Native performance
Compiled to a native binary, Go starts almost instantly and uses little memory, which matters for containers and serverless functions.
Expertise · Go
Golang Development: fast, lean cloud services
Etixio delivers custom Golang development for your services and tools: APIs, microservices, concurrent processing and infrastructure components, designed to be simple to operate. We build, take over and ship to production, including the services that orchestrate your calls to AI models.
Understanding the technology
Go in your project.
Go is a compiled language used in particular to build services and infrastructure tools. Its concurrency model makes it possible to organize multiple operations, but reliability still depends on how timeouts, errors and resources are handled. We approach it from the expected behavior of the service.
The strengths for your product
Why choose Go (Golang)?
Go, created at Google and open source, has become a standard for cloud services and distributed systems. It combines a deliberately simple language with strong performance and frictionless deployment.
Built-in concurrency
Goroutines, channels and the context package make it possible to handle many simultaneous connections, with explicit timeouts and cancellation.
Designed for the cloud
Docker, Kubernetes, Prometheus and Terraform are written in Go; its ecosystem is built for containers and microservices.
Simple deployment
A single binary with no runtime dependencies, cross-compiled for multiple architectures (amd64, arm64) from the same machine.
Code that is easy to read
Minimal syntax, standard formatting, built-in testing and profiling tools, a comprehensive standard library; one team can easily pick up another team’s code.
Our scope of work
The work we take on.
Services
Define component interfaces, responsibilities and configuration.
Concurrency
Organize parallel processing, timeouts and operation cancellation.
Performance
Measure allocations, latency and load before targeting optimizations.
Our Go expertise
The Go stack we master.
Web & APIs
The net/http standard library, Gin, Echo or Chi depending on the need, with documentation and clients generated from OpenAPI.
Service-to-service communication
gRPC and Protocol Buffers for typed, high-performance exchanges, with backward-compatible schema evolution.
Data
PostgreSQL with pgx and its connection pool, MongoDB with the official driver, Redis for caching, sessions and pub/sub; sqlc, Squirrel or GORM depending on the desired level of abstraction.
Cloud & observability
Multi-architecture containers, Kubernetes and operators written in Go, Prometheus and Grafana metrics, distributed tracing with OpenTelemetry.
The right tool in the right place
When to choose Go over another language?
High-load APIs and microservices
When latency, resource consumption and the number of simultaneous connections are decisive.
Infrastructure and operations tools
Agents, command-line tools, Kubernetes operators, gateways and technical services that need to be simple to deploy.
Gateways and services around AI
A Go service can centralize calls to models: authentication, rate limiting, caching, logging and cost tracking, while the richer AI logic stays in Python.
When to prefer another language
For a web application rich in screens and business rules, a more complete framework such as Django, Symfony or Spring can be more productive. For data science, Python remains the reference.
Go and AI
Reliable AI services in production.
The major model providers offer Go SDKs. We use it for components where operational robustness comes first — model gateways, document queue processing, concurrent calls with timeouts and cancellation — as part of enterprise AI solutions that are deployed to production and maintained.
In the field
From technology to real-world use.
A service that aggregates data from several APIs must limit waiting time and keep a defined behavior if one of the partners fails. We plan for cancellation, concurrency limits and acceptable partial responses. Tests simulate slowdowns and errors to verify behavior beyond the happy path.
The choices that matter
The choices to examine before building.
Adding more parallel processing is not a performance strategy in itself. We measure load, allocations and latency, then target the optimizations that matter. Interfaces between packages and process configuration must remain understandable for the operations team.
From work to deliverables
Delivery your team can take over.
The scope of the engagement specifies the components to build or take over and the acceptance criteria. We prepare what is needed to understand the changes, verify them and continue the work.
- Services and API contracts
- Business rule tests
- Deployment procedures
Frequently asked questions
Go development: your questions.
What is Go (Golang) and why use it?
Go is an open-source language created at Google, designed for concurrency, cloud services and distributed systems. It combines a simple syntax with the performance of a compiled language, making it a good choice for microservices and infrastructure.
Is Go faster than Node.js or Python?
Generally yes, especially for compute-intensive processing and heavily loaded services, thanks to native compilation and goroutines. The real gap depends on the workload; we measure on your use cases rather than relying on benchmarks.
When should you choose Go over Node.js or Python?
Go for high-load APIs, microservices and infrastructure tools. Node.js for real-time web applications close to the front end. Python for data and AI. All three often coexist within the same architecture.
Does Go have frameworks like Spring or Django?
Go favors its standard library (net/http) and lightweight frameworks such as Gin or Echo. There are fewer built-in features, but more control and predictability; projects are organized by functional domain.
How do you handle databases with Go?
With native drivers (pgx for PostgreSQL, the official MongoDB driver, go-redis) and lightweight tools such as sqlc or Squirrel. GORM is available for more conventional needs; SQL generally stays explicit.
How do you deploy a Go application?
A single binary to ship, most often in a lightweight Docker image, on Kubernetes or on managed services such as Cloud Run, AWS Lambda or Azure Container Apps.
Can Go be used for AI features?
Yes, for services that call models and need to handle production load (gateways, queue processing, call orchestration), thanks to the providers’ Go SDKs. Data preparation and evaluation often remain in Python.
What collaboration models do you offer?
A fixed-price project for a defined scope, a dedicated team to evolve your services over time, or a targeted engagement: performance, migrating a service to Go, infrastructure tooling.
Let’s talk about your technical context.
Tell us about the application, the issue to address and the known constraints. We will review the dependencies and the first scope of work with your team.