Hey devs!

Over the years, I've worked with a ton of stacks--Go, Rust, Elixir, and more--and along the way, I've gathered tips, patterns, and battle scars that I couldn't find all in one place.

This is my attempt to fix that. 🎯

About Me

I've spent the last few years building production systems across various industries. I've had to wire up all the difficult parts that tutorials often skip: auth flows, payment processing, search optimization, and robust error handling. My goal is to share what I've learned the hard way so you don't have to.

The Series

I'm kicking off a Polyglot Apps series where I'll build real-world apps in different stacks--not just "Hello, World!" demos, but apps with proper project structure, authentication, background jobs, uploads, search, payments, and more.

Here's the lineup:
Go:

Go Fiber
Go Gin
Go net/http

Rust:

Axum + Tera
Actix + Tera
Warp + Tera
Rocket + Tera

Elixir:

Phoenix + Absinthe (GraphQL)
Phoenix LiveView
Phoenix Full-stack (non-LiveView)

What makes this different?

Each app will cover real use cases:

OAuth, magic links, 2FA 🔐

File uploads with MinIO 📂

Search with Typesense 🔍

Stripe billing 💳

HTMX/AlpineJS for frontend interactivity ⚡

Background jobs with RabbitMQ/Kafka 🐇

Streaming responses

Clean project structure and best practices I've learned the hard way

Additional Focus Areas

Database Strategies: I'll cover both SQL (PostgreSQL) and NoSQL (MongoDB) implementations where appropriate, including migration strategies and ORM/query builder approaches

Testing Approaches: Each stack has different testing paradigms - I'll demonstrate best practices for unit, integration, and end-to-end testing

Containerization & Deployment: Docker configurations and deployment pipelines for each stack

Performance Comparisons: Real benchmarks with analysis on throughput, latency, and resource usage

Error Handling & Observability: Proper logging, monitoring, and error tracking in production

Caching Strategies: Implementation of various caching layers (Redis, in-memory, CDN)

Security Considerations: OWASP top 10 mitigations specific to each stack

Bonus Advanced Topics

After covering the core implementations, I'll expand into AI integration with:

Ollama Open Source Models: Adding language translation capabilities

Computer Vision: Implementing face recognition features

Vector Databases: Storing and querying embeddings for semantic search

RAG Systems: Building simple retrieval-augmented generation systems

These advanced topics will demonstrate how modern applications can leverage AI capabilities without relying solely on third-party APIs, giving you more control and potentially reducing costs.

Timeline & Code Access

I'll be releasing a new implementation every 2-3 weeks. All code will be available in GitHub repositories with comprehensive documentation. Each repo will include a working demo you can run locally with minimal setup.
Why am I doing this?

Because picking the "right" stack can feel overwhelming.

By building the same core features across different stacks, I hope to give you real-world insights into how they compare in performance, developer experience, and ecosystem strengths.
Follow the journey!

I'll be posting the series on thedeveloper.tech and sharing highlights here on dev.to as well. The first few articles will cover why I chose these stacks and how I structure my projects, followed by deep dives into each app.

Let's learn together! 💪