作为统一的配置中心。目前在微服务引擎(Micro Service Engine,简称 MSE),Nacos作为注册配置中心,提供了纯托管的服务,只需要购买Nacos专业版即可享受到10倍的性能提升。
此外,MSE微服务引擎顾名思义,是一个面向业界主流开源微服务生态的一站式微服务平台, 帮助微服务用户更稳定、更便捷、更低成本的使用开源微服务技术构建微服务体系。不但提供注册中心、配置中心全托管(兼容 Nacos/ZooKeeper/Eureka),而且提供网关(兼容 Ingress/Enovy)和无侵入的开源增强服务治理能力。
在阿里,MSE微服务引擎已经被大规模的接入使用,经历阿里内部生产考验以及反复淬炼,其中微服务服务治理能力支撑了大量的微服务系统,对包括Spring Cloud、Dubbo等微服务框架的治理功能增强,提供了无损上下线、金丝雀发布、离群摘除以及无损滚动升级的功能。
如果有快速搭建高性能微服务以及大规模服务治理的需求,相比于从零搭建和运维,MSE微服务引擎是一个不错的选择。
