鉴于内容过多，先上太长不看版：
grpc 就是请求流&响应流特殊一点的 Http 请求，性能和 WebAPI 比起来只快在 Protobuf 上；附上完整试验代码：GrpcWithOutSDK.zip
另附小Demo，基于 Controller 和 HttpClient 的在线聊天室：ChatRoomOnController.zip
本文内容有点长，涉及较多基础知识点，某些结论可能直接得出，没有上下文，限于篇幅，不会在本文内详细描述，如有疑惑请友好交流或尝试搜索互联网。
本文仅代表个人试验结果和观点，可能会有偏颇，请自行判断。
个人经常在网上看到 grpc、高性能 字眼的文章；有幸也面试过一些同僚，问及 grpc 对比 WebAPI，答案都是更快、性能更高；至于能快多少，答案就各种各样了，几倍到几十倍的回答都有，但大概是统一的：“grpc 要快得多”。那么具体快在哪里呢？回答我就觉得不那么准确了。
现在我们就来探索一下 grpc 和 WebAPI 的差别是什么？ grpc 快在哪里？
就是个常规的 asp.net core 使用 grpc 的步骤
asp.net core grpc 项目
reverse.proto 用于测试 grpc 的几种通讯模式，并为其生成服务端syntax = "proto3";option csharp_namespace = "GrpcWithOutSDK";package reverse;service Reverse { rpc Simple (Request) returns (Reply); rpc ClientSide (stream Request) returns (Reply); rpc ServerSide (Request) returns (stream Reply); rpc Bidirectional (stream Request) returns (stream Reply);}message Request { string message = 1;}message Reply { string message = 1;}ReverseService.cs 实现具体的方法逻辑public class ReverseService : Reverse.ReverseBase{ private readonly ILogger<ReverseService> _logger; public ReverseService(ILogger<ReverseService> logger) { _logger = logger; } private static Reply CreateReplay(Request request) { return new Reply { Message = new string(request.Message.Reverse().ToArray()) }; } private void DisplayReceivedMessage(Request request, [CallerMemberName] string? methodName = null) { _logger.LogInformation($"{methodName} Received: {request.Message}"); } public override async Task Bidirectional(IAsyncStreamReader<Request> requestStream, IServerStreamWriter<Reply> responseStream, ServerCallContext context) { while (await requestStream.MoveNext()) { DisplayReceivedMessage(requestStream.Current); await responseStream.WriteAsync(CreateReplay(requestStream.Current)); } } public override async Task<Reply> ClientSide(IAsyncStreamReader<Request> requestStream, ServerCallContext context) { var total = 0; while (await requestStream.MoveNext()) { total++; DisplayReceivedMessage(requestStream.Current); } return new Reply { Message = $"{nameof(ServerSide)} Received Over. Total: {total}" }; } public override async Task ServerSide(Request request, IServerStreamWriter<Reply> responseStream, ServerCallContext context) { DisplayReceivedMessage(request); for (int i = 0; i < 5; i++) { await responseStream.WriteAsync(CreateReplay(request)); } } public override Task<Reply> Simple(Request request, ServerCallContext context) { return Task.FromResult(CreateReplay(request)); }}最后记得 app.MapGrpcService<ReverseService>();
Google.Protobuf、Grpc.Net.Client、Grpc.Tools这几个包的引用reverse.proto 并为其生成客户端private static async Task Bidirectional(Reverse.ReverseClient client){ var stream = client.Bidirectional(); var sendTask = Task.Run(async () => { for (int i = 0; i < 10; i++) { await stream.RequestStream.WriteAsync(new() { Message = $"{nameof(Bidirectional)}-{i}" }); } await stream.RequestStream.CompleteAsync(); }); var receiveTask = Task.Run(async () => { while (await stream.ResponseStream.MoveNext(default)) { DisplayReceivedMessage(stream.ResponseStream.Current); } }); await Task.WhenAll(sendTask, receiveTask);}private static async Task ClientSide(Reverse.ReverseClient client){ var stream = client.ClientSide(); for (int i = 0; i < 5; i++) { await stream.RequestStream.WriteAsync(new() { Message = $"{nameof(ClientSide)}-{i}" }); } await stream.RequestStream.CompleteAsync(); var reply = await stream.ResponseAsync; DisplayReceivedMessage(reply);}private static async Task Sample(Reverse.ReverseClient client){ var reply = await client.SimpleAsync(new() { Message = nameof(Sample) }); DisplayReceivedMessage(reply);}private static async Task ServerSide(Reverse.ReverseClient client){ var stream = client.ServerSide(new() { Message = nameof(ServerSide) }); while (await stream.ResponseStream.MoveNext(default)) { DisplayReceivedMessage(stream.ResponseStream.Current); }}const string Host = "http://localhost:5035";var channel = GrpcChannel.ForAddress(Host);var grpcClient = new Reverse.ReverseClient(channel);await Sample(grpcClient);await ClientSide(grpcClient);await ServerSide(grpcClient);await Bidirectional(grpcClient);Microsoft.AspNetCore 日志等级调整为 Information 以打印请求日志info: Microsoft.AspNetCore.Hosting.Diagnostics[1] Request starting HTTP/2 POST http://localhost:5035/reverse.Reverse/Simple application/grpc -info: Microsoft.AspNetCore.Routing.EndpointMiddleware[0] Executing endpoint 'gRPC - /reverse.Reverse/Simple'info: Microsoft.AspNetCore.Routing.EndpointMiddleware[1] Executed endpoint 'gRPC - /reverse.Reverse/Simple'info: Microsoft.AspNetCore.Hosting.Diagnostics[2] Request finished HTTP/2 POST http://localhost:5035/reverse.Reverse/Simple application/grpc - - 200 - application/grpc 99.1956msinfo: Microsoft.AspNetCore.Hosting.Diagnostics[1] Request starting HTTP/2 POST http://localhost:5035/reverse.Reverse/ClientSide application/grpc -info: Microsoft.AspNetCore.Routing.EndpointMiddleware[0] Executing endpoint 'gRPC - /reverse.Reverse/ClientSide'info: Microsoft.AspNetCore.Routing.EndpointMiddleware[1] Executed endpoint 'gRPC - /reverse.Reverse/ClientSide'info: Microsoft.AspNetCore.Hosting.Diagnostics[2] Request finished HTTP/2 POST http://localhost:5035/reverse.Reverse/ClientSide application/grpc - - 200 - application/grpc 21.9445msinfo: Microsoft.AspNetCore.Hosting.Diagnostics[1] Request starting HTTP/2 POST http://localhost:5035/reverse.Reverse/ServerSide application/grpc -info: Microsoft.AspNetCore.Routing.EndpointMiddleware[0] Executing endpoint 'gRPC - /reverse.Reverse/ServerSide'info: Microsoft.AspNetCore.Routing.EndpointMiddleware[1] Executed endpoint 'gRPC - /reverse.Reverse/ServerSide'info: Microsoft.AspNetCore.Hosting.Diagnostics[2] Request finished HTTP/2 POST http://localhost:5035/reverse.Reverse/ServerSide application/grpc - - 200 - application/grpc 12.7054msinfo: Microsoft.AspNetCore.Hosting.Diagnostics[1] Request starting HTTP/2 POST http://localhost:5035/reverse.Reverse/Bidirectional application/grpc -info: Microsoft.AspNetCore.Routing.EndpointMiddleware[0] Executing endpoint 'gRPC - /reverse.Reverse/Bidirectional'info: Microsoft.AspNetCore.Routing.EndpointMiddleware[1] Executed endpoint 'gRPC - /reverse.Reverse/Bidirectional'info: Microsoft.AspNetCore.Hosting.Diagnostics[2] Request finished HTTP/2 POST http://localhost:5035/reverse.Reverse/Bidirectional application/grpc - - 200 - application/grpc 41.2414ms对日志进行一些分析我们可以发现：
grpc 通讯模式执行逻辑都是相同的，都是一次完整的http请求周期；HTTP/2；POST；/{package名}.{service名}/{方法名}；ContentType 都为 application/grpc；如果我们上一步的分析是对的，那么数据只能承载在 请求流 & 响应流 中，我们可以尝试获取流中的数据，进一步分析具体细节；
借助 asp.net core 的中间件，我们可以比较容易的进行 请求流 & 响应流 的内容 dump；
请求流 是只读的，响应流 是只写的，我们需要两个代理流替换原有的流，进行数据dump，将数据保存到 MemoryStream 中，以便我们观察；
这两个流分别为 ReadCacheProxyStream.cs 和 WriteCacheProxyStream.cs，直接上代码：
public class ReadCacheProxyStream : Stream{ private readonly Stream _innerStream; public MemoryStream CachedStream { get; } = new MemoryStream(1024); public override bool CanRead => _innerStream.CanRead; public override bool CanSeek => false; public override bool CanWrite => false; public override long Length => _innerStream.Length; public override long Position { get => _innerStream.Length; set => throw new NotSupportedException(); } public ReadCacheProxyStream(Stream innerStream) { _innerStream = innerStream; } public override void Flush() => throw new NotSupportedException(); public override Task FlushAsync(CancellationToken cancellationToken) => _innerStream.FlushAsync(cancellationToken); public override int Read(byte[] buffer, int offset, int count) => throw new NotSupportedException(); public override async ValueTask<int> ReadAsync(Memory<byte> buffer, CancellationToken cancellationToken = default) { var len = await _innerStream.ReadAsync(buffer, cancellationToken); if (len > 0) { CachedStream.Write(buffer.Span.Slice(0, len)); } return len; } public override long Seek(long offset, SeekOrigin origin) => throw new NotSupportedException(); public override void SetLength(long value) => throw new NotSupportedException(); public override void Write(byte[] buffer, int offset, int count) => throw new NotSupportedException();}public class WriteCacheProxyStream : Stream{ private readonly Stream _innerStream; public MemoryStream CachedStream { get; } = new MemoryStream(1024); public override bool CanRead => false; public override bool CanSeek => false; public override bool CanWrite => _innerStream.CanWrite; public override long Length => _innerStream.Length; public override long Position { get => _innerStream.Length; set => throw new NotSupportedException(); } public WriteCacheProxyStream(Stream innerStream) { _innerStream = innerStream; } public override void Flush() => throw new NotSupportedException(); public override Task FlushAsync(CancellationToken cancellationToken) => _innerStream.FlushAsync(cancellationToken); public override int Read(byte[] buffer, int offset, int count) => throw new NotSupportedException(); public override long Seek(long offset, SeekOrigin origin) => throw new NotSupportedException(); public override void SetLength(long value) => throw new NotSupportedException(); public override void Write(byte[] buffer, int offset, int count) => throw new NotSupportedException(); public override async ValueTask WriteAsync(ReadOnlyMemory<byte> buffer, CancellationToken cancellationToken = default) { await _innerStream.WriteAsync(buffer, cancellationToken); CachedStream.Write(buffer.Span); }}app.Use(async (context, next) =>{ var originRequestBody = context.Request.Body; var originResponseBody = context.Response.Body; var requestCacheStream = new ReadCacheProxyStream(originRequestBody); var responseCacheStream = new WriteCacheProxyStream(originResponseBody); context.Request.Body = requestCacheStream; context.Response.Body = responseCacheStream; try { await next(); } finally { await context.Response.CompleteAsync(); //要不要还回去不在这里进行讨论了 context.Request.Body = originRequestBody; context.Response.Body = originResponseBody; var requestData = requestCacheStream.CachedStream.ToArray(); var responseData = requestCacheStream.CachedStream.ToArray(); }});finally 块的最后打上断点，然后运行服务端和客户端，即可在中间件中通过 requestData 和 responseData 观察数据交互 理论上我们可以直接使用 Protobuf 进行解析，不过这里我们目的是为了手动实现一个超级简单的编码器。。。
客户端执行 Sample 方法，并在服务端获取 requestData 和 responseData：
requestData
这个样子太不直观了，由于我们的消息定义 Request 只有一个 string 类型的字段，那么如果之前猜测正确，这个数据里面必定有对应字符串。我们直接尝试拿来看看：
果然有对应的数据 Sample ，我们尝试去掉多余的数据看看：
那么前7个byte是干什么的呢，我们改一下请求的消息内容，将 Sample 修改为 Sample1 再次进行分析：
这样就比较明显了，稍做分析，我们可以先做个简单的总结，第5个字节为消息的总长度，第6个字节应该是字段描述之类的，当前消息体固定为10，第7个字节为Request.message字段的长度；
不过这样有点草率，byte最大为255，我们再探索一下内容超过255时，是什么结构。将 Sample 修改为 50 个重复的 Sample 再次进行分析：
情况一下就复杂了。。。不过第6个字节仍然是10，那么前5个字节应该有描述消息总长度，[0,0,0,1,47] 和长度 303 (注：308-5)之间的关系是什么呢；稍微试了一下，数据的第1个字节目前假设固定为0，第2-5字节应该是一个大端序的uint32，用来声明消息总长度
但是第7、8个字节如何转换为300，就有点难琢磨了。。。算了，我们先不处理内容过大的情况吧（具体编码逻辑可参见 protocol-buffers-encoding）
responseData查看后发现结构和 requestData 是一样的（因为 Request 和 Reply 消息声明的结构相同），这里就不多描述了，可以自行Debug查看。
requestData和responseData分析后发现流式请求里面的多个消息每个都是单个消息的结构，然后顺序放到请求或响应流中，这里也不多描述了，可以自行Debug进行查看，直接上基于以上总结的解码器代码：
public static IEnumerable<string> ReadMessages(byte[] originData){ var slice = originData.AsMemory(); while (!slice.IsEmpty) { var messageLen = BinaryPrimitives.ReadInt32BigEndian(slice.Slice(1, 4).Span); var messageData = slice.Slice(5, messageLen); slice = slice.Slice(5 + messageLen); int len = messageData.Span[1]; var content = Encoding.UTF8.GetString(messageData.Slice(2, len).Span); yield return content; }}然后在中间件中展示内容
TempMessageCodecUtil.DisplayMessages(requestData);TempMessageCodecUtil.DisplayMessages(responseData);再次运行程序，能够正确看到控制台直接输出的请求和响应消息内容，形如：
Controller 实现能够与 Grpc Client SDK 交互的服务端基于之前的分析，理论上我们只需要满足：
- 请求的协议使用的是 `HTTP/2`； - 方法都为 `POST`； - 所有grpc方法都映射到了对应的终结点 `/{package名}.{service名}/{方法名}`； - 请求&响应的 `ContentType` 都为 `application/grpc`；然后正确的从请求流中解析数据结构，将正确的数据结构写入响应流，就可以响应 Grpc Client 的请求了。
Reply 消息格式；以及一个解码器，从请求流中读取 Request 消息。直接上代码。编码器：public static byte[] BuildMessage(string message){ var contentData = Encoding.UTF8.GetBytes(message); if (contentData.Length > 127) { throw new ArgumentException(); } var messageData = new byte[contentData.Length + 7]; Array.Copy(contentData, 0, messageData, 7, contentData.Length); messageData[5] = 10; messageData[6] = (byte)contentData.Length; BinaryPrimitives.WriteInt32BigEndian(messageData.AsSpan().Slice(1), contentData.Length + 2); return messageData;}解码器：
private async IAsyncEnumerable<string> ReadMessageAsync([EnumeratorCancellation] CancellationToken cancellationToken){ var pipeReader = Request.BodyReader; while (!cancellationToken.IsCancellationRequested) { var readResult = await pipeReader.ReadAsync(cancellationToken); var buffer = readResult.Buffer; if (readResult.IsCompleted && buffer.IsEmpty) { yield break; } if (buffer.Length < 5) { pipeReader.AdvanceTo(buffer.Start, buffer.End); continue; } var messageBuffer = buffer.IsSingleSegment ? buffer.First : buffer.ToArray(); var messageLen = BinaryPrimitives.ReadInt32BigEndian(messageBuffer.Slice(1, 4).Span); if (buffer.Length < messageLen + 5) { pipeReader.AdvanceTo(buffer.Start, buffer.End); continue; } messageBuffer = messageBuffer.Slice(5); int len = messageBuffer.Span[1]; var content = Encoding.UTF8.GetString(messageBuffer.Slice(2, len).Span); yield return content; pipeReader.AdvanceTo(readResult.Buffer.GetPosition(7 + len)); }}ReverseController.cs ，映射 reverse.proto 中对应的方法，实现和 ReverseService.cs 中相同的执行逻辑。代码如下：[Route("reverse.Reverse")][ApiController]public class ReverseController : ControllerBase{ [HttpPost] [Route(nameof(Bidirectional))] public async Task Bidirectional() { await foreach (var item in ReadMessageAsync(HttpContext.RequestAborted)) { DisplayReceivedMessage(item); await ReplayReverseAsync(item); } } [HttpPost] [Route(nameof(ClientSide))] public async Task ClientSide() { var total = 0; await foreach (var item in ReadMessageAsync(HttpContext.RequestAborted)) { total++; DisplayReceivedMessage(item); } await ReplayAsync($"{nameof(ServerSide)} Received Over. Total: {total}"); } [HttpPost] [Route(nameof(ServerSide))] public async Task ServerSide() { string message = null!; await foreach (var item in ReadMessageAsync(HttpContext.RequestAborted)) { message = item; } DisplayReceivedMessage(message); for (int i = 0; i < 5; i++) { await ReplayReverseAsync(message); } } [HttpPost] [Route(nameof(Simple))] public async Task Simple() { string message = null!; await foreach (var item in ReadMessageAsync(HttpContext.RequestAborted)) { message = item; } DisplayReceivedMessage(message); await ReplayReverseAsync(message); } private async Task ReplayAsync(string message) { if (!Response.HasStarted) { Response.Headers.ContentType = "application/grpc"; Response.AppendTrailer("grpc-status", "0"); await Response.StartAsync(); } await Response.Body.WriteAsync(TempMessageCodecUtil.BuildMessage(message)); } private Task ReplayReverseAsync(string rawMessage) => ReplayAsync(new string(rawMessage.Reverse().ToArray())); //省略其他信息}最后记得 services.AddControllers() 和 app.MapControllers() 并取消Grpc的ServiceMap；
此时分别使用 Controller 和 GrpcService 运行服务端，并查看客户端日志，可以看到运行结果相同，如图：
HttpClient 实现能够与 Grpc Server 交互的客户端在上面我们已经使用原生 Controller 实现了一个可以让客户端正常运行的服务端，现在我们不使用 Grpc SDK 来实现一个可以和服务端交互的客户端。
HttpClient 没有直接获取请求流的办法，我们需要从 HttpContent 的 SerializeToStreamAsync 方法中获取到真正的请求流。具体细节不在这里赘述，直接上代码：class LongAliveHttpContent : HttpContent{ private readonly TaskCompletionSource<Stream> _streamGetCompletionSource = new(TaskCreationOptions.RunContinuationsAsynchronously); private readonly TaskCompletionSource _taskCompletionSource = new(TaskCreationOptions.RunContinuationsAsynchronously); public LongAliveHttpContent() { Headers.ContentType = new MediaTypeHeaderValue("application/grpc"); } protected override Task SerializeToStreamAsync(Stream stream, TransportContext? context) { _streamGetCompletionSource.SetResult(stream); return _taskCompletionSource.Task; } protected override bool TryComputeLength(out long length) { length = -1; return false; } public void Complete() { _taskCompletionSource.TrySetResult(); } public Task<Stream> GetStreamAsync() { return _streamGetCompletionSource.Task; }} - 请求的协议使用的是 `HTTP/2`； - 方法都为 `POST`； - 所有grpc方法都映射到了对应的终结点 `/{package名}.{service名}/{方法名}`； - 请求&响应的 `ContentType` 都为 `application/grpc`；直接上代码，使用 HttpClient 发起请求，并获取 请求流 & 响应流：
private static (Task<Stream> RequestStreamGetTask, Task<Stream> ResponseStreamGetTask, LongAliveHttpContent HttpContent) CreateStreamGetTasksAsync(HttpClient client, string path){ var content = new LongAliveHttpContent(); var httpRequestMessage = new HttpRequestMessage() { Method = HttpMethod.Post, RequestUri = new Uri(path, UriKind.Relative), Content = content, Version = HttpVersion.Version20, VersionPolicy = HttpVersionPolicy.RequestVersionExact, }; var responseStreamGetTask = client.SendAsync(httpRequestMessage, HttpCompletionOption.ResponseHeadersRead) .ContinueWith(m => m.Result.Content.ReadAsStreamAsync()) .Unwrap(); return (content.GetStreamAsync(), responseStreamGetTask, content);}Grpc客户端相同的执行逻辑。代码如下：private static async Task BidirectionalWithOutSDK(HttpClient client){ var (requestStreamGetTask, responseStreamGetTask, httpContent) = CreateStreamGetTasksAsync(client, "reverse.Reverse/Bidirectional"); var requestStream = await requestStreamGetTask; var sendTask = Task.Run(async () => { for (int i = 0; i < 10; i++) { await requestStream.WriteAsync(TempMessageCodecUtil.BuildMessage($"{nameof(Bidirectional)}-{i}")); } httpContent.Complete(); }); var receiveTask = DisplayReceivedMessageAsync(responseStreamGetTask); await Task.WhenAll(sendTask, receiveTask);}private static async Task ClientSideWithOutSDK(HttpClient client){ var (requestStreamGetTask, responseStreamGetTask, httpContent) = CreateStreamGetTasksAsync(client, "reverse.Reverse/ClientSide"); var requestStream = await requestStreamGetTask; for (int i = 0; i < 5; i++) { await requestStream.WriteAsync(TempMessageCodecUtil.BuildMessage($"{nameof(ClientSide)}-{i}")); await requestStream.FlushAsync(); } httpContent.Complete(); await DisplayReceivedMessageAsync(responseStreamGetTask);}private static async Task SampleWithOutSDK(HttpClient client){ var (requestStreamGetTask, responseStreamGetTask, httpContent) = CreateStreamGetTasksAsync(client, "reverse.Reverse/Simple"); var requestStream = await requestStreamGetTask; await requestStream.WriteAsync(TempMessageCodecUtil.BuildMessage(nameof(Sample))); httpContent.Complete(); await DisplayReceivedMessageAsync(responseStreamGetTask);}private static async Task ServerSideWithOutSDK(HttpClient client){ var (requestStreamGetTask, responseStreamGetTask, httpContent) = CreateStreamGetTasksAsync(client, "reverse.Reverse/ServerSide"); var requestStream = await requestStreamGetTask; await requestStream.WriteAsync(TempMessageCodecUtil.BuildMessage(nameof(ServerSide))); httpContent.Complete(); await DisplayReceivedMessageAsync(responseStreamGetTask);}此时分别进行如下测试：
GrpcService 运行服务端，并分别使用sdk客户端和HttpClient客户端进行请求；Controller 运行服务端，并分别使用sdk客户端和HttpClient客户端进行请求；可以看到客户端运行结果相同，如下：
Sample Received: elpmaSClientSide Received: ServerSide Received Over. Total: 5ServerSide Received: ediSrevreSServerSide Received: ediSrevreSServerSide Received: ediSrevreSServerSide Received: ediSrevreSServerSide Received: ediSrevreSBidirectional Received: 0-lanoitceridiBBidirectional Received: 1-lanoitceridiBBidirectional Received: 2-lanoitceridiBBidirectional Received: 3-lanoitceridiBBidirectional Received: 4-lanoitceridiBBidirectional Received: 5-lanoitceridiBBidirectional Received: 6-lanoitceridiBBidirectional Received: 7-lanoitceridiBBidirectional Received: 8-lanoitceridiBBidirectional Received: 9-lanoitceridiB ----------------- WithOutSDK -----------------SampleWithOutSDK Received: elpmaSClientSideWithOutSDK Received: ServerSide Received Over. Total: 5ServerSideWithOutSDK Received: ediSrevreSServerSideWithOutSDK Received: ediSrevreSServerSideWithOutSDK Received: ediSrevreSServerSideWithOutSDK Received: ediSrevreSServerSideWithOutSDK Received: ediSrevreSBidirectionalWithOutSDK Received: 0-lanoitceridiBBidirectionalWithOutSDK Received: 1-lanoitceridiBBidirectionalWithOutSDK Received: 2-lanoitceridiBBidirectionalWithOutSDK Received: 3-lanoitceridiBBidirectionalWithOutSDK Received: 4-lanoitceridiBBidirectionalWithOutSDK Received: 5-lanoitceridiBBidirectionalWithOutSDK Received: 6-lanoitceridiBBidirectionalWithOutSDK Received: 7-lanoitceridiBBidirectionalWithOutSDK Received: 8-lanoitceridiBBidirectionalWithOutSDK Received: 9-lanoitceridiB至此，我们稍作分析和总结，可以得出结论：
Grpc 所有类型的方法调用都是普通的Http请求，只是请求和响应的内容是经过 Protobuf 编码的数据；我们再稍作拓展，可以得出更多结论：
多路复用、Header压缩 什么的，都是 Http2 带来的优化，不是和 Grpc 绑定的，使用 Http2 访问常规 WebAPI 也能享受到其带来的好处；Grpc 的 Unary 请求模式和和 WebAPI 逻辑是一样的；Server streaming、Client streaming 请求模式都可以通过 Http1.1 进行实现（但不能多路复用，每个请求会独占一个连接）；Bidirectional streaming 是基于 二进制分帧 的，只能在 Http2 及以上版本实现双向流通讯；基于以上结论，我们总结一下 Grpc 比 WebAPI 的优势在哪里：
Protobuf 基于二进制的编码，在数据量较多时，比 json 这种基于文本的编码效率更高；但丢失了直接的可阅读性；（没做性能测试，理论是这样，如果性能打不过 json 的话，那就没有存在价值了。理论上数据量越大，性能差距越大）json 因为要自我描述，所有字段都有名字，在序列化 List 时这种浪费就比较多了，重复对象越多，浪费越多（但可阅读性也是这样来的）；Protobuf 没有这方面的浪费，还有一些其它的优化，参见 protocol-buffers-encoding；proto 文件直接生成服务端和客户端，上手更快，跨语言也能快速生成客户端（这点其实见仁见智，WebAPI 也有类似的工具）;Grpc 比传统 WebAPI 的劣势有哪些呢：
Grpc 的消息内容是没法直接阅读的；HTTP2 强绑定；WebAPI 可以在低版本协议下运行，某些时候会方便一点；Grpc SDK；虽然 Grpc SDK 已经覆盖了很多主流语言，但如果恰好某个需求要使用的语言没有SDK，那就有点麻烦了；相比之下基于文本的 WebAPI 会更通用一点；Protobuf 要求严格的格式，字段增删最后再基于结论，总结一些我认为有问题的 grpc 使用方法吧：
grpc 当作一个封包/拆包工具；在消息体中放一个 json 之类的东西，拿到消息之后在反序列化一次。。。这又是何必呢。。。直接基于原生 Http 写一个 基于消息头指定消息长度 的分包逻辑并花不了多少工作量，也不会额外引入grpc的相关东西；这个用法也和 grpc 的 高性能 背道而驰，还多了一层 序列化/反序列化 操作；（我在这里没有说nacos）grpc 调用就是 Http 请求，那么 Header 的工作逻辑是和 WebAPI 完全一样的；那么 grpc 请求完全可以使用现有的 Http 认证 和 Header处理 代码甚至请求管道；额外再自定义消息实现相关功能不是多此一举吗？（我在这里也没有说nacos）综上，个人认为，不是别人说 grpc 高性能，就认为它碾压传统 WebAPI，就去用它；还是需要了解原理后好好考虑的，确认它能否为你带来理想的效果；有时候或许自己手写一个变体的 Http 请求处理逻辑能更快更好的满足需求；
如果有闲心的话，理论上甚至可以做下列的玩具：
WebAPI 的 grpc 兼容层，使 Controller 既能以 grpc 工作又能处理普通请求；通过 Controller 定义，反向生成 DTO 的 proto 消息定义，以及整个service的 proto 定义；grpc 的 WebAPI 兼容层，使 grpc 服务能工作的像 Controller 一样，对外输入输出 json；