kubernetes/

README

Micro on Kubernetes

Micro on Kubernetes is a kubernetes native micro service deployment.

Overview

Micro is a blueprint for microservice development. Kubernetes is a container orchestration system. Together they provide the foundations for a microservice platform. Micro on Kubernetes provides a kubernetes native runtime to help build micro services.

Features

• No external dependencies
• K8s native services
• Service mesh integration
• gRPC communication protocol
• Pre-initialised micro images
• Healthchecking sidecar

Getting Started

• Installing Micro
• Writing a Service
• Deploying a Service
• Writing a Web Service
• Healthchecking
• Load Balancing
• Using Service Mesh
• Using Config Map
• Contribute

Installing Micro

go get github.com/xxdawn/micro/examples/kubernetes/cmd/micro

or

docker pull microhq/micro:kubernetes

For go-micro

import "github.com/xxdawn/micro/examples/kubernetes/go/micro"

Writing a Service

Write a service as you would any other go-micro service.

import (
	"github.com/micro/go-micro/v2"
	k8s "github.com/xxdawn/micro/examples/kubernetes/go/micro"
)

func main() {
	service := k8s.NewService(
		micro.Name("greeter"),
	)
	service.Init()
	service.Run()
}

Deploying a Service

Here's an example k8s deployment for a micro service

Create a Deployment

apiVersion: apps/v1
kind: Deployment
metadata:
  namespace: default
  name: greeter
spec:
  replicas: 1
  template:
    metadata:
      labels:
        app: greeter-srv
    spec:
      containers:
        - name: greeter
          command: [
		"/greeter-srv",
		"--server_address=0.0.0.0:8080",
		"--broker_address=0.0.0.0:10001"
	  ]
          image: microhq/greeter-srv:kubernetes
          imagePullPolicy: Always
          ports:
          - containerPort: 8080
            name: greeter-port

Deploy with kubectl

kubectl create -f greeter.yaml

Create a Service

apiVersion: v1
kind: Service
metadata:
  name: greeter
  labels:
    app: greeter
spec:
  ports:
  - port: 8080
    protocol: TCP
  selector:
    app: greeter

Deploy with kubectl

kubectl create -f greeter-svc.yaml

Writing a Web Service

Write a web service as you would any other go-micro/web service.

import (
	"net/http"

	"github.com/micro/go-micro/v2/web"
	k8s "github.com/xxdawn/micro/examples/kubernetes/go/web"
)

func main() {
	service := k8s.NewService(
		web.Name("greeter"),
	)

	service.HandleFunc("/greeter", func(w http.ResponseWriter, r *http.Request) {
		w.Write([]byte(`hello world`))
	})

	service.Init()
	service.Run()
}

Healthchecking Sidecar

The healthchecking sidecar exposes /health as a http endpoint and calls the rpc endpoint Debug.Health on a service. Every go-micro service has a built in Debug.Health endpoint.

Install

go get github.com/xxdawn/micro/examples/kubernetes/cmd/health

or

docker pull microhq/health:kubernetes

Run

Run e.g healthcheck greeter service with address localhost:9091

health --server_name=greeter --server_address=localhost:9091

Call the healthchecker on localhost:8080

curl http://localhost:8080/health

K8s Deployment

Add the healthchecking sidecar to a kubernetes deployment

apiVersion: apps/v1
kind: Deployment
metadata:
  namespace: default
  name: greeter
spec:
  replicas: 1
  template:
    metadata:
      labels:
        app: greeter-srv
    spec:
      containers:
        - name: greeter
          command: [
		"/greeter-srv",
		"--server_address=0.0.0.0:8080",
		"--broker_address=0.0.0.0:10001"
	  ]
          image: microhq/greeter-srv:kubernetes
          imagePullPolicy: Always
          ports:
          - containerPort: 8080
            name: greeter-port
        - name: health
          command: [
		"/health",
                "--health_address=0.0.0.0:8081",
		"--server_name=greeter",
		"--server_address=0.0.0.0:8080"
	  ]
          image: microhq/health:kubernetes
          livenessProbe:
            httpGet:
              path: /health
              port: 8081
            initialDelaySeconds: 3
            periodSeconds: 3

Load Balancing

Micro includes client side load balancing by default but kubernetes also provides Service load balancing strategies. In micro on kubernetes we offload load balancing to k8s by using the static selector and k8s services.

Rather than doing address resolution, the static selector returns the service name plus a fixed port e.g greeter returns greeter:8080. Read about the static selector.

This approach handles both initial connection load balancing and health checks since Kubernetes services stop routing traffic to unhealthy services, but if you want to use long lived connections such as the ones in gRPC protocol, a service-mesh like Conduit, Istio and Linkerd should be prefered to handle service discovery, routing and failure.

Note: The static selector is enabled by default.

Usage

To manually set the static selector when running your service specify the flag or env var

Note: This is already enabled by default

MICRO_SELECTOR=static ./service

or

./service --selector=static

Deployment

An example deployment

apiVersion: apps/v1
kind: Deployment
metadata:
  namespace: default
  name: greeter
spec:
  replicas: 1
  template:
    metadata:
      labels:
        app: greeter-srv
    spec:
      containers:
        - name: greeter
          command: [
		"/greeter-srv",
		"--server_address=0.0.0.0:8080",
		"--broker_address=0.0.0.0:10001"
	  ]
          image: microhq/greeter-srv:kubernetes
          imagePullPolicy: Always
          ports:
          - containerPort: 8080
            name: greeter-port

Deploy with kubectl

kubectl create -f deployment-static-selector.yaml

Service

The static selector offloads load balancing to k8s services. So ensure you create a k8s Service for each micro service.

Here's a sample service

apiVersion: v1
kind: Service
metadata:
  name: greeter
  labels:
    app: greeter
spec:
  ports:
  - port: 8080
    protocol: TCP
  selector:
    app: greeter

Deploy with kubectl

kubectl create -f service.yaml

Calling micro service "greeter" from your service will route to the k8s service greeter:8080.

Using Service Mesh

Service mesh acts as a transparent L7 proxy for offloading distributed systems concerns to an external source.

See linkerd2 for usage.

Using Config Map

Go Config is a simple way to manage dynamic configuration. We've provided a pre-initialised version which reads from environment variables and the k8s config map.

It uses the default namespace and expects a configmap with name micro to be present.

Example

Create a configmap

// we recommend to setup your variables from multiples files example:
$ kubectl create configmap micro --namespace default --from-file=./testdata

// verify if were set correctly with
$ kubectl get configmap micro --namespace default
{
    "apiVersion": "v1",
    "data": {
        "config": "host=0.0.0.0\nport=1337",
        "mongodb": "host=127.0.0.1\nport=27017\nuser=user\npassword=password",
        "redis": "url=redis://127.0.0.1:6379/db01"
    },
    "kind": "ConfigMap",
    "metadata": {
        ...
        "name": "micro",
        "namespace": "default",
        ...
    }
}

Import and use the config

import "github.com/xxdawn/micro/examples/kubernetes/go/config"

cfg := config.NewConfig()

// the example above "mongodb": "host=127.0.0.1\nport=27017\nuser=user\npassword=password" will be accessible as:
conf.Get("mongodb", "host") // 127.0.0.1
conf.Get("mongodb", "port") // 27017

Contribute

We're looking for contributions from the community to help guide the development of Micro on Kubernetes

TODO

• Fix k8s namespace/service name issue
• Add example multi-service application
• Add k8s CRD for micro apps