自监控指标接口

LoongCollector提供了指标接口，可以方便地为插件增加一些自监控指标，目前支持Counter，Gauge，String，Latency等类型。

接口：

https://github.com/alibaba/ilogtail/blob/main/pkg/pipeline/self_metric.go

实现：

https://github.com/alibaba/ilogtail/blob/main/pkg/helper/self_metrics_vector_imp.go

用户使用时需要引入pkg/helper包：

import (
    "github.com/alibaba/ilogtail/pkg/helper"
)

创建指标

指标必须先定义后使用，在插件的结构体内声明具体指标。

type ProcessorRateLimit struct {
    // other fields
    context         pipeline.Context
    limitMetric     pipeline.CounterMetric  // 第一个指标
    processedMetric pipeline.CounterMetric   // 第二个指标
}

创建指标时，需要将其注册到iLogtail Context 的 MetricRecord 中，以便 iLogtail 能够采集上报数据，在插件的Init方法中，调用context 的 GetMetricRecord()方法来获取MetricRecord，然后调用helper.NewXXXMetricAndRegister函数去注册一个指标，例如：

metricsRecord := p.context.GetMetricRecord()
p.limitMetric = helper.NewCounterMetricAndRegister(metricsRecord, fmt.Sprintf("%v_limited", pluginType))
p.processedMetric = helper.NewCounterMetricAndRegister(metricsRecord, fmt.Sprintf("%v_processed", pluginType))

用户在声明一个Metric时可以还额外注入一些插件级别的静态Label，这是一个可选参数，例如flusher_http就把RemoteURL等配置进行上报：

metricsRecord := f.context.GetMetricRecord()
metricLabels := f.buildLabels()
f.matchedEvents = helper.NewCounterMetricAndRegister(metricsRecord, "http_flusher_matched_events", metricLabels...)

指标打点

不同类型的指标有不同的打点方法，直接调用对应Metric类型的方法即可。
Counter：

p.processedMetric.Add(1)

Latency:

tracker.ProcessLatency.Observe(float64(time.Since(startProcessTime)))

StringMetric:

sc.lastBinLogMetric.Set(string(r.NextLogName))

指标上报

LoongCollector会自动采集所有注册的指标，默认采集间隔为60s，然后通过default_flusher上报，数据格式为LogGroup，格式如下：

{"Logs":[{"Time":0,"Contents":[{"Key":"http_flusher_matched_events","Value":"2.0000"},{"Key":"__name__","Value":"http_flusher_matched_events"},{"Key":"RemoteURL","Value":"http://testeof.com/write"},{"Key":"db","Value":"%{metadata.db}"},{"Key":"flusher_http_id","Value":"0"},{"Key":"project","Value":"p"},{"Key":"config_name","Value":"c"},{"Key":"plugins","Value":""},{"Key":"category","Value":"p"},{"Key":"source_ip","Value":"100.80.230.110"}]},{"Time":0,"Contents":[{"Key":"http_flusher_unmatched_events","Value":"0.0000"},{"Key":"__name__","Value":"http_flusher_unmatched_events"},{"Key":"db","Value":"%{metadata.db}"},{"Key":"flusher_http_id","Value":"0"},{"Key":"RemoteURL","Value":"http://testeof.com/write"},{"Key":"project","Value":"p"},{"Key":"config_name","Value":"c"},{"Key":"plugins","Value":""},{"Key":"category","Value":"p"},{"Key":"source_ip","Value":"100.80.230.110"}]},{"Time":0,"Contents":[{"Key":"http_flusher_dropped_events","Value":"0.0000"},{"Key":"__name__","Value":"http_flusher_dropped_events"},{"Key":"RemoteURL","Value":"http://testeof.com/write"},{"Key":"db","Value":"%{metadata.db}"},{"Key":"flusher_http_id","Value":"0"},{"Key":"project","Value":"p"},{"Key":"config_name","Value":"c"},{"Key":"plugins","Value":""},{"Key":"category","Value":"p"},{"Key":"source_ip","Value":"100.80.230.110"}]},{"Time":0,"Contents":[{"Key":"http_flusher_retry_count","Value":"2.0000"},{"Key":"__name__","Value":"http_flusher_retry_count"},{"Key":"RemoteURL","Value":"http://testeof.com/write"},{"Key":"db","Value":"%{metadata.db}"},{"Key":"flusher_http_id","Value":"0"},{"Key":"project","Value":"p"},{"Key":"config_name","Value":"c"},{"Key":"plugins","Value":""},{"Key":"category","Value":"p"},{"Key":"source_ip","Value":"100.80.230.110"}]},{"Time":0,"Contents":[{"Key":"http_flusher_flush_failure_count","Value":"2.0000"},{"Key":"__name__","Value":"http_flusher_flush_failure_count"},{"Key":"db","Value":"%{metadata.db}"},{"Key":"flusher_http_id","Value":"0"},{"Key":"RemoteURL","Value":"http://testeof.com/write"},{"Key":"project","Value":"p"},{"Key":"config_name","Value":"c"},{"Key":"plugins","Value":""},{"Key":"category","Value":"p"},{"Key":"source_ip","Value":"100.80.230.110"}]},{"Time":0,"Contents":[{"Key":"http_flusher_flush_latency_ns","Value":"2504448312.5000"},{"Key":"__name__","Value":"http_flusher_flush_latency_ns"},{"Key":"db","Value":"%{metadata.db}"},{"Key":"flusher_http_id","Value":"0"},{"Key":"RemoteURL","Value":"http://testeof.com/write"},{"Key":"project","Value":"p"},{"Key":"config_name","Value":"c"},{"Key":"plugins","Value":""},{"Key":"category","Value":"p"},{"Key":"source_ip","Value":"100.80.230.110"}]}],"Category":"","Topic":"","Source":"","MachineUUID":""}

一组LogGroup中会有多条Log，每一条Log都对应一条指标，其中 {"Key":"__name__","Value":"http_flusher_matched_events"} 是一个特殊的Label，代表指标的名字。

高级功能

动态Label

和Prometheus SDK类似，LoongCollector也允许用户在自监控时上报可变Label，对于这些带可变Label的指标集合，LoongCollector称之为MetricVector，
MetricVector同样也支持上述的指标类型，因此把上面的Metric看作是MetricVector不带动态Label的特殊实现。
用例：

type FlusherHTTP struct {
    // other fields

    context     pipeline.Context
    statusCodeStatistics pipeline.MetricVector[pipeline.CounterMetric] // 带有动态Label的指标
}

声明并注册MetricVector时，可以使用helper.NewXXXMetricVectorAndRegister方法，
需要将其带有哪些动态Label的Name也进行声明：

f.statusCodeStatistics = helper.NewCounterMetricVectorAndRegister(metricsRecord,
    "http_flusher_status_code_count",
    map[string]string{"RemoteURL": f.RemoteURL},
    []string{"status_code"},
)

打点时通过WithLabels API传入动态Label的值，拿到一个Metric对象，然后进行打点：

f.statusCodeStatistics.WithLabels(pipeline.Label{Key: "status_code", Value: strconv.Itoa(response.StatusCode)}).Add(1)

示例

可以参考内置的一些插件：

限流插件：
https://github.com/alibaba/ilogtail/blob/main/plugins/processor/ratelimit/processor_rate_limit.go

http flusher插件：
https://github.com/alibaba/ilogtail/blob/main/plugins/flusher/http/flusher_http.go