Go development for high-throughput backends: concurrent data pipeline workers, APIs, and services that stay fast and cheap to run under real load.
When a scripting language stops keeping up
Plenty of systems start life as a Python script and hit a wall: one process cannot saturate the workload, memory climbs, and horizontal scaling multiplies infrastructure cost. Rewriting hot paths in Go typically collapses whole worker fleets into a handful of processes with better tail latency.
What we build with Go
- Data pipeline workers that process high-volume feeds concurrently
- REST and gRPC services with predictable latency under load
- CLI tooling and schedulers that deploy as single static binaries
- Targeted rewrites of hot paths inside existing systems
How we work
Profile the existing bottleneck before proposing a rewrite
Port the hot path first, keep the rest of the stack intact
Design for observability: metrics and tracing from day one
Load-test against production-shaped traffic before cutover
Typical stack
Frequently asked questions
Almost never. The wins concentrate in throughput-critical paths: ingestion, fan-out, API edges. We port those and leave product logic in the language your team ships fastest in.
As the muscle layer. Orchestration and transformation stay in Python and dbt where the ecosystem lives; Go handles the ingestion firehose and services where concurrency and cost per request dominate.