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。
文章图片
【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"}
...
原文链接
本文为阿里云原创内容,未经允许不得转载。
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