Building Scalable Microservices with Go and gRPC

Introduction

Building microservices that can handle millions of requests requires careful consideration of communication protocols, error handling, and observability. In this post, I'll walk through my approach to building production-grade microservices with Go and gRPC.

Why Go for Microservices?

Go's simplicity, excellent concurrency model, and small binary sizes make it an ideal choice for microservices:

• Goroutines make concurrent processing trivial
• Fast compilation speeds up the development loop
• Static binaries simplify deployment and containerization
• Strong standard library reduces dependency bloat

package main

import (
    "log"
    "net"
    "google.golang.org/grpc"
    pb "github.com/example/proto"
)

type server struct {
    pb.UnimplementedUserServiceServer
}

func main() {
    lis, err := net.Listen("tcp", ":50051")
    if err != nil {
        log.Fatalf("failed to listen: %v", err)
    }
    
    s := grpc.NewServer()
    pb.RegisterUserServiceServer(s, &server{})
    
    log.Printf("server listening at %v", lis.Addr())
    if err := s.Serve(lis); err != nil {
        log.Fatalf("failed to serve: %v", err)
    }
}

gRPC vs REST

While REST is great for public-facing APIs, gRPC shines in service-to-service communication:

Error Handling Patterns

Proper error handling in distributed systems is critical. I use a layered approach:

1. Domain errors - Business logic validation
2. Infrastructure errors - Database, network failures
3. gRPC status codes - Standardized error communication

func (s *server) GetUser(ctx context.Context, req *pb.GetUserRequest) (*pb.User, error) {
    user, err := s.repo.FindByID(ctx, req.GetId())
    if err != nil {
        if errors.Is(err, ErrNotFound) {
            return nil, status.Errorf(codes.NotFound, "user not found: %s", req.GetId())
        }
        return nil, status.Errorf(codes.Internal, "internal error")
    }
    return toProto(user), nil
}

Observability

Every production microservice needs three pillars of observability:

• Logging - Structured logs with correlation IDs
• Metrics - Prometheus counters, histograms, gauges
• Tracing - Distributed traces with OpenTelemetry

Conclusion

Go and gRPC form a powerful combination for building microservices. The key is to keep services focused, handle errors gracefully, and invest in observability from day one.

What's your experience with Go microservices? Let me know on X!