How to Deploy Your Go API

So you wrote a Go API (slay ✨), now you wanna put it out there so people can actually use it. Go is kinda OP here ‘cause it compiles into a single binary (aka just one file to move around). That makes deployment stupid simple compared to languages that need a million dependencies.

We are going to explore the following in this post:

• What kind of deployment options suit your needs
• How I deploy in a bare-metal or virtual server
• How I deploy using Docker
• How I deploy using Kubernetes
• How I deploy using serverless

How to Deploy a Go API

There’s a bunch of ways you can deploy, and each has its pros/cons. Let’s run through the main ones:

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🖥️ 1. Bare Metal (OG Style)

Basically: run your Go binary straight on a physical server.

• ✅ Pros:
  • Zero abstraction layers (so better performance).
  • Full control over your setup.
  • Great if your app is small/simple.
• ❌ Cons:
  • Scaling = pain. You literally have to buy/setup more servers.
  • Gotta handle everything yourself (logs, backups, monitoring, etc).
  • Can’t “downscale” if traffic drops—you already paid for the hardware.

👉 If you’re running a hobby project or a tiny startup with predictable traffic, bare metal might actually slap. Otherwise… mid.

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🖥️ 2. Virtual Machines (VMs)

Think of this as “fake computers” running on top of a real server. AWS EC2, Google Compute, etc.

• ✅ Flexible: spin up/down servers whenever.
• ✅ Pay as you go.
• ❌ Slightly slower (extra virtualization layer).
• ❌ Can get $$ if you don’t manage resources well.

👉 Good middle ground if you like control but don’t wanna mess with physical hardware.

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📦 3. Containers (Docker & friends)

Instead of pretending you have full hardware, containers just package your app + dependencies into a lil box.

• ✅ “It works on my machine” becomes “it works everywhere.”
• ✅ Easy to ship + run consistently.
• ❌ Need to learn Dockerfiles & image building.
• ❌ If you have tons of containers, it gets messy.

👉 Perfect for small to medium projects where you want reproducible builds & simple deployment.

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☸️ 4. Kubernetes (The Big Boss)

This is basically Docker on steroids. Kubernetes orchestrates tons of containers across clusters.

• ✅ Auto-healing, scaling, networking, load balancing… all built in.
• ✅ Industry standard for big apps.
• ❌ Steep learning curve (like, really steep 💀).
• ❌ Overkill if you’re just running 1–2 services.

👉 If you’re building something big or wanna flex devops skills, Kubernetes is the way.

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⚡ 5. FaaS / Serverless (AWS Lambda, etc)

Here you don’t even think about servers. You just upload a function, and it runs when triggered.

• ✅ Zero server management.
• ✅ Cheap if your app is event-driven & low-traffic.
• ❌ Limits (runtime, memory, cold starts).
• ❌ Hard to manage state & complex apps.

👉 Great for quick APIs, background tasks, or side projects. Not great for long-running, stateful systems.

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🛠️ Example Bare-Metal Flow (Simple Demo)

1. Build your Go binary: go build my-api.go
2. Copy it to your server: scp my-api user@server:/opt/my-api
3. Run it: /opt/my-api
4. (Better) Hook it into systemd so it auto-restarts if it crashes.

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🐳 Example Dockerfile (Container Flow)

FROM ubuntu:latest
WORKDIR /opt
COPY my-api .
RUN chmod +x my-api
EXPOSE 8080
CMD ["./my-api"]

Then:

docker build -t my-api .
docker run -p 8080:8080 my-api

Boom, your Go API is running in Docker.

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💡 TL;DR

Go API

1. Build your app

Go makes this easy, just compile it into one lil binary:

go build -o myapi main.go

Now you’ve got a single file myapi that runs anywhere (well, anywhere that matches your GOOS + GOARCH).

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2. Pick your deployment style

You got options, depending on vibes + scale:

• Bare Metal: throw the binary on a server & run it. Old school, works fine for hobby stuff.
• VMs (AWS EC2, GCP Compute, etc): a bit fancier, you control the OS + resources.
• Docker Containers: wrap your app into a container for consistency, easier shipping.
• Kubernetes: if you need scaling + self-healing, but steep learning curve.
• Serverless (AWS Lambda, etc): good for small functions or bursty workloads.

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3. Basic Deployment Example (Bare Metal / VM)

1. Upload your binary: scp myapi user@yourserver:/opt/myapi
2. Run it: /opt/myapi
3. (Optional) Set up systemd so it stays alive: [Unit] Description=My Go API After=network.target [Service] ExecStart=/opt/myapi Restart=always [Install] WantedBy=multi-user.target Then: sudo systemctl enable myapi sudo systemctl start myapi

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4. Containerized Deployment (Docker)

Dockerfile:

FROM golang:1.22-alpine AS builder
WORKDIR /app
COPY . .
RUN go build -o myapi main.go

FROM alpine:latest
WORKDIR /opt
COPY --from=builder /app/myapi .
EXPOSE 8080
CMD ["./myapi"]

Build & run:

docker build -t myapi .
docker run -p 8080:8080 myapi

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5. Scale & Go Pro

• Add Nginx or Caddy in front as reverse proxy (SSL, routing).
• Add monitoring (Prometheus, Grafana, or even just logs).
• Deploy with Kubernetes if you’re planning to go global 🌍.

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TL;DR 📝

1. go build → get your binary.
2. Upload → run it on server (bare metal, VM, or container).
3. Optional: wrap in Docker for portability.
4. Use systemd or Kubernetes for scaling & reliability.

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