Technology
Go
Concurrent, boring, fast to compile and hard to write cleverly — which is exactly what you want in a payment path.
A language with a small surface is an operational advantage
Go's constraints are the point. Limited abstraction means the code an engineer reads under incident pressure is close to the code that runs, and onboarding takes days rather than months.
We use it for services where latency predictability, memory behaviour and operational clarity matter more than expressiveness.
Practice
How we use it
Service architecture
Explicit dependencies, context propagation and interfaces defined by the consumer rather than the implementation.
Concurrency
Goroutines and channels used where they clarify the problem, with cancellation handled properly throughout.
Observability
Structured logging, metrics and tracing built into service scaffolding rather than added under pressure.
Deployment footprint
Static binaries and minimal containers, which makes both the security surface and the cold start small.
Judgement
When Go is the right call
And when it is not. A technology page that only lists strengths is a brochure.
Reach for it when
- Latency-sensitive services with predictable resource behaviour
- High-concurrency workloads — gateways, ingestion, event processing
- Teams that need new engineers productive within a week
Look elsewhere when
- Data science and ML workloads, where the Python ecosystem is decisive
- Domains needing rich type-level modelling — the type system is deliberately modest
Sectors
Where we run it
Proof
Related work
Also relevant