大家一般都是用Grafana自定义Dashboard来监控Prometheus数据的，作者这次尝试用ECharts来绘制Prometheus数据图表，一方面可以减少依赖，另一方面可以将监控界面灵活的集成进应用系统。至于如何在被监测机器上安装NodeExporter以及如何部署Prometheus作者就不描述了，园子里有很多文章介绍。

一、数据查询及转换

  Prometheus提供了Http Api来执行promql查询，但需要将返回的数据格式转换为ECharts的格式，好在EChars的xAxis.type可以设置为'time'类型，与Prometheus返回的格式接近。作者写了个简单的服务来执行查询及转换数据，详见以下代码：

public class MetricService
{
private static readonly HttpClient http = new HttpClient()
{
//请修改指向Prometheus地址
BaseAddress = new Uri("http://10.211.55.2:9090/api/v1/"),
Timeout = TimeSpan.FromSeconds(2)
};

public async Task<object> GetCpuUsages(string node, DateTime start, DateTime end)
{
var promql = $"100-irate(node_cpu{{instance='{node}:9100',mode='idle'}}[5m])*100";
return await QueryRange(promql, start, end, 20, 2);
}

public async Task<object> GetMemUsages(string node, DateTime start, DateTime end)
{
var promql = $"(1-(node_memory_MemAvailable{{instance='{node}:9100'}}/(node_memory_MemTotal{{instance='{node}:9100'}})))*100";
return await QueryRange(promql, start, end, 20, 2);
}

public async Task<object> GetNetTraffic(string node, DateTime start, DateTime end)
{
var downql = $"irate(node_network_receive_bytes{{instance='{node}:9100',device!~'tap.*|veth.*|br.*|docker.*|virbr*|lo*'}}[5m])";
var ls = await QueryRange(downql, start, end, 15/*4*/, 0);
var upql = $"irate(node_network_transmit_bytes{{instance='{node}:9100',device!~'tap.*|veth.*|br.*|docker.*|virbr*|lo*'}}[5m])";
ls.Add(await QueryRange(upql, start, end, 15/*4*/, 0));
return ls;
}

public async Task<object> GetDiskIO(string node, DateTime start, DateTime end)
{
var readql = $"irate(node_disk_bytes_read{{instance='{node}:9100'}}[1m])";
var ls = await QueryRange(readql, start, end, 15/*10*/, 0);
var writeql = $"irate(node_disk_bytes_written{{instance='{node}:9100'}}[1m])";
ls.Add(await QueryRange(writeql, start, end, 15/*10*/, 0));
return ls;
}

#region ====Parse PromQL====
private static async Task<List<object>> QueryRange(string promql, DateTime start, DateTime end, int step, int round)
{
if (start >= end) throw new ArgumentOutOfRangeException();
var ts1 = (int)(start.ToUniversalTime() - DateTime.UnixEpoch).TotalSeconds;
var ts2 = (int)(end.ToUniversalTime() - DateTime.UnixEpoch).TotalSeconds;
var res = await http.GetAsync($"query_range?query={promql}&start={ts1}&end={ts2}&step={step}s");
var stream = await res.Content.ReadAsStreamAsync();
using (var sr = new System.IO.StreamReader(stream))
using (var jr = new JsonTextReader(sr))
{
return ParseToSeries(jr, round);
}
}

private static List<object> ParseToSeries(JsonTextReader jr, int round)
{
if (!jr.Read() || jr.TokenType != JsonToken.StartObject) throw new Exception();
if (!jr.Read() || jr.TokenType != JsonToken.PropertyName || (string)jr.Value != "status")
throw new Exception();
var status = jr.ReadAsString();
if (status != "success") throw new Exception();
if (!jr.Read() || jr.TokenType != JsonToken.PropertyName || (string)jr.Value != "data")
throw new Exception();

if (!jr.Read() || jr.TokenType != JsonToken.StartObject) throw new Exception();
if (!jr.Read() || jr.TokenType != JsonToken.PropertyName || (string)jr.Value != "resultType")
throw new Exception();
var resultType = jr.ReadAsString();
if (!jr.Read() || jr.TokenType != JsonToken.PropertyName || (string)jr.Value != "result")
throw new Exception();

return ReadResultArray(jr, round);
//No need read others
}

private static List<object> ReadResultArray(JsonTextReader jr, int round)
{
if (!jr.Read() || jr.TokenType != JsonToken.StartArray) throw new Exception();

var ls = new List<object>();
do
{
if (!jr.Read()) throw new Exception();
if (jr.TokenType == JsonToken.EndArray) break;
if (jr.TokenType != JsonToken.StartObject) throw new Exception();
ls.Add(ReadResultItem(jr, round));
} while (true);
return ls;
}

private static List<double[]> ReadResultItem(JsonTextReader jr, int round)
{
//已读取StartObject标记
if (!jr.Read() || jr.TokenType != JsonToken.PropertyName || (string)jr.Value != "metric")
throw new Exception();
ReadMetric(jr);

if (!jr.Read() || jr.TokenType != JsonToken.PropertyName || (string)jr.Value != "values")
throw new Exception();
var values = ReadValues(jr, round);
if (!jr.Read() || jr.TokenType != JsonToken.EndObject) throw new Exception();
return values;
}

private static void ReadMetric(JsonTextReader jr)
{
if (!jr.Read() || jr.TokenType != JsonToken.StartObject) throw new Exception();
do
{
//PropertyName or EndObject
if (!jr.Read()) throw new Exception();
if (jr.TokenType == JsonToken.EndObject) return;
//PropertyValue
jr.Read();
} while (true);
}

private static List<double[]> ReadValues(JsonTextReader jr, int round)
{
if (!jr.Read() || jr.TokenType != JsonToken.StartArray) throw new Exception();

var ls = new List<double[]>();
do
{
if (!jr.Read()) throw new Exception();
if (jr.TokenType == JsonToken.EndArray) break;
if (jr.TokenType != JsonToken.StartArray) throw new Exception();
var ts = jr.ReadAsDouble().Value * 1000; //PromQL时间*1000
var value = Math.Round(double.Parse(jr.ReadAsString()), round, MidpointRounding.ToEven); //PromQL值为字符串
ls.Add(new double[] { ts, value });
if (!jr.Read() || jr.TokenType != JsonToken.EndArray) throw new Exception();
} while (true);
return ls;
}
#endregion

}

二、单指标Vue组件

  作者使用Vue-ECharts作为ECharts的包装，以CPU使用率Vue组件为例：

<v-chart theme="dark" autoresize :options="chartOptions" style="height:250px">
</v-chart>

@Component
export default class CpuUsages extends Vue {
/** 目标实例IP */
@Prop({ type: String, default: '10.211.55.3' }) node
/** 开始时间 */
@Prop({ type: Date, default: () => { var now = new Date(); return new Date(now.getFullYear(), now.getMonth(), now.getDate()) } }) start
/** 结束时间 */
@Prop({ type: Date, default: () => { return new Date() } }) end

chartOptions = {
title: { text: 'Cpu Usages', x: 'center' },
tooltip: { trigger: 'axis' },
xAxis: { type: 'time' },
yAxis: { min: 0, max: 100 },
series: []
}

refresh() {
sys.Services.MetricService.GetCpuUsages(this.node, this.start, this.end).then(res => {
this.chartOptions.series.splice(0)
for (var i = 0; i < res.length; ++i) {
var seria = { type: 'line', name: 'cpu' + i, data: res[i], showSymbol: false }
this.chartOptions.series.push(seria)
}
}).catch(err => {
this.$message(err)
})
}

mounted() {
this.refresh()
}
}

三、组合多个组件形成Dashboard

  根据需要可以灵活组合多个指标组件，形成相应的Dashboard界面（如下图所示）。

四、小结

  感谢Vue、ECharts、Vue-ECharts、Prometheus等项目，使得开发并集成监控Dashboard如此简单。另码文不易，码技术文更不易，所以请您多多推荐！