Category: containers

Communication between microservices in Kubernetes with Go Micro

In this post, we continue the story we started with two earlier posts:

In the previous post, I described a very simple service written with the help of Go Micro. It exposes an RPC call Get that retrieves a device from a list of devices. Now we want a simple data service we can call via a RESTful interface like so: http://name_or_ip/data/device1. Note that no actual data is returned by the call. We just return true if the device exists and false if it does not.

The code for the “data” service can be found here: https://github.com/gbaeke/go-data/blob/master/main.go. The code is again very simply. To expose the RESTful interface, I used Gorilla. In the handler for the route /data/{device}, we call the Device service using a Go Micro client. Because the client is configured to use Kubernetes as the registry, it will look up where the Device service lives and call it. Let’s take a look at the code to call the Device service.

It starts with declaring a variable of type device.DevSvcClient which is defined in the generated code by protoc (see code for the device service here):

// devSvc is the service for the client
var (
	cl device.DevSvcClient
)

In the init() function, the client is created and configured to call the go.micro.srv.device service:

func init() {
	// make sure flags are processed
	cmd.Init()

	// initialise a default client for device service
	cl = device.NewDevSvcClient("go.micro.srv.device", client.DefaultClient)

}

In the route handler, the device name is extracted from the URL and then we call another function that returns true if the device exists and is active.

deviceActive(&device.DeviceName{Name: deviceName})

The deviceActive function looks like:

func deviceActive(d *device.DeviceName) bool {
	//call Get method from devSvcClient to obtain the device
	fmt.Println("Getting device", d.Name)
	rsp, err := cl.Get(context.TODO(), d)
	if err != nil {
		fmt.Println(err)
		return false
	}

	return rsp.Active
}

The above function expects a pointer to a DeviceName struct which is again defined by the protoc generated code used by the Device service. As you can see, calling the Get method is trivial. Behind the scenes, the client code locates the Device service in Kubernetes and does all the serialization/deserialization work to and from a binary format.

After the service is deployed in Kubernetes (see this post), we can check if it works using:

curl http://ip_of_loadbalancer/data/device1

The above should return the following:

Device active:  true
Oh and, no data for you!

I told you the service returned no data! 🙂

We now have two services that communicate using RPC in a Kubernetes cluster. Writing RESTful APIs and putting them in front of the RPC services is easy enough but something is off though! We don’t want to deploy many services that offer a RESTful API and then expose them using multiple external IPs because that’s just cumbersome. What we do want is to use the API Gateway pattern. In a future post, I will describe how to use Go Micro’s API gateway and an API service that exposes the device service to the outside world using a RESTful interface. Quite the mouthful… Stay tuned!

Microservices on Kubernetes: a simple example in Go

In the previous post, Getting started with Kubernetes on Azure, we talked about creating a Kubernetes cluster and deploying a couple of services. There are basically two services:

  • Data: a service that exposes an endpoint to pick up data for an IoT device; you call it with http://service_endpoint:8080/data/devicename
  • Device: a service that can be used by the Data API to check if a device exists; if the device exists you will see that in the response

When you call the Data service, it will call the Device service using gRPC, using HTTP as the transport protocol. You define the service using Protocol Buffers. gRPC works across languages and platforms, so I could have implemented each service using a different language like Go for the Device service and Node.js for the Data service. In this example, I decided to use Go in both cases and use Go Micro, a pluggable RPC framework for microservices. Go Micro uses gRPC and protocol buffers under the hood with changes specific to Go Micro.

Ok, enough with the talk, let’s take a look how it is done. The Device service is kept extremely simple for an abvious reason: I just started with Go Micro and then it is best to start with something simple. I do expect you know a bit of Go from here on out. All the code can be found at https://github.com/gbaeke/go-device.

Lets start with the definition of Protocol Buffers, found in proto/device.proto:

syntax = "proto3";

service DevSvc {
    rpc Get(DeviceName) returns (Device) {}
}

message DeviceName {
    string name = 1;
}

message Device {
    string name = 1;
    bool active = 2;
}

We define one RPC call here that expects a DeviceName message as input and returns a Device message. Simple enough but this does not get us very far. To actually use this in Go (or another supported language), we will generate some code from the above definition. You need a couple of things to do that though:

  • protoc compiler: download from Github  for your platform
  • protobuf plugins for code generation for Go Micro: run go get github.com/micro/protobuf/{proto,protoc-gen-go} (if you have issues, use 2 gets, one for proto and one for protoc-gen-go)

To actually compile the proto file, use the following command:

protoc --go_out=plugins=micro:. device.proto

That compiles device.proto to device.pb.go with help from the micro plugin. You can check the generated code here. Among other things, there are Go structs for the DeviceName and Device message plus several methods you can call on these structs such as Reset() and String().

Now for main.go! You’ll need several imports: for the generated code but also for the dependencies to build the service with Go Micro. If you check the code, you will also find the following import:

_ "github.com/micro/go-plugins/registry/kubernetes"

As stated above, Go Micro is a pluggable RPC framework. Out of the box, a microservice written with Go Micro will try to register itself with Consul on localhost for service discovery and configuration. We could run the Consul service in Kubernetes but Kubernetes supports service registration natively. Kubernetes support is something you add with the import above. That is not enough though! You still need to tell Go Micro to use Kubernetes as the registry, either with the —registry command line parameter or with an environment variable MICRO_REGISTRY. Check https://github.com/gbaeke/go-device/blob/master/go-device-dep.yaml file where that environment variable is set. Besides Consul and Kubernetes, there are other alternatives. One of them is multicast DNS (mdns) which is handy when you are testing services on your local machine and you don’t have something like Consul running.

If you want to check the information that is registered, you can do the following (after running kubectl proxy --port=8080):

curl http://localhost:8080/api/v1/pods | grep micro

Each pod will have an annotation with key micro.mu/service-<servicename> with information about the service such as its name, IP address, port, and much more.

Now really over to main.go, which is pretty self explanatory. There’s a struct called DevSvc which has a field called devs which holds the map of strings to Device structs. The DevSvc actually defines the service and you write the RPC calls as methods of that struct. Check out the following code snippet:

// DevSvc defines the service
type DevSvc struct {
	devs map[string]*device.Device
}
func (d *DevSvc) Get(ctx context.Context, req *device.DeviceName, rsp *device.Device) error {
	device, ok := d.devs[req.Name]
	if !ok {
		fmt.Println("Device does not exist")
		return nil
	}

	fmt.Println("Will respond with ", device)

	// this also works
	rsp.Name = device.Name
	rsp.Active = device.Active

	return nil
}

The Get function implements what was defined in the .proto file earlier and uses pointers to a DeviceName struct as input and a pointer to a Device struct as output. The code itself is of course trivial and just looks up a device in the map and returns it with rsp.

Of course, this handler needs to be registered and this happens in the main() function (besides setting up the service and implementing a custom flag):

// register handler and initialise devs map with a list of devices
device.RegisterDevSvcHandler(service.Server(), &DevSvc{devs: LoadDevices()})

If you want to test the service and call it (e.g. on the local machine) then clone the repository (or get it) and run the server as follows:

go run main.go --registry=mdns

In another terminal, run:

go run main.go --registry=mdns --run_client

When you run the code with the run_client option, the runClient function is called which looks like:

func runClient(service micro.Service) {
	// Create new client to call DevSvc service
	DevClient := device.NewDevSvcClient("go.micro.srv.device", service.Client())

	// Call Get to get a device
	rsp, err := DevClient.Get(context.TODO(), &device.DeviceName{Name: "device2"})
	if err != nil {
		fmt.Println(err)
		return
	}

	// Print response
	fmt.Println("Response: ", rsp)
}

This again shows the power of using a framework like Go Micro: you create a client for the DevSvc service and then simply perform the remote procedure call with the Get method, passing in a DeviceName struct with the Name field set to the device you want to check. The client uses the service registry to know where and how to connect. All the serialization and deserialization is handled for you as well using protocol buffers.

So great, you now have a little bit more information about the Device service and you know how to deploy it to Kubernetes. In another post, we’ll see how the Data service works and explore some other options to write that service.

Getting started with Kubernetes on Azure

As you may or may not know, at Xylos we have developed an IoT platform to support sensor networks of any kind. The back-end components are microservices running as containers on Rancher, a powerful and easy to use container orchestration tool. In the meantime, we are constantly evaluating other ways of orchestrating containers and naturally, Azure Container Services is one of the options. Recently, Microsoft added support for Kubernetes so we decided to check that out.

Instead of the default “look, here’s how you deploy an nginx container”, we will walk through an example of an extremely simple microservices application written in Go with the help of go-micro, a microservices toolkit. Now, I have to warn you that I am quite the newbie when it comes to Go and go-micro. If you have remarks about the code, just let me know. This post will not explain the Go services however, so let’s focus on deploying a Kubernetes cluster first and deploying the finished containers. Subsequent posts will talk about the services in more detail.

With the help of Azure CLI 2.0, deploying Kubernetes could not be simpler. You will find full details about installation on https://docs.microsoft.com/en-us/cli/azure/install-azure-cli. The CLI runs on Windows, Linux and macOS. For this post, I used macOS. If you are a bit unsure about how the Azure CLI works, check out this post: https://docs.microsoft.com/en-us/cli/azure/get-started-with-azure-cli.

After installation, use az login to authenticate and az account to set the default subscription. After that you are all set to deploy Kubernetes. First, create a resource group for the cluster:

az group create --name=rgname --location=westeurope

After the above command (use any name as resource group), use the following command to create a Kubernetes cluster with only one master and two agents and use a small virtual machine size. We do this to keep costs down while testing.

az acs create --orchestrator-type=kubernetes --resource-group=rgname --name=clustername --generate-ssh-keys --agent-count=2 --master-count=1 --agent-vm-size=Standard_A1_v2

Tip: to know the other virtual machine sizes in a region (like westeurope) use az vm list-sizes --location=westeurope

Note that in the az acs command, we auto-generate SSH keys. These are used to interact with the cluster and you can of course create your own. When you use generate-ssh-keys, you will find them in your home folder in the .ssh folder (id_rsa and id_rsa.pub files).

Now you need a way to administer the Kubernetes cluster. You do that with the kubectl command-line tool. Get kubectl with the following command:

az acs kubernetes install-cli

The kubectl tool needs a configuration file that instructs the tool where to connect and the credentials to use. Just use the following command to get this configured:

az acs kubernetes get-credentials --resource-group=rgname --name=clustername

Running the above command creates a config file in the .kube folder of your home folder. In the config file, you will see a https location that kubectl connects to, in addition to user information such as a user name and certificates.

Now, as a test, lets deploy a part of the microservices application that exposes a REST API endpoint to the outside world (I call it the data API). To do so, do the following:

kubectl create -f https://raw.githubusercontent.com/gbaeke/go-data/master/go-data-dep.yaml

The above command creates a deployment from a configuration file that makes sure that there are two containers running that use the image gbaeke/go-data. Each container runs in its own pod. You can check this like so:

kubectl get pods

You will see something like:

image-2

Run kubectl get deployment to see the deployment. Use kubectl describe deployment dataapito obtain more details about the deployment.

You will not be able to access this API from the outside world. To do this, let’s create a service of type LoadBalancer which will also configure an Azure load balancer automatically (could have been done from the YAML file as well):

kubectl expose deployments dataapi --port=8080 --type=LoadBalancer

You can check the service with kubectl get service. After a while and by running the last command again, the external IP will appear. You should now be able to hit the service with curl like so:

curl http://IP_of_service:8080/data/device1

No matter what device id you type at the end, you will always get Device active: false because the device API has not been deployed yet. How the data API talks to the device API and how they use service registration in Kubernetes will be discussed in another post.

Tip: for those that cannot wait, just run kubectl create -f https://raw.githubusercontent.com/gbaeke/go-device/master/go-device-dep.yaml and then use curl again with device1 at the end (should return true). The above command deploys the device API so that the data API can find and use it to check if a device exists.