GRPC: 如何实现分布式日志跟踪()

简介: 本文将介绍如何在 gRPC 分布式场景中,实现 API 的日志跟踪。
介绍
本文将介绍如何在 gRPC 分布式场景中,实现 API 的日志追踪。
什么是 API 日志追踪?
一个 API 请求会跨多个微服务,我们希望通过一个唯一的 ID 检索到整个链路的日志。
GRPC: 如何实现分布式日志跟踪()
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【GRPC: 如何实现分布式日志跟踪()】我们将会使用 rk-boot 来启动 gRPC 服务。
请访问如下地址获取完整教程:
https://rkdev.info/cn
https://rkdocs.netlify.app/cn (备用)
安装
go get github.com/rookie-ninja/rk-boot
快速开始
rk-boot 默认集成了 grpc-gateway,并且会默认启动。
我们会创建 /api/v1/greeter API 进行验证,同时开启 logging, meta 和 tracing 拦截器以达到目的。
1. 创建 api/v1/greeter.proto

syntax = "proto3"; package api.v1; option go_package = "api/v1/greeter"; service Greeter { rpc Greeter (GreeterRequest) returns (GreeterResponse) {} }message GreeterRequest { string name = 1; }message GreeterResponse { string message = 1; }

2. 创建 api/v1/gw_mapping.yaml
type: google.api.Service config_version: 3# Please refer google.api.Http in https://github.com/googleapis/googleapis/blob/master/google/api/http.proto file for details. http: rules: - selector: api.v1.Greeter.Greeter get: /api/v1/greeter

3. 创建 buf.yaml
version: v1beta1 name: github.com/rk-dev/rk-demo build: roots: - api

4. 创建 buf.gen.yaml
version: v1beta1 plugins: # protoc-gen-go needs to be installed, generate go files based on proto files - name: go out: api/gen opt: - paths=source_relative # protoc-gen-go-grpc needs to be installed, generate grpc go files based on proto files - name: go-grpc out: api/gen opt: - paths=source_relative - require_unimplemented_servers=false # protoc-gen-grpc-gateway needs to be installed, generate grpc-gateway go files based on proto files - name: grpc-gateway out: api/gen opt: - paths=source_relative - grpc_api_configuration=api/v1/gw_mapping.yaml # protoc-gen-openapiv2 needs to be installed, generate swagger config files based on proto files - name: openapiv2 out: api/gen opt: - grpc_api_configuration=api/v1/gw_mapping.yaml

5. 编译 proto file
$ buf generate 如下的文件会被创建。 $ tree api/gen api/gen └── v1 ├── greeter.pb.go ├── greeter.pb.gw.go ├── greeter.swagger.json └── greeter_grpc.pb.go 1 directory, 4 files

6. 创建 bootA.yaml & serverA.go Server-A 监听 1949 端口,并且发送请求给 Server-B。
我们通过 rkgrpcctx.InjectSpanToNewContext() 方法把 Tracing 信息注入到 Context 中,发送给 Server-B。
--- grpc: - name: greeter# Name of grpc entry port: 1949# Port of grpc entry enabled: true# Enable grpc entry interceptors: loggingZap: enabled: true meta: enabled: true tracingTelemetry: enabled: true

package mainimport ( "context" "demo/api/gen/v1" "fmt" "github.com/rookie-ninja/rk-boot" "github.com/rookie-ninja/rk-grpc/interceptor/context" "google.golang.org/grpc" )// Application entrance. func main() { // Create a new boot instance. boot := rkboot.NewBoot(rkboot.WithBootConfigPath("bootA.yaml"))// Get grpc entry with name grpcEntry := boot.GetGrpcEntry("greeter") grpcEntry.AddRegFuncGrpc(registerGreeter) grpcEntry.AddRegFuncGw(greeter.RegisterGreeterHandlerFromEndpoint)// Bootstrap boot.Bootstrap(context.Background())// Wait for shutdown sig boot.WaitForShutdownSig(context.Background()) }func registerGreeter(server *grpc.Server) { greeter.RegisterGreeterServer(server, &GreeterServer{}) }type GreeterServer struct{}func (server *GreeterServer) Greeter(ctx context.Context, request *greeter.GreeterRequest) (*greeter.GreeterResponse, error) { // Call serverB at 2008 with grpc client opts := []grpc.DialOption{ grpc.WithBlock(), grpc.WithInsecure(), } conn, _ := grpc.Dial("localhost:2008", opts...) defer conn.Close() client := greeter.NewGreeterClient(conn)// Inject current trace information into context newCtx := rkgrpcctx.InjectSpanToNewContext(ctx) client.Greeter(newCtx, &greeter.GreeterRequest{Name: "A"})return &greeter.GreeterResponse{ Message: fmt.Sprintf("Hello %s!", request.Name), }, nil }

7. 创建 bootB.yaml & serverB.go Server-B 监听 2008 端口。
--- grpc: - name: greeter# Name of grpc entry port: 2008# Port of grpc entry enabled: true# Enable grpc entry interceptors: loggingZap: enabled: true meta: enabled: true tracingTelemetry: enabled: true

package mainimport ( "context" "demo/api/gen/v1" "fmt" "github.com/rookie-ninja/rk-boot" "google.golang.org/grpc" )// Application entrance. func main() { // Create a new boot instance. boot := rkboot.NewBoot(rkboot.WithBootConfigPath("bootB.yaml"))// Get grpc entry with name grpcEntry := boot.GetGrpcEntry("greeter") grpcEntry.AddRegFuncGrpc(registerGreeterB) grpcEntry.AddRegFuncGw(greeter.RegisterGreeterHandlerFromEndpoint)// Bootstrap boot.Bootstrap(context.Background())// Wait for shutdown sig boot.WaitForShutdownSig(context.Background()) }func registerGreeterB(server *grpc.Server) { greeter.RegisterGreeterServer(server, &GreeterServerB{}) }type GreeterServerB struct{}func (server *GreeterServerB) Greeter(ctx context.Context, request *greeter.GreeterRequest) (*greeter.GreeterResponse, error) { return &greeter.GreeterResponse{ Message: fmt.Sprintf("Hello %s!", request.Name), }, nil }

8. 文件夹结构
├── api │├── gen ││└── v1 ││├── greeter.pb.go ││├── greeter.pb.gw.go ││├── greeter.swagger.json ││└── greeter_grpc.pb.go │└── v1 │├── greeter.proto │└── gw_mapping.yaml ├── bootA.yaml ├── bootB.yaml ├── buf.gen.yaml ├── buf.yaml ├── go.mod ├── go.sum ├── serverA.go └── serverB.go

9. 启动 ServerA & ServerB `$ go run serverA.go
$ go run serverB.go`
10. 往 ServerA 发送请求 ¥ curl "localhost:1949/api/v1/greeter?name=rk-dev"
11. 验证日志 两个服务的日志中,会有同样的 traceId,不同的 requestId。
我们可以通过 grep traceId 来追踪 RPC。
ServerA
------------------------------------------------------------------------ endTime=2021-10-20T00:02:21.739688+08:00 ... ids={"eventId":"0d145356-998a-4999-ab62-6f1b805274a0","requestId":"0d145356-998a-4999-ab62-6f1b805274a0","traceId":"c36a45eb076066df39fa407174012369"} ... operation=/api.v1.Greeter/Greeter resCode=OK eventStatus=Ended EOE

ServerB
------------------------------------------------------------------------ endTime=2021-10-20T00:02:21.739125+08:00 ... ids={"eventId":"8858a6eb-e953-42ad-bdc3-c466bbbd798e","requestId":"8858a6eb-e953-42ad-bdc3-c466bbbd798e","traceId":"c36a45eb076066df39fa407174012369"} ... operation=/api.v1.Greeter/Greeter resCode=OK eventStatus=Ended EOE

概念
当我们没有使用例如 jaeger 调用链服务的时候,我们希望通过日志来追踪分布式系统里的 RPC 请求。
rk-boot 的拦截器会通过 openTelemetry 库来向日志写入 traceId 来追踪 RPC。
当启动了日志拦截器,原数据拦截器,调用链拦截器的时候,拦截器会往日志里写入如下三种 ID。
EventId
当启动了日志拦截器,EventId 会自动生成。
--- grpc: - name: greeter# Name of grpc entry port: 1949# Port of grpc entry enabled: true# Enable grpc entry interceptors: loggingZap: enabled: true

------------------------------------------------------------------------ ... ids={"eventId":"cd617f0c-2d93-45e1-bef0-95c89972530d"} ...

RequestId
当启动了日志拦截器和原数据拦截器,RequestId 和 EventId 会自动生成,并且这两个 ID 会一致。
--- grpc: - name: greeter# Name of grpc entry port: 1949# Port of grpc entry enabled: true# Enable grpc entry interceptors: loggingZap: enabled: true meta: enabled: true ------------------------------------------------------------------------

... ids={"eventId":"8226ba9b-424e-4e19-ba63-d37ca69028b3","requestId":"8226ba9b-424e-4e19-ba63-d37ca69028b3"} ...

即使用户覆盖了 RequestId,EventId 也会保持一致。
rkgrpcctx.AddHeaderToClient(ctx, rkgrpcctx.RequestIdKey, "overridden-request-id")

------------------------------------------------------------------------ ... ids={"eventId":"overridden-request-id","requestId":"overridden-request-id"} ...

TraceId
当启动了调用链拦截器,traceId 会自动生成。
--- grpc: - name: greeter# Name of grpc entry port: 1949# Port of grpc entry enabled: true# Enable grpc entry interceptors: loggingZap: enabled: true meta: enabled: true tracingTelemetry: enabled: true

------------------------------------------------------------------------ ... ids={"eventId":"dd19cf9a-c7be-486c-b29d-7af777a78ebe","requestId":"dd19cf9a-c7be-486c-b29d-7af777a78ebe","traceId":"316a7b475ff500a76bfcd6147036951c"} ...

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