---
title: "Go Backend Systems"
description: "Go backend architecture consulting: service boundaries, event-driven design, resilience patterns and operability for high-throughput systems in regulated industries."
url: https://gqlteam.com/services/go-development/
markdown: https://gqlteam.com/services/go-development/index.md
type: services
date: 2025-01-01
lastmod: 2026-08-28
subtitle: "Services that stay fast, observable and boring under load"
stats: [{"label":"Payment throughput","value":"5K to 50K+ tx/hr"},{"label":"Latency on the critical path","value":"Sub-100ms"}]
---

# Go Backend Systems

Services that stay fast, observable and boring under load

> Go backend architecture consulting: service boundaries, event-driven design, resilience patterns and operability for high-throughput systems in regulated industries.

## Systems that hold under real traffic

Go earns its place in a backend when the system has to do a lot of work per second, with predictable latency, on hardware that does not cost a fortune. Getting there is an architecture problem more than a language problem: where the service boundaries sit, what happens when a dependency is slow, how work moves between services, and how an operator sees what is going on at three in the morning.

I design those systems and review the ones that already exist. The output is a set of boundaries, patterns and runbooks your team can keep applying after I leave.

## What I design

- **Service boundaries.** Decomposition with clear ownership and explicit contracts, so a change in one service stays in that service.
- **Event-driven flows.** Asynchronous work over NATS or Kafka where it decouples teams and absorbs spikes, synchronous calls where they keep things simple.
- **Resilience.** Circuit breakers, retries with backoff, timeouts, graceful degradation and health checks that mean something.
- **Performance.** Profiling and benchmarking of the paths that matter, then the specific fixes that move p95, not a blanket rewrite.
- **Operability.** Structured logs, metrics and traces that answer real questions, and Kubernetes-native scaling with thresholds someone has actually calculated.
- **Compliance-ready foundations.** Audit logging, encrypted data handling and role-based access built into the service layer for healthcare and payments.

## Ten times the transaction volume

A payment processor needed to grow from 5,000 to more than 50,000 transactions per hour while meeting PCI-DSS Level 1 requirements. I designed the Go microservices architecture for the payment path, isolated the cardholder data environment, and set the latency budget for each hop. The system reached the required throughput with sub-100 ms latency on the critical path, and the QSA audit passed on the first attempt.

5K to 50K+ transactions per hour, first-pass PCI audit

## What you receive

1. **Architecture decision records.** The rationale for each major choice, so the team understands the why and can revisit it later.
2. **Service boundary diagrams.** Ownership maps showing how services communicate, what each one owns and where the seams are.
3. **Performance benchmark report.** Baseline measurements, bottleneck analysis and targeted recommendations with expected results.
4. **Deployment runbook.** Deployment, rollback and incident procedures written for your infrastructure.
5. **Scaling strategy.** Horizontal scaling plan with resource estimates, autoscaling thresholds and capacity projections.

## Stack

Go, gqlgen, entgo, GORM, gRPC, PostgreSQL, MySQL, Redis, ElasticSearch, NATS, RabbitMQ, AWS, GCP, Terraform, Docker, Kubernetes. The reference implementation for how I structure Go services is open source: LabraGo, linked from the sidebar.

## Key figures

- Payment throughput: 5K to 50K+ tx/hr
- Latency on the critical path: Sub-100ms

## Questions

**Do you write the code or design the system?**

I design the system and review the code. When a team wants hands-on implementation, I bring in senior Go engineers I have worked with for years and stay on as technical lead.

**Is Go the right choice for us?**

For services where throughput, predictable latency and a small operational footprint matter, usually yes. For a CRUD app with ten users, the language is not the problem. I will tell you which case you are in.

**How do you handle compliance requirements in Go services?**

The same way as in any stack: audit logging, encryption at rest and in transit, role-based access and least privilege, designed into the service boundaries rather than added at the edge.

**What does the open-source work have to do with this?**

LabraGo is the Go and GraphQL platform I created and lead. It is the reference for how I structure services, and it is public, so you can read the code before you hire me.


Contact: https://gqlteam.com/contact/ | Book: https://cal.com/dan-podina-snqasy/30min | MCP: https://mcp.gqlteam.com/mcp