Go services that ship in 6 weeks and survive year 3.
For teams who want compile-time safety, predictable performance, and operational simplicity. We have written Go services that have not crashed in production since 2023.
Why teams pick Go and what they get wrong.
Most teams pick Go for two reasons: they need predictable performance, or they need operational simplicity. They get themselves into trouble by reaching for the wrong patterns from the start. Channels for everything (when a mutex would do). Microservices for the start (when a modular monolith would ship faster). Custom HTTP routers (when net/http would have been fine). We have inherited enough Go codebases written by Java developers and JavaScript developers to know which patterns to encourage and which to extract.
What changes when a Metafic pod is in your repo.
Modular monolith first, microservices later if needed
Internal packages with clear interface boundaries. We split into services only when the deployment model actually demands it.
sqlc for type-safe SQL, not GORM
Generated typed accessors from SQL queries. The compile-time guarantees you actually want from Go applied to your database layer.
gRPC for service-to-service, JSON for the edge
When you have multiple Go services, gRPC pays back fast. We do not push gRPC out to consumers who do not want it.
context.Context wired everywhere from day one
Cancellation, timeouts, tracing IDs. Not added later. We use the linter that fails the build if a function takes ctx but does not propagate it.
OpenTelemetry, not custom log lines
Traces and structured logs from week one. Distributed tracing across services is the only way to debug Go at scale.
Who is on the pod for this work.
Pods scale up from here for Enterprise engagements.
Has shipped Go services at scale. Knows when to reach for sync.Pool and when to leave it alone.
5+ years Go, comfortable with goroutine lifecycle management and profiling pprof output.
Table-driven tests as the default. testcontainers for integration tests against real Postgres/Redis.
Tuned to read Go idioms (not Java-style Go), generate sqlc query files, and propose context-propagation fixes.
The bugs that bite this stack.
Goroutine leaks from missing context cancellation
A request times out, the goroutine it spawned keeps running. We catch these with leak-tested integration suites.
Channel patterns where a mutex would be simpler
Channels are great for some patterns and terrible for others. Most "elegant" Go code we inherit uses channels where sync.Mutex or sync.Map would be clearer.
time.Time without timezone discipline
A UTC timestamp parsed as local on the read side. Classic. We use the linter and the integration tests to catch it.
Database connection pools sized wrong
Go can saturate Postgres faster than Postgres can keep up. We tune SetMaxOpenConns based on actual database hardware, not the default.
Honest about scope.
We will not write Go for a team that does not have at least one senior engineer who wants to learn it. Go is a great language. It is a worse choice if nobody on your team wants to maintain it after we leave.
Common questions.
Go or Rust in 2026?
Go for almost everything where performance is "good enough but predictable" matters more than peak performance. Rust for systems where the latency tail genuinely matters or where unsafe memory management would be a liability.
Should we use a framework like Echo or Fiber?
net/http is fine for 90% of services. chi or gorilla/mux when you want routing helpers. The big frameworks are mostly unnecessary for the work most teams ship.
gRPC or REST?
gRPC for internal service-to-service. REST or JSON-over-HTTP for external consumers. Mixed stacks are normal.
What database client should we use?
sqlc for query-typed code, the standard lib database/sql or pgx for direct work. Avoid heavy ORMs unless your team specifically prefers that style.
Ready to scope it?
A 25-minute call. We will tell you what we would do, what we would not, and whether a pod is the right shape.
Or stay in the loop. One engineering teardown a week.