Migrating Rest Apis to gRPC in Spring Boot: What We Gained and What We Lost

As the demand for faster, more efficient microservice communication grows, many teams are exploring alternatives to REST. One of the most often discussed rivals is gRPC. It has a high-performance, open-source universal RPC framework. It is created by Google.
In this blog, we’ll walk you through Migration from REST APIs to gRPC in a Spring Boot environment – what we gain in terms of performance and structure, and what we lost for it.

What is gRPC?

Google Remote Procedure Calls is referred to as gRPC. It is a high-performance, open-source RPC (Remote Procedure Call) framework developed by Google. It also enables efficient and robust communication between services, based on HTTP/2 and using Protocol Buffers (protobuf) for serialization.

Remote Procedure Call: gRPC allows clients to directly invoke methods on a remote server as if it were a local object.
Protocol Buffers: Google Remote Procedure Calls(gRPC) uses a compact, language-agnostic, and platform-independent binary format to define and serialize the structure data.
HTTP/2 Support: grpc uses capabilities like multiplexing, flow management, and header compression to achieve low-latency, high-throughput communication.

If our original architecture was built in with REST APIs using Spring Boot and Spring Web. As we know REST is simple and widely supported, it shows some limitations as our system grew:

For the gRPC, it came with a set of advertised advantages or benefits and solutions to the limitations that you experienced in REST

We are replacing REST request/response DTOs with .proto definitions:

syntax = "proto3";
package com.example.grpc;

option java_multiple_files = true;
option java_package = "com.techprimers.grpc";

service GreetingService {
  rpc greeting(GreetingRequest) returns (GreetingResponse) {
  }
}

message GreetingRequest {
  string message = 1;
}
message GreetingResponse {
  string message = 1;
}

@GrpcService
public class GreetingServiceImpl extends GreetingServiceGrpc.GreetingServiceImplBase {
    @Override
    public void greeting(GreetingRequest request, StreamObserver<GreetingResponse> responseObserver) {
        String message = request.getMessage();
        System.out.println("Received Message: " + message);

        GreetingResponse greetingResponse = GreetingResponse.newBuilder()
                .setMessage("Received your " + message + ". Hello From Server. ")
                .build();

        responseObserver.onNext(greetingResponse);
        responseObserver.onCompleted();
    }
}

<plugins>
    <plugin>
        <groupId>org.xolstice.maven.plugins</groupId>
        <artifactId>protobuf-maven-plugin</artifactId>
        <version>0.6.1</version>
        <configuration>
            <protocArtifact>com.google.protobuf:protoc:${protobuf.version}:exe:linux-x86_64</protocArtifact>
            <pluginId>grpc-java</pluginId>
            <pluginArtifact>io.grpc:protoc-gen-grpc-java:${grpc.version}:exe:linux-x86_64</pluginArtifact>
        </configuration>
        <executions>
            <execution>
                <goals>
                    <goal>compile</goal>
                    <goal>compile-custom</goal>
                </goals>
            </execution>
        </executions>
    </plugin>
</plugins>

<dependency>
            <groupId>io.grpc</groupId>
            <artifactId>grpc-stub</artifactId>
            <version>1.73.0</version>
 </dependency>
 <dependency>
            <groupId>io.grpc</groupId>
            <artifactId>grpc-protobuf</artifactId>
            <version>1.73.0</version>
 </dependency>

Improved Performance: With the help of Protocol Buffers gRPC reduces the payload sizes and faster serialization/deserialization which improves the overall efficiency. In the gRPC, HTTP/2 enables the multiplexed streams, and it minimizes connection overhead and boost the speed.

Strong Contracts: We can achieve strict typing and schema enforcement using .proto files, which improves the API Consistency, collaboration between teams, and generated accurate documentation.

Streaming Capabilities: gRPC natively supports client-side, server-side and bidirectional streaming. It makes ideal for real time features like live updates and persistent data flows.

Code Generation: gRPC automatically generates client and server code (stubs) in various languages. This feature of gRPC simplifies the development across polyglot environments and also reduces the boilerplate code.

Human-Readability and Debugging Simplicity: As we know the JSON is easy to read and we can debug the code in tools like Postman or logs but the Protobuf is binary. It requires special tools to decode the code and makes debugging less straightforward.

Browser Compatibility: REST APIs work natively in browsers, but gRPC needs gRPC-Web or additional proxies to function in browser environments. So, the browser compatibility is adding complexity for frontend integration.

Steeper Learning Curve: For the gRPC, Teams had to get familiar with .proto files, streaming concepts, and new tools. Reading the plain REST logs is easy as compared to the debugging gRPC based issues which become more complex.

While the Migration came with challenges especially around tooling, debugging, and the learning curve. However, Migration isn’t a one-size-fits-all solution. gRPC best suits for internal APIs, real-time streaming, and low-latency services where performance matters most. For external-facing APIs, REST still holds strong due to its human-readability, tooling support, and browser compatibility.
In the end, our biggest takeaway is this: Don’t replace REST with gRPC blindly. Evaluate your use cases carefully. In many modern systems, a hybrid approach using REST and gRPC side by side can offer the best of both worlds.

https://medium.com/@giefferre/from-00s-to-20s-migrating-from-restful-to-grpc-5a5aa0cf27ba

https://blog.nashtechglobal.com/what-is-grpc-protocol-buffers-streaming-and-architecture/