GRPC beautiful architecture

Why gRPC?

gRPC is a modern open source high performance RPC framework that can run in any environment. It can efficiently connect services in and across data centers with pluggable support for load balancing, tracing, health checking and authentication. It is also applicable in last mile of distributed computing to connect devices, mobile applications and browsers to backend services.

In gRPC, a client application can directly call a method on a server application on a different machine as if it were a local object, making it easier for you to create distributed applications and services. As in many RPC systems, gRPC is based around the idea of defining a service, specifying the methods that can be called remotely with their parameters and return types. On the server side, the server implements this interface and runs a gRPC server to handle client calls. On the client side, the client has a stub (referred to as just a client in some languages) that provides the same methods as the server.

Working with Protocol Buffers

By default, gRPC uses Protocol Buffers, Google’s mature open source mechanism for serializing structured data (although it can be used with other data formats such as JSON). Here’s a quick intro to how it works. If you’re already familiar with protocol buffers, feel free to skip ahead to the next section.

The first step when working with protocol buffers is to define the structure for the data you want to serialize in a proto file: this is an ordinary text file with a .proto extension. Protocol buffer data is structured as messages, where each message is a small logical record of information containing a series of name-value pairs called fields. Here’s a simple example:

message Person {
string name = 1;
int32 id = 2;
bool has_ponycopter = 3;

Then, once you’ve specified your data structures, you use the protocol buffer compiler protoc to generate data access classes in your preferred language(s) from your proto definition. These provide simple accessors for each field, like name() and set_name(), as well as methods to serialize/parse the whole structure to/from raw bytes. So, for instance, if your chosen language is C++, running the compiler on the example above will generate a class called Person. You can then use this class in your application to populate, serialize, and retrieve Person protocol buffer messages.

You define gRPC services in ordinary proto files, with RPC method parameters and return types specified as protocol buffer messages:

// The greeter service definition.
service Greeter {
// Sends a greeting
rpc SayHello (HelloRequest) returns (HelloReply) {}

// The request message containing the user's name.
message HelloRequest {
string name = 1;

// The response message containing the greetings
message HelloReply {
string message = 1;
}RPC methods

gRPC uses protoc with a special gRPC plugin to generate code from your proto file: you get generated gRPC client and server code, as well as the regular protocol buffer code for populating, serializing, and retrieving your message types. You’ll see an example of this below.

  • A simple RPC where the client sends a request to the server using the stub and waits for a response to come back, just like a normal function call.
  • A server-side streaming RPC where the client sends a request to the server and gets a stream to read a sequence of messages back. The client reads from the returned stream until there are no more messages. As you can see in our example, you specify a server-side streaming method by placing the stream keyword before the response type.
  • A client-side streaming RPC where the client writes a sequence of messages and sends them to the server, again using a provided stream. Once the client has finished writing the messages, it waits for the server to read them all and return its response. You specify a client-side streaming method by placing the stream keyword before the request type.
  • A bidirectional streaming RPC where both sides send a sequence of messages using a read-write stream. The two streams operate independently, so clients and servers can read and write in whatever order they like: for example, the server could wait to receive all the client messages before writing its responses, or it could alternately read a message then write a message, or some other combination of reads and writes. The order of messages in each stream is preserved. You specify this type of method by placing the stream keyword before both the request and the response.

Communication flow

If anyone want the complete project, you can download the project in the next link.

Thanks for all, and give me a star in github 💪



Get the Medium app

A button that says 'Download on the App Store', and if clicked it will lead you to the iOS App store
A button that says 'Get it on, Google Play', and if clicked it will lead you to the Google Play store