Our API crashes when traffic spikes — should we rewrite in Go?

High-traffic API services rewritten in Go — without rewriting the whole product.

Identify the hottest microservices, rewrite only those in Go, and add a memory cache that absorbs spikes.

Talk to us about this See: Refactor & performance

Signs this is your problem

You will recognise yourself in at least one of these

Server crashes under traffic surges that should be manageable.
CPU pegs while throughput plateaus — adding instances barely helps.
Latency on hot endpoints is two to ten times higher than it should be.
Server bills keep climbing as you scale horizontally.

Why it happens

The root cause, in plain language

Some workloads (high-concurrency, low-latency, data-heavy) hit the limits of frameworks that were never optimised for them. Go is a much better fit for that specific shape of work — but only for the parts that actually need it.

Our approach

How we actually fix this

1
Identify the heaviest data-processing microservices through real profiling.
2
Rewrite only those in Go (Golang), keeping the rest of the stack intact.
3
Combine with a robust memory cache (e.g. Redis) for high-volume reads.
4
Continuously track API response times and update autoscaling rules monthly.

What you can expect

Outcomes our clients see

Server resource costs reduced by ~60% on the rewritten services.
Concurrent traffic handled without degradation.
Continuous monitoring keeps the gains as traffic patterns shift.

Case study

Mobile backend — high-traffic API rewrite to Go

A rapidly growing mobile app experiencing server crashes because its old framework couldn't handle concurrent user spikes. We rewrote the heaviest microservices in Golang with a robust memory cache. Server costs dropped by 60%.

See more of our work →