Golang development company
Go services that stay predictable under concurrency: REST and gRPC APIs, Kafka and NATS consumers, CLIs, and Kubernetes operators, written with context-aware cancellation, race-tested CI, and the profiling hooks you need once traffic grows.
- Senior engineers · IST + EST overlap
- NDA on day 1
- 24-hour reply
- Projects shipped
- 50+
- Code ownership
- 100%
- Client rating
- 4.8/5
- First reply
- 24h
Go backends that stay fast and debuggable
Our Golang development company builds the parts of a backend that have to stay fast under concurrency: HTTP and gRPC APIs, event consumers, background workers, CLIs, and Kubernetes operators written in Go. Go fits well when you want small static binaries, quick builds, a strong standard library, and code that new engineers can read without a guide. It fits less well for data science that lives in Python, rich domain models that lean on heavy abstraction, or hard real-time systems that cannot tolerate garbage collection pauses. Krapton’s engineers pass context through every request path so cancellations and deadlines actually stop work, wrap errors with fmt.Errorf so callers can inspect them with errors.Is and errors.As, and run the race detector and govulncheck in CI. Services ship with structured logging through slog, OpenTelemetry traces, Prometheus metrics, and protected pprof endpoints, so the first production incident does not begin with guesswork.
Golang development services
REST and gRPC APIs
REST endpoints on the standard net/http router or chi, internal calls over gRPC or Connect, protobuf contracts managed with Buf, and generated clients for every service that consumes them.
Event-driven workers
Consumers for Kafka, NATS, or SQS with idempotent handlers, bounded worker pools, dead-letter handling, and backpressure, so a slow downstream system cannot exhaust memory or goroutines.
Kubernetes operators and controllers
Custom controllers built with controller-runtime and Kubebuilder that reconcile your own resources, handle finalizers correctly, and expose metrics for every reconcile loop.
Monolith to Golang extraction
High-traffic endpoints peeled out of a Ruby, PHP, Python, or Node.js monolith into Go services, with traffic mirrored first and routes switched only when responses match.
Profiling and tuning
CPU, heap, and goroutine profiles with pprof plus execution traces, followed by fixes for allocation hot spots, lock contention, and pool limits, each measured with benchmarks before and after.
Data access layers
PostgreSQL access through pgx and sqlc-generated queries, migrations with goose or Atlas, and transaction handling kept explicit rather than hidden inside an ORM.
Why teams choose Krapton for Golang
Senior engineers, fixed scope, and code you own — the things agencies promise and rarely deliver.
Concurrency reviewed line by line
Reviews trace every goroutine to the context that cancels it, check channels for blocked senders, and look for maps written from several goroutines, the usual sources of leaks and crashes.
Plain code on purpose
We favor the standard library, small interfaces defined where they are consumed, and explicit error handling, so your team inherits Go that reads like Go rather than a framework port.
Container-aware runtime settings
Services set GOMEMLIMIT for their memory budget and run on Go releases that size GOMAXPROCS from container CPU limits, avoiding throttling and out-of-memory kills on Kubernetes.
Vulnerability scans that read calls
govulncheck reports only vulnerabilities your code actually reaches, which keeps dependency alerts actionable, and golangci-lint with gosec enabled catches risky patterns before human review.
How a Golang project runs with Krapton
01
Service boundary mapping
Endpoints, queues, and data stores are assigned to each Go service, protobuf or OpenAPI contracts are drafted, and latency targets are agreed before any handler is written.
02
Walking skeleton first
A thin service reaches staging early with CI, container build, health checks, tracing, and deployment wired up, so later features land on a proven path.
03
Feature sprints with tests
Each feature arrives with table-driven unit tests, integration tests against real dependencies via testcontainers-go, and race-detector runs, all visible in pull requests you can follow.
04
Load test and release
Before cutover we run load tests with k6 or vegeta, compare profiles against targets, and release behind canaries with dashboards and alerts already in place.
The Golang stack we build with
Golang development: questions answered
What work should I hand to a Golang development company?
Backend systems where concurrency and operational simplicity matter most. Typical scopes are public REST APIs, internal gRPC services, event consumers, scheduled workers, command-line tools, and Kubernetes operators. A capable Golang development company such as Krapton also owns the operational side, meaning container images, health checks, metrics, tracing, and profiling, because a Go service nobody can observe in production is hard to keep fast.
Should we choose Go or Node.js for a new backend?
Choose Go when the service is CPU-bound, highly concurrent, or must run as a small static binary with predictable memory use. Choose Node.js when the team already writes TypeScript across the stack, the workload is mostly I/O glue, and shared types with the frontend remove real duplication. Plenty of companies run both, with Node.js in backend-for-frontend layers and Go for the core services behind them.
How do services move from another language to Go safely?
Endpoint by endpoint, with traffic evidence at each step. One bounded piece is rebuilt in Go, production requests are mirrored to it while the old service still answers, and responses and latency are compared. Once they match, routing switches for a slice of traffic, then all of it. Shared databases need care, usually by giving the new service ownership of its tables before old code is removed.
How do Go services scale on Kubernetes?
Horizontally, as long as the Go runtime knows its container limits. Go 1.25 sizes GOMAXPROCS from the container CPU limit by default, and setting GOMEMLIMIT keeps the garbage collector within the memory budget. Add autoscaling on meaningful signals, connection pooling for databases, and timeouts on every outbound HTTP client, since the default client has none. Those settings prevent the throttling and cascading timeouts that commonly hit Go services in containers.
Which factors set the budget for Golang development services?
Service count, integrations, and reliability targets set most of it. Other drivers are the number of endpoints and event flows in scope, data migration from an existing system, compliance work such as audit logging, and the seniority mix of the team. A technical call turns those factors into a written scope, and the estimate is built from that document rather than from a guess.
Ready to build? Tell us what you have in mind.
Send a short brief and a senior engineer will reply within one business day with next steps — no sales fluff.