简单回顾asp.net core中如何使用

遥测数据分为链路、指标和日志 ，dotnet中使用可参考OpenTelemetry文档

简单的示例

using Microsoft.Extensions.Options;

using OpenTelemetry;

using OpenTelemetry.Resources;

using OpenTelemetry.Trace;

Environment.SetEnvironmentVariable("OTEL_EXPORTER_OTLP_ENDPOINT", "http://127.0.0.1:4317/"); // 配置OpenTelemetry收集器

var builder = WebApplication.CreateBuilder(args);

// Add services to the container.

builder.Services.AddControllers();

// Learn more about configuring OpenAPI at https://aka.ms/aspnet/openapi

builder.Services.AddOpenApi();

builder.Services.AddOpenTelemetry()

.ConfigureResource(resource => resource.AddService("TestApi", "").AddContainerDetector())

.WithTracing(tracing => tracing.AddAspNetCoreInstrumentation())

.WithMetrics(builder =>

{

builder.AddMeter("System.Runtime", "Microsoft.AspNetCore.Server.Kestrel", "Microsoft.AspNetCore.MemoryPool");

})

.WithLogging()

.UseOtlpExporter(); // 示例使用 Otlp协议

var app = builder.Build();

// Configure the HTTP request pipeline.

if (app.Environment.IsDevelopment())

{

app.MapOpenApi();

}

app.UseHttpsRedirection();

app.UseAuthorization();

app.MapControllers();

app.Run();

日志

这个其实没什么特别，由于已经提供非常抽象的 ILogger， 所以只需大家按照自己记录log所需正常使用就好，

log 大家使用非常多，这里就不详细示例了，可参考文档Logging in .NET and ASP.NET Core

而OpenTelemetry 对于log，主要是如何在log 结构化并记录分布式追踪的信息，以方便关联。

OpenTelemetry sdk 已经内置支持，只需配置好 .WithLogging()，对应log和分布式追踪的信息都会写入收集器中。

指标

dotnet 中已提供统一的抽象 Meter， 大家不必再关注是为 Prometheus 还是其他方案提供对应性能指标方案

详细文档可参考ASP.NET Core 指标 和 ASP.NET 核心内置指标

这里举个简单例子说明 如何自定义指标

public class ProxyMetrics

{

private readonly Meter? metrics;

private readonly Counter? requestsCounter;

private readonly Histogram? requestDuration;

public ProxyMetrics(IMeterFactory meterFactory)

{

var f = serviceProvider.GetService();

metrics = f == null ? null : f.Create("VKProxy.ReverseProxy");

if (metrics != null)

{

// 计数器

requestsCounter = metrics.CreateCounter("vkproxy.requests", unit: "{request}", "Total number of (HTTP/tcp/udp) requests processed by the reverse proxy.");

// 直方图

requestDuration = metrics.CreateHistogram(

"vkproxy.request.duration",

unit: "s",

description: "Proxy handle duration of (HTTP/tcp/udp) requests.",

advice: new InstrumentAdvice { HistogramBucketBoundaries = [0.01, 0.02, 0.05, 0.1, 0.2, 0.5, 1, 2, 5, 10, 30, 60, 120, 300] });

}

}

public void ProxyBegin(IReverseProxyFeature feature) // 在请求开始调用

{

string routeId = GetRouteId(feature);

GeneralLog.ProxyBegin(generalLogger, routeId);

if (requestsCounter != null && requestsCounter.Enabled)

{

var tags = new TagList

{

{ "route", routeId } // 设置 指标 tag，让其粒度到 route 级别

};

requestsCounter.Add(1, in tags); // +1 记录总共接受了多少个请求

}

}

public void ProxyEnd(IReverseProxyFeature feature) // 在请求结束调用

{

string routeId = GetRouteId(feature);

GeneralLog.ProxyEnd(generalLogger, routeId);

if (requestDuration != null && requestDuration.Enabled)

{

var endTimestamp = Stopwatch.GetTimestamp();

var t = Stopwatch.GetElapsedTime(feature.StartTimestamp, endTimestamp);

var tags = new TagList

{

{ "route", routeId } // 设置 指标 tag，让其粒度到 route 级别

};

requestDuration.Record(t.TotalSeconds, in tags); // 记录请求耗时

}

}

}

接着在 Program.cs 中向 DI 注册指标类型：

var builder = WebApplication.CreateBuilder(args);

builder.Services.AddSingleton();

然后在具体地方使用

private async Task DoHttp(HttpContext context, ListenEndPointOptions? options)

{

try

{

logger.ProxyBegin(proxyFeature);

///......

}

finally

{

logger.ProxyEnd(proxyFeature);

}

}

链路

对于分布式链路追踪，其实dotnet现在已有内置抽象 Activity

这里举个简单例子说明 如何自定义链路

在 Program.cs 中向 DI 注册指标类型：

var builder = WebApplication.CreateBuilder(args);

builder.Services.TryAddSingleton(sp => new ActivitySource("VKProxy"));

builder.Services.TryAddSingleton(DistributedContextPropagator.Current);

使用 Activity 埋点信息

internal class ListenHandler : ListenHandlerBase

{

internal const string ActivityName = "VKProxy.ReverseProxy";

private readonly DistributedContextPropagator propagator;

private readonly ActivitySource activitySource;

public ListenHandler(...,

DistributedContextPropagator propagator, ActivitySource activitySource)

{

this.propagator = propagator;

this.activitySource = activitySource;

}

private async Task DoHttp(HttpContext context, ListenEndPointOptions? options)

{

Activity activity;

if (activitySource.HasListeners())

{

var headers = context.Request.Headers;

Activity.Current = activity = ActivityCreator.CreateFromRemote(activitySource, propagator, headers,

static (object? carrier, string fieldName, out string? fieldValue, out IEnumerable? fieldValues) =>

{

fieldValues = default;

var headers = (IHeaderDictionary)carrier!;

fieldValue = headers[fieldName];

},

ActivityName,

ActivityKind.Server,

tags: null,

links: null, false);

}

else

{

activity = null;

}

if (activity != null)

{

activity.Start();

context.Features.Set(new HttpActivityFeature(activity));

context.Features.Set(new HttpMetricsTagsFeature()

{

Method = context.Request.Method,

Protocol = context.Request.Protocol,

Scheme = context.Request.Scheme,

MetricsDisabled = true,

});

activity.DisplayName = $"{context.Request.Method} {context.Request.Path.Value}";

activity.SetTag("http.request.method", context.Request.Method);

activity.SetTag("network.protocol.name", "http");

activity.SetTag("url.scheme", context.Request.Scheme);

activity.SetTag("url.path", context.Request.Path.Value);

activity.SetTag("url.query", context.Request.QueryString.Value);

if (ProtocolHelper.TryGetHttpVersion(context.Request.Protocol, out var httpVersion))

{

activity.SetTag("network.protocol.version", httpVersion);

}

activity.SetTag("http.request.host", context.Request.Host);

activity.SetTag("http.request.content_type", context.Request.ContentType);

var l = context.Request.ContentLength;

if (l.HasValue)

activity.SetTag("http.request.content_length", l.Value);

}

try

{

logger.ProxyBegin(proxyFeature);

///......

}

finally

{

if (activity != null)

{

var statusCode = context.Response.StatusCode;

activity.SetTag("http.response.status_code", statusCode);

activity.Stop();

Activity.Current = null;

}

logger.ProxyEnd(proxyFeature);

}

}

仪表盘

遥测数据收集到哪儿，用什么展示，业界有各种方案， 比如

将 OpenTelemetry 与 OTLP 和独立 Aspire 仪表板配合使用

将 OpenTelemetry 与 Prometheus、Grafana 和 Jaeger 结合使用

将 OpenTelemetry 与 SkyWalking ui 结合使用

等等

大家可以根据自己喜好和实际选择

不过对应效果大致如 Aspire 一般

aspire-dashboard

在VKProxy中如何使用？

默认情况，OpenTelemetry 已经启用，并且配置为 otlp 协议，大家只需配置otlp收集器，

相关配置如下：

Environment variable OtlpExporterOptions property

OTEL_EXPORTER_OTLP_ENDPOINT Endpoint

OTEL_EXPORTER_OTLP_HEADERS Headers

OTEL_EXPORTER_OTLP_TIMEOUT TimeoutMilliseconds

OTEL_EXPORTER_OTLP_PROTOCOL Protocol (grpc or http/protobuf)

(更多详细配置参见OpenTelemetry.Exporter.OpenTelemetryProtocol)

这里我们用 Aspire 仪表盘举例

因为它有个独立模式，只需启动一个镜像就可以尝试一下，当然真实产线还是需要配置其他存储等等

docker run --rm -it -p 18888:18888 -p 4317:18889 -d --name aspire-dashboard \

mcr.microsoft.com/dotnet/aspire-dashboard:9.0

前面的 Docker 命令：

从 mcr.microsoft.com/dotnet/aspire-dashboard:9.0 映像启动容器。

公开两个端口的容器实例：

将仪表板的 OTLP 端口 18889 映射到主机的端口 4317。 端口 4317 从应用接收 OpenTelemetry 数据。 应用使用 OpenTelemetry 协议 （OTLP）发送数据。

将仪表板的端口 18888 映射到主机的端口 18888。 端口 18888 具有仪表板 UI。 导航到浏览器中 http://localhost:18888 以查看仪表板。

// 设置收集器环境变量

set OTEL_EXPORTER_OTLP_ENDPOINT=http://127.0.0.1:4317/

// 启动vkproxy （具体配置可参见之前的性能测试 https://www.cnblogs.com/fs7744/p/18978275 ）

vkproxy proxy -c D:\code\github\VKProxy\samples\CoreDemo\test.json

访问一下

curl --location 'https://localhost:5001/WeatherForecast'

可以在 Aspire 中看到相关链路信息

tracing

指标信息

meters

日志信息

logs

当然你还可以通多如下命令调整过滤记录的信息

--telemetry (Environment:VKPROXY_TELEMETRY)

Allow export telemetry data (metrics, logs, and traces) to help you analyze your software’s performance and behavior.

--meter (Environment:VKPROXY_TELEMETRY_METER)

Subscribe meters, default is System.Runtime,Microsoft.AspNetCore.Server.Kestrel,Microsoft.AspNetCore.Server.Kestrel.Udp,Microsoft.AspNetCore.MemoryPool,VKProxy.ReverseProxy

--drop_instrument (Environment:VKPROXY_TELEMETRY_DROP_INSTRUMENT)

Drop instruments

--exporter (Environment:VKPROXY_TELEMETRY_EXPORTER)

How to export telemetry data (metrics, logs, and traces), support prometheus,console,otlp , default is otlp, please set env like `OTEL_EXPORTER_OTLP_ENDPOINT=http://127.0.0.1:4317/`

测一测性能

.\vegeta.exe attack -insecure -rate=10000/s -duration=60s -format=http -targets=http2proxy -output=http2proxyresults -http2

// http2proxy content:

// GET https://127.0.0.1:5001/WeatherForecast

HTTP2

http2plot

汇总

Requests [total, rate, throughput] 599999, 10000.94, 9992.64

Duration [total, attack, wait] 59.994s, 59.994s, 0s

Latencies [min, mean, 50, 90, 95, 99, max] 0s, 3.428ms, 2.015ms, 5.405ms, 6.882ms, 32.941ms, 301.44ms

Bytes In [total, mean] 231889817, 386.48

Bytes Out [total, mean] 0, 0.00

Success [ratio] 99.92%

Status Codes [code:count] 0:498 200:599501

Error Set:

Get "https://127.0.0.1:5001/WeatherForecast": dial tcp 0.0.0.0:0->127.0.0.1:5001: connectex: No connection could be made because the target machine actively refused it.

之前没有遥测的性能测试汇总

Requests [total, rate, throughput] 599930, 9998.35, 9998.35

Duration [total, attack, wait] 1m0s, 1m0s, 0s

Latencies [min, mean, 50, 90, 95, 99, max] 0s, 676.024μs, 0s, 2.56ms, 3.705ms, 5.367ms, 26.437ms

Bytes In [total, mean] 232052167, 386.80

Bytes Out [total, mean] 0, 0.00

Success [ratio] 100.00%

Status Codes [code:count] 200:599930

Error Set:

对比之前的测试而言，的确 otlp 遥测对性能有了不小的影响，但这点消耗单次请求看，消耗还是很低微的，总体利大于弊

VKProxy 是使用c#开发的基于 Kestrel 实现 L4/L7的代理（感兴趣的同学烦请点个github小赞赞呢）