Go (Golang)
Go is the language the cloud is written in — Kubernetes, Docker, Terraform, half the CNCF landscape — and it earned the position honestly: goroutines make high concurrency ordinary, single-binary deploys make operations simple, and the language is small enough that a team can actually maintain each other's code years later. Boring by design, and we mean that as praise.
We reach for Go where its virtues compound: services holding thousands of concurrent connections at predictable latency, Kubernetes operators that encode your operational knowledge into controllers, gateways and proxies on the request path where garbage-collection pauses would show, and the CLI tooling engineers copy to a box and run. Between our platform work and our agent work, there's usually a Go service in the load-bearing middle.
High-concurrency services
APIs, gateways, and streaming backends built for thousands of simultaneous connections at stable p99s.
Kubernetes operators
Custom controllers that automate your platform's operational knowledge — reconciliation loops done right.
Infrastructure tooling
CLIs and daemons that ship as one static binary and run anywhere.
Performance-critical paths
Request-path services where latency budgets are real and profiling is a habit.
Service rewrites that pay
The specific hot service that outgrew its runtime, rewritten with a benchmark to prove it.
When is Go the right choice over Python or TypeScript?
When concurrency, latency stability, or operational simplicity dominate: infrastructure services, high-throughput APIs, anything on the request path, anything you ship to someone else's machine. For ML-adjacent work Python's ecosystem wins; for product velocity TypeScript's stack unity wins. We use all three where each is strongest.
Should we write our own Kubernetes operator?
If you're running stateful or operationally complex workloads and a mature community operator doesn't exist — yes, it's how platform teams encode expertise into automation. If one exists, extend it. We've built and maintained both kinds; the maintenance cost is real, so the bar should be too.
Is Go relevant for AI systems?
In the infrastructure layer, very: inference gateways, routing and rate-limiting proxies, high-throughput ingestion — the components around the model where concurrency and predictable latency matter more than ML libraries. Model logic stays in Python; the traffic it rides on is frequently Go.
Put Go (Golang) to work — in production.
One forward-deployed engineer, embedded in your stack, owning the outcome from discovery to production. Weeks, not quarters.
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