Nacos2.0配置灰度发布原理源码解析
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2021-09-02 08:18
本文作者:宁与(包冬庆),目前在【阿里云云原生中间件】团队实习
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。
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。
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。
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。
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。
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。
@Override
public Connection connectToServer(ServerInfo serverInfo) {
try {
// ......
int port = serverInfo.getServerPort() + rpcPortOffset();
// 创建一个Grpc的Stub
RequestGrpc.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Stream
BiRequestStreamGrpc.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holder
GrpcConnection 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Payload
Payload 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json
String jsonString = toJson(request);
Payload.Builder builder = Payload.newBuilder();
// 创建Payload
return 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。
@Override
public 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 = "";
@Override
public void onNext(Payload payload) {
// 获取客户端IP
clientIp = 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holder
Connection 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 $
*/
@Service
public 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connection
connections.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 type
if (!ConfigType.isValidType(type)) {
type = ConfigType.getDefaultType().getType();
}
// check tenant
ParamUtils.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
*/
@Service
public 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;
@Autowired
private DumpService dumpService;
@Autowired
private ConfigClusterRpcClientProxy configClusterRpcClientProxy;
private ServerMemberManager memberManager;
@Autowired
public 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() {
@Override
public void onEvent(Event event) {
// Generate ConfigDataChangeEvent concurrently
if (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 be
Queue<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));
}
}
}
@Override
public 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;
}
@Override
public 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dump
if (memberManager.hasMember(member.getAddress())) {
// start the health check and there are ips that are not monitored, put them directly in the notification queue, otherwise notify
boolean unHealthNeedDelay = memberManager.isUnHealth(member.getAddress());
if (unHealthNeedDelay) {
// target ip is unhealthy, then put it in the notification list
ConfigTraceService.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 task
asyncTaskExecute(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;
}
@Override
public 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;
}
// ......
}
@Override
public void onEvent(ConfigDumpEvent event) {
configDump(event);
}
@Override
public 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> {
// ......
@Autowired
ConfigChangeListenContext configChangeListenContext;
@Autowired
private RpcPushService rpcPushService;
@Autowired
private 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Ip
if (isBeta && betaIps != null && !betaIps.contains(clientIp)) {
continue;
}
// tag check
if (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);
}
@Override
public 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;
}
@Override
public 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) {
@Override
public void onSuccess() {
tpsMonitorManager.applyTpsForClientIp(POINT_CONFIG_PUSH_SUCCESS, connectionId, clientIp);
}
@Override
public 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 $
*/
@Service
public class RpcPushService {
@Autowired
private 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()) {
@Override
public Executor getExecutor() {
return executor;
}
@Override
public void onResponse(Response response) {
if (response.isSuccess()) {
requestCallBack.onSuccess();
} else {
requestCallBack.onFail(new NacosException(response.getErrorCode(), response.getMessage()));
}
}
@Override
public 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;
}
@Override
public 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。