Skip to content
Back to Stack Recommender

Microservices API Stack

Go + gRPC + PostgreSQL + Redis + NATS + OpenTelemetry for high-throughput microservice architectures.

API ServicesComplex

Stack Components

LanguageGo 1.23
RPCgRPC + Protobuf
DatabasePostgreSQL 16
CacheRedis 7
Message QueueNATS JetStream
ObservabilityOpenTelemetry + Jaeger
DeployKubernetes + Helm

Why

Go compiles to single binaries with 10x less memory than Node.js. gRPC is 3x faster than REST with built-in streaming. NATS handles 1M+ msg/s.

This stack serves 100k RPS with <10ms p99 latency.

When

Choose this for high-throughput APIs (>10k RPS), microservice architectures with 5+ services, and latency-critical systems (payments, real-time bidding). Overkill for simple CRUD apps.

How

1. Define proto — api/proto/user.proto with service + message definitions 2. Generate Go code — protoc --go_out=. --go-grpc_out=. api/proto/*.proto 3. Implement service — internal/service/user.go with gRPC server methods 4. Add PostgreSQL — sqlc for type-safe SQL queries, run migrations 5. Add Redis — caching layer with go-redis, TTL-based invalidation 6. Add NATS — event publishing on writes, subscription for projections 7. Tracing — OpenTelemetry SDK, spans for DB + cache + queue calls 8. Docker + K8s — multi-stage Dockerfile, Helm chart for deployment

Example

// api/proto/user.proto syntax = "proto3"; service UserService { rpc GetUser(GetUserRequest) returns (User); rpc CreateUser(CreateUserRequest) returns (User); } message User { string id = 1; string email = 2; string name = 3; } message GetUserRequest { string id = 1; } message CreateUserRequest { string email = 1; string name = 2; } // internal/service/user.go — gRPC implementation func (s *UserServer) GetUser(ctx context.Context, req *pb.GetUserRequest) (*pb.User, error) { ctx, span := tracer.Start(ctx, "GetUser") defer span.End() // Check cache first if cached, err := s.redis.Get(ctx, "user:"+req.Id).Bytes(); err == nil { var user pb.User proto.Unmarshal(cached, &user) return &user, nil } // Query database user, err := s.db.GetUserByID(ctx, req.Id) if err != nil { return nil, status.Errorf(codes.NotFound, "user not found") } // Cache for 5 minutes data, _ := proto.Marshal(user) s.redis.Set(ctx, "user:"+req.Id, data, 5*time.Minute) return user, nil }

Common Problems

  • ⚠gRPC debugging hard — no curl, use grpcurl or Postman gRPC, add reflection service
  • ⚠Protobuf breaking changes — adding required fields breaks old clients, use optional
  • ⚠Distributed tracing gaps — missing context propagation in NATS handlers breaks traces
  • ⚠Connection pool exhaustion — PostgreSQL max_connections hit, use pgxpool with limits

Best Practices

  • ✓Use buf for protobuf management — linting, breaking change detection, code generation
  • ✓Implement circuit breakers — sony/gobreaker to prevent cascade failures
  • ✓Use context deadlines — ctx.WithTimeout for all external calls, never block forever
  • ✓Structured logging with slog — correlate logs with trace ID from OpenTelemetry

FAQ

What is Microservices API Stack and what projects is it for?

Go + gRPC + PostgreSQL + Redis + NATS + OpenTelemetry for high-throughput microservice architectures. It pairs layered technologies for end-to-end type safety and out-of-the-box deploys, fitting everything from MVPs to production SaaS.

How do I spin up a working demo with Microservices API Stack in 10 minutes?

Two steps: (1) Define proto — api/proto/user.proto with service + message definitions; (2) Generate Go code — protoc --go_out=. --go-grpc_out=. api/proto/*.proto. Get the local dev server running, then wire one real data source to verify the end-to-end loop.

What is the most common pitfall with Microservices API Stack and how do I avoid it?

The most common pitfall is: gRPC debugging hard — no curl, use grpcurl or Postman gRPC, add reflection service. Avoid it by adding the matching checklist to your PR template and running type-check + lint + unit tests in CI — three gates before merge.

What are the best practices for Microservices API Stack?

Best practices for Microservices API Stack include: Use buf for protobuf management — linting, breaking change detection, code generation; Implement circuit breakers — sony/gobreaker to prevent cascade failures; Use context deadlines — ctx.WithTimeout for all external calls, never block forever. The first one — "Use buf for protobuf management — linting, breaking change detection, code generation" — should be set up at project init to avoid costly rework later.

When should I NOT choose Microservices API Stack?

Pick something else in three cases: (1) the team has zero experience with the core framework and the deadline is tight (learning-curve risk); (2) it's a pure content/marketing site (Astro is lighter); (3) you need very high throughput (>10k RPS) or strict-consistency microservices (Go/Rust). Microservices API Stack shines for mid-to-high complexity full-stack and API work — don't over-engineer simple static pages with it.