Building Microservices in Go

Go was designed for exactly the kind of work that microservices demand: handling many concurrent network connections, compiling to a single static binary, and starting in milliseconds. Where a Java service needs a JVM and a Node service needs a runtime, a Go binary is a self-contained executable that you drop into a scratch or distroless Docker image. The result is container images measured in megabytes rather than hundreds of megabytes, with startup times fast enough that Kubernetes liveness probes pass on the first check.

A typical Go microservice has three responsibilities: serve HTTP requests, consume messages from a queue, and read or write data to a store. The standard library’s net/http package is production-ready — you do not need a framework for basic routing and middleware. For more complex APIs, libraries like chi or Echo add pattern matching and middleware chaining without heavy abstractions. The key architectural decision is keeping your HTTP handlers thin: they parse the request, call a service layer, and serialize the response. Business logic lives in the service layer, which is unaware of HTTP and can be tested with plain function calls.

For asynchronous workloads, SQS is a reliable and simple message queue. Your Go service polls SQS using the AWS SDK, processes each message, and deletes it on success. The goroutine model makes it natural to process multiple messages concurrently — spin up a worker pool of goroutines, each pulling from a shared channel, and you have parallel message processing with bounded concurrency. If a message fails, SQS automatically retries it after the visibility timeout expires. After a configurable number of failures, the message moves to a dead-letter queue for manual inspection.

Data access in Go is straightforward but opinionated. The database/sql package provides a connection pool and a query interface for PostgreSQL . Libraries like sqlx add struct scanning and named parameters without introducing an ORM. For Redis , the go-redis library covers everything from simple key-value operations to pub/sub and Lua scripting. The pattern I recommend is a repository layer that accepts a context, executes a query, and returns domain structs. This keeps database concerns isolated and makes it trivial to swap implementations for testing.

Deploying Go microservices on Kubernetes is where the compilation model pays off. Multi-stage Docker builds — a builder stage that compiles the binary, and a runtime stage that copies it into a minimal base image — produce tiny, secure containers. Define a Kubernetes Deployment with resource requests and limits, a horizontal pod autoscaler based on CPU or custom metrics, and a service for internal routing. The binary’s low memory footprint means you can run more replicas per node, and the fast startup means the autoscaler can respond to traffic spikes in seconds rather than minutes. Add a readiness probe on your /health endpoint, and Kubernetes handles the rest.