The Complete Microservice Tutorial — [Part 1] Building User Service With GRPC, Node.JS, and MongoDB

MD Ahad Hasan

Published in

The Startup

4 min readNov 19, 2020

Project Link: https://github.com/Joker666/microservice-demo/

The Complete Microservice Tutorial — Part 0

Microservices are about decoupling your system. In a monolith, you build all the components of the software in one large codebase and deploy the software at once. But in the microservice world, we build each component of a large system decoupled from each other.

In Part - 0, we explored the project’s architecture and now we are going to build it. We are going to build the authentication and user service module of the application. We will use NodeJS for this logic and MongoDB for the data layer.

Prerequisites

Since we are going to build this service in NodeJS, you would need NodeJS and NPM installed. Also, we would need GRPC installed along with Protobuf for the transport layer.

NodeJS with NPM
ProtoBuf
GRPC
Docker

Essentially, we will build a GRPC server in NodeJS that accepts incoming RPC requests. We would need GRPC tools installed globally in NPM, so let’s do that first.

npm install -g grpc-tools

Proto

Let’s make a new directory Microservice-Demo and cd into it. The directory structure we will follow

MicroService-Demo
├── userService
│   ├── proto
│   │   ├── **/*.js
│   ├── node_modules
│   ├── api.js
│   ├── auth.js
|   ├── .env
|   ├── Dockerfile
│   ├── index.js
|   ├── package.json
│   └── testClient.js
├── protos
│   ├── user
│   │   ├── user.proto
|   docker-compose.yml

We are going to keep all our proto files outside of our NodeJS application so that it’s easier for us to use those in other services. If you are wondering what is a proto file, it is a new format introduced by Google to serialize data for API usage that needs to be compiled with protoc compiler. The compiler outputs the language generated files in the desired language and GRPC uses them to communicate between services. So let’s see the user.proto file.

The proto file is using proto3 syntax. We see that there are a couple of messages in this file representing request and response data. Then there is a service UserSvc defined that has four methods that leverage these messages. Essentially, these are four APIs that we would be building today. There is a way to load the proto file’s definition in runtime without compiling the file, but we are going to compile the file here because that would make our life much easier when we build other services. Let’s compile this proto file and store the results in userService/proto directory. Run the next command from the root Microservice-Demo directory.

grpc_tools_node_protoc \
    --js_out=import_style=commonjs,binary:userService/proto/ \
    --grpc_out=grpc_js:userService/proto \
    --proto_path=./protos/user ./protos/user/*.proto

Running this command will output two files in userService/proto directory, one is user.pb.js and another user_grpc.pb.js . We would need to require them in code next to build our APIs.

Building the service

Sowe have some APIs we are going to build, let’s start with user registration. We would install bcrypt for password hashing and jsonwebtoken for generating a JWT token for authentication.

This is a very basic NodeJS setup. Here we are importing the generated user_grpc.pb.js file. That gives us access to UserSvcService that we defined earlier in the proto file. We initialize a new GRPC service and add our API methods to it as services. Next, we bind the address that we get from .env and start the server. There’s some boilerplate code to connect to MongoDB and pass the db and grpc instance to API class. Let’s code out API class.

In the API class, we implement the register method. There are two parameters that have been passed to us by GRPC service definition, call and callback . The call parameter contains request information that we can access with call.get{ParamName} and callback is what gets returned from the method. It has two parameters, the first parameter takes error object and the second one response object.

We hash the password user has provided and then save the user to MongoDB. We then create the UserResponse message we made in the proto file earlier and set the necessary fields. The callback then returns the message. You can explore the token generation code here and the rest of the APIs of this service here. The full code is available here.

So we have coded our first API and now let's test it.

Docker Deploy

We have coded the application, now let’s write the Dockerfile to deploy it.

We are copying everything from the service directory and installing the packages here. Since we would also need MongoDB, running only this in docker would not be enough. Let’s write the docker-compose.yml file.

Let’s run this with docker-compose.yml up --build . We should see both MongoDB and our service is running successfully.

Testing

Since we have written a GRPC service, we cannot test it directly with any tool like Postman, well not yet. There are some tools out there that somewhat ease the process like BloomRPC but I like to test the service with real code.

So, we have a server and now we have to write a client to test it.

Here, we are importing the message and service files and creating a client by connecting to port 8080 since we port-forwarded it in the docker-compose file. When we run this client with node testClient.js we would see that the user is being registered and a new user entry getting created in MongoDB. It should print in the console the response that contains the created user information.

Whoa! That was a lot. But now we have a full functioning microservice written in NodeJS that is running a GRPC server that can accept incoming RPC requests and interact with the database.

Conclusion

Here we have explored user registration/authentication, in the next article, we will build the project service with Python and MySQL. Til then, stay tuned.