上一篇博文中说到Prometheus有四种指标类型：Counter（计数器）、Gauge（仪表盘）、Histogram（直方图）、Summary（摘要），并且我们做了一个Counter的Demo，接下来看看Histogram。

3、Histogram：直方图

直方图，维基百科的定义：是一种对数据分布情况的图形表示，是一种二维统计图表，它的两个坐标分别是统计样本和该样本对应的某个属性的度量，以长条图（bar）的形式具体表现。因为直方图的长度及宽度很适合用来表现数量上的变化，所以较容易解读差异小的数值。

还是拿上一篇的Sample来说明，假如每个订单都有一个金额，在order时在返回值{result=true,data=1000}的data属性中返回，这里，我们就可以用直方图来收集这个金额，由于订单的金额不一样，我们就可以用直方图来展示一定范围金额内订单的数据，监控出一定金额范围内的订单比例了。就是说在一定数量的订单里，少于1000元的有多少个订单，少于2000元有多少个订单，少于3000元的有多少个订单……

首先，我们得修改BusinessController中Order Action的业务逻辑，把订单金额作为返回值：

[HttpGet("/order")]public IActionResult Order(string orderno){try{_logger.LogInformation("下单");//返回订单金额var random = new Random();return new JsonResult(new { Result = true, data = random.Next(1, 8000) });}catch (Exception exc){_logger.LogCritical(exc, exc.Message);return new JsonResult(new{Result = false,Message = exc.Message});}}

这里的金额为了方便demo，是随机生成一个1到8000的随机数。

需要在MetricsHub.cs中添加Histogram类型的指标收集集合：

using Prometheus;
using System.Collections.Generic;namespace PrometheusSample.Middlewares
{public class MetricsHub{private static Dictionary<string, Counter> _counterDictionary = new Dictionary<string, Counter>();private static Dictionary<string, Dictionary<string, Gauge>> _gaugeDictionary = new Dictionary<string, Dictionary<string, Gauge>>();private static Dictionary<string, Histogram> _histogramDictionary = new Dictionary<string, Histogram>();public Counter GetCounter(string key){if (_counterDictionary.ContainsKey(key)){return _counterDictionary[key];}else{return null;}}public Dictionary<string, Gauge> GetGauge(string key){if (_gaugeDictionary.ContainsKey(key)){return _gaugeDictionary[key];}else{return null;}}public Histogram GetHistogram(string key){if (_histogramDictionary.ContainsKey(key)){return _histogramDictionary[key];}else{return null;}}public void AddCounter(string key, Counter counter){_counterDictionary.Add(key, counter);}public void AddGauge(string key, Dictionary<string, Gauge> gauges){_gaugeDictionary.Add(key, gauges);}   public void AddHistogram(string key, Histogram histogram){_histogramDictionary.Add(key, histogram);}}
}

接下来就要在BusinessMetricsMiddleware的中间件中添加处理Histogram指标的代码了：

using Microsoft.AspNetCore.Http;
using PrometheusSample.Models;
using System.IO;
using System.Threading.Tasks;namespace PrometheusSample.Middlewares
{/// <summary>/// 请求记录中间件/// </summary>public class BusinessMetricsMiddleware{private readonly RequestDelegate _next;public BusinessMetricsMiddleware(RequestDelegate next){_next = next;}public async Task InvokeAsync(HttpContext context, MetricsHub metricsHub){var originalBody = context.Response.Body;try{using (var memStream = new MemoryStream()){//从管理返回的Response中取出返回数据，根据返回值进行监控指标计数context.Response.Body = memStream;await _next(context);memStream.Position = 0;string responseBody = new StreamReader(memStream).ReadToEnd();memStream.Position = 0;await memStream.CopyToAsync(originalBody);if (metricsHub.GetCounter(context.Request.Path) != null || metricsHub.GetGauge(context.Request.Path) != null){//这里约定所有action返回值是一个APIResult类型var result = System.Text.Json.JsonSerializer.Deserialize<APIResult>(responseBody, new System.Text.Json.JsonSerializerOptions { PropertyNameCaseInsensitive = true });if (result != null && result.Result){//获取到Countervar counter = metricsHub.GetCounter(context.Request.Path);if (counter != null){//计数counter.Inc();}var gauges = metricsHub.GetGauge(context.Request.Path);if (gauges != null){//存在增加指标+就Incif (gauges.ContainsKey("+")){gauges["+"].Inc();} //存在减少指标-就Decif (gauges.ContainsKey("-")){gauges["-"].Dec();}}var histogram = metricsHub.GetHistogram(context.Request.Path);if (histogram != null){var parseResult = int.TryParse(result.Data.ToString(), out int i);if (parseResult){histogram.Observe(i);}}}}}}finally{context.Response.Body = originalBody;}}}
}

再就是在Starsup中配置对应url的Histogram参数了：

using Microsoft.AspNetCore.Builder;
using Microsoft.AspNetCore.Hosting;
using Microsoft.Extensions.Configuration;
using Microsoft.Extensions.DependencyInjection;
using Microsoft.Extensions.Hosting;
using Microsoft.OpenApi.Models;
using Prometheus;
using PrometheusSample.Middlewares;
using PrometheusSample.Services;using System.Collections.Generic;namespace PrometheusSample
{public class Startup{public Startup(IConfiguration configuration){Configuration = configuration;}public IConfiguration Configuration { get; }public void ConfigureServices(IServiceCollection services){MetricsHandle(services);services.AddScoped<IOrderService, OrderService>();services.AddControllers();services.AddSwaggerGen(c =>{c.SwaggerDoc("v1", new OpenApiInfo { Title = "PrometheusSample", Version = "v1" });});}public void Configure(IApplicationBuilder app, IWebHostEnvironment env){if (env.IsDevelopment()){app.UseDeveloperExceptionPage();app.UseSwagger();app.UseSwaggerUI(c => c.SwaggerEndpoint("/swagger/v1/swagger.json", "PrometheusSample v1"));}app.UseRouting();//http请求的中间件app.UseHttpMetrics();app.UseAuthorization();//自定义业务跟踪app.UseBusinessMetrics();app.UseEndpoints(endpoints =>{//映射监控地址为  /metricsendpoints.MapMetrics();endpoints.MapControllers();});}/// <summary>/// 处理监控事项/// </summary>/// <param name="services"></param>void MetricsHandle(IServiceCollection services){var metricsHub = new MetricsHub();//countermetricsHub.AddCounter("/register", Metrics.CreateCounter("business_register_user", "注册用户数。"));metricsHub.AddCounter("/order", Metrics.CreateCounter("business_order_total", "下单总数。"));metricsHub.AddCounter("/pay", Metrics.CreateCounter("business_pay_total", "支付总数。"));metricsHub.AddCounter("/ship", Metrics.CreateCounter("business_ship_total", "发货总数。"));//gaugevar orderGauge = Metrics.CreateGauge("business_order_count", "当前下单数量。");var payGauge = Metrics.CreateGauge("business_pay_count", "当前支付数量。");var shipGauge = Metrics.CreateGauge("business_ship_count", "当前发货数据。");metricsHub.AddGauge("/order", new Dictionary<string, Gauge> {{ "+", orderGauge}});metricsHub.AddGauge("/pay", new Dictionary<string, Gauge> {{"-",orderGauge},{"+",payGauge}});metricsHub.AddGauge("/ship", new Dictionary<string, Gauge> {{"+",shipGauge},{"-",payGauge}});         //histogram           var orderHistogram = Metrics.CreateHistogram("business_order_histogram", "订单直方图。",new HistogramConfiguration{Buckets = Histogram.LinearBuckets(start: 1000, width: 1000, count: 5)});metricsHub.AddHistogram("/order", orderHistogram);services.AddSingleton(metricsHub);}}
}

Histogram.LinearBuckets(start: 1000, width: 1000, count: 5)是金额从1000开始，每1000为一个台阶，一共6个台阶：0~1000，1001~2000，2001~3000，3001~4000，4001~5000，还有一个是大于5000的。

最后一步，就是打开Grafana来配置展示图表了。

订单金额分布图

订单比例分布图

图中histogram_quantile(0.80, sum(rate(business_order_histogram_bucket[5m])) by (le))的意思是“80%的订单金额小于等于这个值”5分钟内的值。

最终展示结果：

聪明的你一定发现，这篇博文与上一篇如出一辙，是的，只是监控指标展示类型不同而以。