Why Flexprice Picked Go From Day One And Never Looked Back

#go #programming #ai #webdev

When you're building the backbone of usage-based billing, pricing, and metering, the language you select isn't just syntax. It’s the speed, and trust baked into your product.

At Flexprice, we didn’t stumble into Go.
We chose it deliberately before a single line of code was written.

Here’s why we picked Go over the more familiar paths, how it powers our architecture today, and why we’re glad we never defaulted to Python.

We needed something production-grade from the first commit.

1. The Problem We Were Solving

From day one, we knew what we were building wasn’t a toy:

APIs that would meter high-frequency usage events in real time
Pricing engines that needed to be deterministic, fast, and scalable
Billing infra that integrates deeply with CRMs, Stripe, analytics, and internal ops
A system that could handle thousands of events per second, without choking

We didn’t want to “move fast and break things.”
We wanted to “ship fast, scale clean, and sleep well.”

2. What Were the Available Options?

We considered the usual suspects:

Python: Familiar, flexible, and widely used — but not built for concurrency at scale
Node.js: Lightweight and async-friendly, but not ideal for CPU-bound operations
Java/Kotlin: Powerful, but verbose and heavy for a fast-moving startup
Go: A compiled, modern systems language designed for cloud-scale infrastructure

Despite being less familiar to some of us, Go stood out for its simplicity and power.

We ran tests. We built a few core modules. We profiled latency, deployment, and developer experience.

The results were clear.

3. Why We Chose Go

💡
Go was everything we needed — and nothing we didn’t.

✅ Compiled performance: Near-C-level speed
✅ First-class concurrency: Goroutines and channels made parallelism feel natural
✅ Dead-simple deployment: Static binaries, no runtime issues
✅ Readable and enforced syntax: The same formatting across every file, every repo
✅ Robust tooling: Built-in race detectors, benchmarks, linters
✅ Minimal memory footprint: Runs smoothly on small container instances

Go didn’t just check boxes. It rewired how we think about backend design.

4. What It Powers Today

Here’s what we’re handling today on production:

1M+ usage events/day per customer (batch and real-time ingestion)
Pricing workflows that respond in under 50ms, even on minimal compute
High-volume API traffic integrated with Stripe, customer portals, and sales workflows
Rapid iteration across entitlements, billing logic, and packaging — with confidence

Even on 0.2 vCPU instances, Go performs like a beast.

5. How We Structured Our Go Backend

Flexprice is open source and built in Go with a modular, scalable architecture designed for high performance and easy extensibility.

You can explore the codebase here.

We’ve kept the structure intentionally clean so developers can read, adapt, and contribute with minimal friction.

Building something similar? Fork it. Want to improve it? Open a PR.

We’re building in public, and we’d love your input.

But what we got in return?

Peace of mind with every deploy
Confidence that scale won’t require rewrites
Codebases that any dev can read and extend in minutes * * *

6. The Tech Deep Dive — For Developers Who Care About the Guts

We’ve talked about why we chose Go.
Now here’s a peek into how it actually runs under the hood.

Architecture Highlights

Event Ingestion Layer
- Uses goroutines for parallel processing of incoming usage events.
- Kafka + Go consumers with backpressure handling to keep ingestion smooth at millions of events/day.
Pricing Engine
- Deterministic pricing logic, no floating-point surprises — all billing calculations are done with Go’s math/big for precise decimal handling.
- Config-driven rules so business teams can tweak pricing without touching code.
API Layer
- Built with net/http + middleware stack for logging, auth, and rate limiting.
- gRPC endpoints for high-throughput internal communication between services.
Storage & Persistence
- Postgres as the source of truth for billing and pricing configs.
- Redis for caching entitlements, pricing tiers, and in-flight usage aggregates.
Deployment
- Each service is a single static binary — no dependency hell, no runtime surprises.
- CI/CD with GitHub Actions → container builds → K8s deploys.
- Health checks + metrics exposed via Prometheus.

Performance Practices We Swear By

Pre-allocating slices and avoiding unnecessary memory allocations
Using worker pools for predictable goroutine lifetimes
Benchmarking every pricing rule with Go’s built-in testing.B suite
Leveraging Go’s pprof for real-time profiling in staging and production

TL;DR — We treat performance as a feature, not an afterthought.

Final Thoughts

We didn't just pick Go for the hype. We picked it for the long game.
Flexprice isn’t just a billing product — it’s the backbone of revenue for companies shipping AI, infra, and complex usage-based products.

And Go gives us the confidence to say:

Bring on the scale. We’re ready.