微服务的可观测性大致分为三大类:Metrics,Tracing 和 Logging
Metrics 监控侧重于技术指标的收集与观测,如服务调用 QPS、响应时间、错误率和资源使用率。
可以使用Prometheus来监控. (
Promtheus 如何使用: https://segmentfault.com/a/11...
PromQL查询:https://segmentfault.com/a/11... )
Logging 侧重于运行日志的采集、存储与检索,通常使用ELK, 可以使用 fileBeat,logurs 等组件,来记录。
Tracing 则偏向于调用链的串联、追踪与 APM 分析,服务与服务之间的调用耗时等等,链路追踪。
对于微服务调用链的监控,开源组件推荐zipkin Jaeger
(jaeger使用: https://segmentfault.com/a/11...)
Prometheus和Grafana用于度量指标收集、监控和警报
Jaeger、开源组件推荐zipkin用于分布式全链路追踪
Kiali为Istio提供基于服务网格的微服务可视化
参考: https://www.cnblogs.com/whuan...
环境安装:
docker下进安装zipkin
docker run -d -p 9411:9411 openzipkin/zipkin
一、对grpc服务进行监控
服务端
const (
serviceName = "simple_zipkin_server"
zipkinAddr = "http://127.0.0.1:9411/api/v1/spans"
zipkinRecorderAddr = "127.0.0.1:9000"
)
/*
获取zipkin的tracer对象,并把tracer封装成ServerInterceptor注入到grpc.ServerOption中
*/
func NewZipkinTracer(opts []grpc.ServerOption) (opentracing.Tracer, []grpc.ServerOption, error) {
collector, err := zipkin.NewHTTPCollector(zipkinAddr)
if err != nil {
log.Fatal(err.Error())
return nil, opts, err
}
recorder := zipkin.NewRecorder(collector, true, zipkinRecorderAddr, serviceName)
tracer, err := zipkin.NewTracer(recorder, zipkin.ClientServerSameSpan(true), zipkin.TraceID128Bit(true))
if err != nil {
log.Fatal(err.Error())
return nil, opts, err
}
opts = append(opts, grpc_middleware.WithUnaryServerChain(
otgrpc.OpenTracingServerInterceptor(tracer, otgrpc.LogPayloads()),
))
return tracer, opts, nil
}
func main() {
//...
go func() {
//...
var opts = []grpc.ServerOption{grpc.Creds(cred)}
_, opts, err = NewZipkinTracer(opts)
if err != nil {
log.Fatal(err.Error())
return
}
rpcserver := grpc.NewServer(opts...)
//...
}
//...
}
客户端
const (
serviceName = "simple_zipkin_server"
zipkinAddr = "http://127.0.0.1:9411/api/v1/spans"
zipkinRecorderAddr = "127.0.0.1:9000"
)
/*
获取zipkin的tracer对象,并把tracer封装成ClientInterceptor注入到grpc.DialOption中
*/
func NewZipkinTracer(opts []grpc.DialOption) (opentracing.Tracer, []grpc.DialOption, error) {
collector, err := zipkin.NewHTTPCollector(zipkinAddr)
if err != nil {
log.Fatal(err.Error())
return nil, opts, err
}
recorder := zipkin.NewRecorder(collector, true, zipkinRecorderAddr, serviceName)
tracer, err := zipkin.NewTracer(recorder, zipkin.ClientServerSameSpan(true), zipkin.TraceID128Bit(true))
if err != nil {
log.Fatal(err.Error())
return nil, opts, err
}
opts = append(opts, grpc.WithUnaryInterceptor(
otgrpc.OpenTracingClientInterceptor(tracer, otgrpc.LogPayloads()),
))
return tracer, opts, nil
}
func main() {
//...
var opts = []grpc.DialOption{grpc.WithTransportCredentials(creds)}
_, opts, err = NewZipkinTracer(opts)
if err != nil {
log.Fatal(err.Error())
return
}
conn, err := grpc.Dial(fmt.Sprintf("%v:%d", addr.Service.Address, addr.Service.Port), opts...)
if err != nil {
log.Fatal(err)
}
defer conn.Close()
//...
}
先后运行server.go和client.go,进行一次grpc的调用;
访问http://localhost:9411/zipkin,选择"serviceName"为"simple_zipkin_server"
二、对Gin框架的Web服务进行监控
var (
zkReporter reporter.Reporter
zkTracer opentracing.Tracer
)
const (
serviceName = "zipkin_gin_server"
serviceEndpoint = "localhost:8080"
zipkinAddr = "http://127.0.0.1:9411/api/v2/spans"
)
func initZipkinTracer(engine *gin.Engine) error {
zkReporter = zkHttp.NewReporter(zipkinAddr)
endpoint, err := zipkin.NewEndpoint(serviceName, serviceEndpoint)
if err != nil {
log.Fatalf("unable to create local endpoint: %+v\n", err)
return err
}
nativeTracer, err := zipkin.NewTracer(zkReporter, zipkin.WithTraceID128Bit(true), zipkin.WithLocalEndpoint(endpoint))
if err != nil {
log.Fatalf("unable to create tracer: %+v\n", err)
return err
}
zkTracer = zkOt.Wrap(nativeTracer)
opentracing.SetGlobalTracer(zkTracer)
// 将tracer注入到gin的中间件中
engine.Use(func(c *gin.Context) {
span := zkTracer.StartSpan(c.FullPath())
defer span.Finish()
c.Next()
})
return nil
}
func main() {
engine := gin.Default()
err := initZipkinTracer(engine)
if err != nil {
panic(err)
}
defer zkReporter.Close()
engine.GET("/ping", func(c *gin.Context) {
c.JSON(http.StatusOK, "pong")
})
//...
engine.Run(":8080")
}
参考文章:
https://github.com/EDDYCJY/go...
http://www.dockone.io/article...
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