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SmartyDevs
Engineering · 10

Go services engineered the way Go rewards.

Performance-sensitive APIs, gateways, control planes and network tooling. Idiomatic Go that uses concurrency correctly, fails predictably and operates with very little ceremony.

§ 01The problem

The problem we solve

Go is at its best on workloads where latency, concurrency and operational simplicity matter — gateways, control planes, real-time fan-out, network and infrastructure code. It's at its worst when written like Java or Python by teams unfamiliar with idiomatic patterns. We've shipped Go in production for a decade and we know where the real wins are.

§ 02Capabilities

What we ship

  • 01HTTP APIs with chi, Echo, Fiber or stdlib net/http
  • 02gRPC services with buf, connect-go and protobuf discipline
  • 03Concurrent pipelines using goroutines, channels and errgroups correctly
  • 04High-throughput network services and proxies
  • 05Control planes and operators for Kubernetes
  • 06CLI tooling with Cobra and Bubble Tea
  • 07Database access with sqlc, pgx and Ent
  • 08Background workers and job queues with River or Asynq
  • 09Performance profiling with pprof, trace and benchstat
  • 10Observability with OpenTelemetry-Go and zerolog / slog
§ 03Deliverables

What you receive

  • Idiomatic, vet-clean Go codebase with race-detector in CI
  • Container image under 30 MB, ready for production
  • Benchmark suite and profiling baseline
  • Operational simplicity — Go services are easy to run
§ 04Stack

Stack we reach for

Go 1.22+
chi · Echo · stdlib
gRPC · buf · Connect
sqlc · pgx · Ent
River · Asynq · Temporal
Cobra · Bubble Tea
OpenTelemetry-Go
slog · zerolog
pprof · benchstat
Docker · Kubernetes
§ 05Ideal for

Ideal for

  • Teams whose Node / Python services hit CPU or memory walls
  • Infrastructure and platform engineering teams
  • Companies building gateways, proxies or control planes
  • Developer-tools companies shipping CLI binaries
  • Real-time fan-out and high-throughput workloads
§ 06Process

How an engagement runs

  1. 01

    Discovery & scope

    Workload profile, latency / throughput targets, integration surface. Written architecture proposal.

  2. 02

    Foundations

    Project layout, dependency management, CI with race-detector, observability scaffolding.

  3. 03

    Implementation

    Service built in vertical slices with benchmarks gating performance regressions.

  4. 04

    Profile & operate

    pprof-driven optimization passes. Deployment, observability, runbook handoff.

§ 07Engagement

How to engage

01

Go Audit

1 — 2 weeks

Code review, performance profile, architectural assessment with prioritized findings.

02

Greenfield Service

6 — 14 weeks

New Go service shipped end-to-end with documentation and benchmarks.

03

Performance Rescue

4 — 10 weeks

Existing Go service profiled, optimized and made operationally sound.

04

Embedded Go Team

3 — 12 months

Senior Go engineering inside your team, including review culture and mentorship.

§ 08Common questions

Frequently asked.

01Should we rewrite our Node service in Go?

Rarely the right call as a first move. Most performance wins in Node come from fixing the database, caching correctly and removing N+1s. We will tell you when Go is actually warranted.

02REST or gRPC?

gRPC for service-to-service in a typed ecosystem. REST + OpenAPI for public surfaces and frontends. Connect-go gives you both from the same definition.

03Do you work alongside our existing Go team?

Yes — we frequently embed alongside an existing Go team to accelerate specific work or transfer practices through pairing and review.

Have a problem worth solving well?

Tell us the outcome you want. We'll tell you what it takes — honestly, within a week, in writing.

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