VKProxy 集成 OpenTelemetry

枢覆引 · 2025-9-28 12:20:26

OpenTelemetry

OpenTelemetry 是各类 API、SDK 和工具形成的集合。可用于插桩、生成、采集和导出遥测数据（链路、指标和日志），帮助你分析软件的性能和行为。

VKProxy 已集成OpenTelemetry，所以现在可以非常简单采集和导出遥测数据（链路、指标和日志）。
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();

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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<long>? requestsCounter;
private readonly Histogram<double>? requestDuration;
public ProxyMetrics(IMeterFactory meterFactory)
{
var f = serviceProvider.GetService<IMeterFactory>();
metrics = f == null ? null : f.Create("VKProxy.ReverseProxy");
if (metrics != null)
{
// 计数器
requestsCounter = metrics.CreateCounter<long>("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<double> { 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
}
}
}

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接着在 Program.cs 中向 DI 注册指标类型：

var builder = WebApplication.CreateBuilder(args);
builder.Services.AddSingleton<ProxyMetrics>();

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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);
}
}

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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);

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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<string>? 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<IHttpActivityFeature>(new HttpActivityFeature(activity));
context.Features.Set<IHttpMetricsTagsFeature>(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);
}
}

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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

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 variableOtlpExporterOptions propertyOTEL_EXPORTER_OTLP_ENDPOINTEndpointOTEL_EXPORTER_OTLP_HEADERSHeadersOTEL_EXPORTER_OTLP_TIMEOUTTimeoutMillisecondsOTEL_EXPORTER_OTLP_PROTOCOLProtocol (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

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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

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访问一下

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

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可以在 Aspire 中看到相关链路信息

指标信息

日志信息

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/`

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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

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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.

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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:

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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）

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