High-Performance Backend Development
Your app is brilliant. Your backend should be too. I build blazing-fast, memory-efficient, and massively scalable APIs and backends with Go and Rust—the languages of modern cloud infrastructure.
Schedule a Technical ConsultationYour Backend is Costing You Users and Money
In a world of fleeting attention spans, speed is not a feature; it's the foundation of user trust. A slow API, a lagging database query, or a server that crashes during a traffic spike doesn't just frustrate users—it drives them to your competitors. For startups, this problem is magnified.
Traditional backend choices, while easy to start with, often create a "performance debt" that comes due when you can least afford it:
- High Server Bills: Inefficient code requires more powerful (and expensive) servers to do the same amount of work. As you scale, your cloud hosting costs spiral out of control.
- Poor User Experience: Every extra 100ms of loading time increases bounce rates. A slow backend means a slow app, leading to churn and negative reviews.
- Scalability Nightmares: The architecture that works for 100 users collapses at 10,000. Re-architecting a live product is a costly and risky distraction from growing your business.
- Reliability Issues: Memory leaks and unhandled concurrent requests in less strict languages lead to unpredictable crashes and downtime, eroding customer confidence.
A slow backend is a silent startup killer. Performance isn't an afterthought; it's your competitive edge.
The Modern Alternative: Go & Rust
The world's most demanding systems—from Google's infrastructure to Dropbox's storage engine and Cloudflare's edge network—aren't built with traditional scripting languages. They're built with compiled, concurrent, and memory-safe languages designed for the cloud era. This is where I focus.
Go (Golang): The Speed of Simplicity
Built by Google for concurrency and networking, Go is perfect for building extremely fast and scalable APIs and microservices. Its simplicity leads to readable, maintainable code that's easy to deploy and scales effortlessly.
Rust: The Power of Safety
For when performance and correctness are non-negotiable. Rust provides fearless concurrency and guaranteed memory safety without a garbage collector, making it ideal for CPU-intensive tasks, embedded systems, and services where every nanosecond counts.
Go vs. Rust: Which is Right For Your Project?
Choosing the right tool is the first step to success. Both are exceptional, but they excel in different areas. This is not just a technical choice; it's a business decision.
Choose Go For...
Speed of development and iteration. Go's simplicity and powerful standard library are optimized for getting robust, concurrent services to market quickly.
- Network services & APIs
- SaaS backends & microservices
- Data processing pipelines
- Command-line tools
Choose Rust For...
Absolute control over performance and memory. Rust's compile-time guarantees make it the choice for systems where failure is not an option.
- CPU-intensive computations
- Embedded systems & IoT
- Real-time applications
- Building infrastructure (e.g., databases)
As a developer focused on both, I can provide unbiased advice on the best technology for your specific goals. My approach is detailed further in my philosophy on focused work.
Why Not Just Use Node.js or Python?
While excellent for many use cases, traditional choices have trade-offs in performance-critical scenarios. Here's how Go and Rust provide a strategic advantage for your MVP.
Compiled to native machine code. Orders of magnitude faster.
Goroutines & Async makes scaling trivial.
Lower server costs, more efficient resource use.
Strict type systems and memory safety eliminate entire classes of bugs.
No dependencies. Just copy the file and run.
From Theory to Practice: Technical Solution Blueprints
Talk is cheap. Here’s a look at how I approach complex backend problems. These are not case studies from past clients, but demonstrative blueprints that showcase the architectural thinking I bring to every project.
Blueprint 1: Real-Time IoT Data Ingestion API in Rust
The Challenge: A service needs to handle thousands of concurrent connections from IoT devices, process incoming data packets with minimal latency, and write to a time-series database reliably.
Architectural Approach:
- Framework: Built on Tokio and Axum for a high-performance, non-blocking web server capable of managing massive I/O.
- Memory Safety: Rust's ownership model guarantees no data races or null pointer exceptions, which is critical for a service that must run 24/7 without memory leaks.
- Data Handling: Used `serde` for zero-cost deserialization of incoming JSON/binary data into strongly-typed Rust structs.
- Outcome: A system with sub-millisecond response times, a tiny memory footprint per connection, and proven reliability under heavy load simulations.
Blueprint 2: Scalable Microservice for a BI Dashboard in Go
The Challenge: A business intelligence SaaS needs a new microservice to fetch data from five third-party APIs (e.g., Stripe, Google Analytics), aggregate it, and expose a single, fast endpoint for the frontend dashboard.
Architectural Approach:
- Concurrency Model: Leveraged Go's native goroutines and channels to make parallel requests to all five external APIs simultaneously, dramatically reducing total data-fetch time.
- Simplicity & Maintainability: Used only Go's powerful standard library (`net/http`, `encoding/json`), resulting in a lean, dependency-free binary that is easy to maintain and deploy.
- Error Handling: Implemented robust error handling and timeout patterns (e.g., `context`) to ensure that if one external API is slow or fails, it doesn't bring down the entire aggregation service.
- Outcome: A service that replaces a slow, complex "Zapier alternative" with a single, fast endpoint, reducing frontend load times from seconds to milliseconds and lowering server costs.
When is a High-Performance Backend the Right Choice?
This approach is ideal for ambitious projects where performance and scalability are key to success. If your business model depends on any of the following, you're in the right place.
SaaS & Web Application MVPs
Build a backend that can handle your first 100,000 users without a rewrite. Start lean and scale confidently without hitting a performance ceiling.
Real-Time Data Processing
Power live dashboards, chat applications, or financial data streams. Go's concurrency model is tailor-made for handling thousands of simultaneous connections.
IoT & Edge Computing
When you need to process data from thousands of devices with minimal latency and a tiny memory footprint, Rust and Go are the undisputed champions.
API-as-a-Product
If your core business is selling API access, reliability and response time are your currency. Build a product your customers can depend on with a rock-solid foundation.
My Backend Development Process
I combine agile methodology with a focus on robust architecture to deliver a backend that is not only fast, but also maintainable and ready for future growth.
- Architecture & Design: We start with a deep dive into your business logic and scalability requirements. I design a database schema and API structure (using OpenAPI standards) built for the future, not just for today.
- Iterative Development: You'll see progress every step of the way. I build and deploy core features in short sprints, allowing for constant feedback and ensuring the final product perfectly matches your vision.
- Automated Testing: Confidence in code comes from testing. I write comprehensive unit and integration tests to ensure your backend is reliable and bug-free from day one.
- Secure Deployment: I deploy your backend as a lightweight, containerized application (Docker) on modern cloud infrastructure (like AWS or Google Cloud), configured for security, monitoring, and auto-scaling.
- Clear Documentation: You receive a fully-documented API so your frontend team or future developers can hit the ground running.
Your Questions, Answered Honestly
Why invest in Go/Rust when a cheaper Node.js/Python developer could build it faster?
This is a crucial question of strategy. Building "faster" often means accumulating technical debt—slow performance, higher server bills, and future scalability crises. My approach is different. We invest a bit more time upfront in solid architecture to build an asset that is dramatically cheaper to own and scale. You save significant money on cloud hosting, avoid costly rewrites when you hit 10,000+ users, and build a more reliable product that retains users. It's the difference between building a temporary shelter and a permanent foundation.
What is your process for guaranteeing my backend can handle a sudden traffic spike?
We don't guess; we prove it. The process includes load testing as a standard part of development. Using tools like k6, I simulate traffic far exceeding your expected peak load. We identify bottlenecks in a controlled environment—not during your product launch. Because Go and Rust are built for concurrency, they handle scaling gracefully. The result isn't just hope; it's data-driven confidence in your backend's performance under pressure.
You're one person. What are the risks? What happens after the project is "done"?
This is a valid concern, and I address it with a "no black box" policy. You own everything, always. The code is hosted on your Git repository. The infrastructure is on your cloud account. The API is documented using OpenAPI standards, making it easy for any developer to understand. I deliver code that is clean, tested, and maintainable because my reputation depends on it. For post-launch, I offer flexible retainers for ongoing support, feature additions, or simply peace of mind.
How do you translate my business needs into a technical architecture?
My process begins with a deep dive into your business logic, not technical jargon. We start with your user stories and revenue goals. What action is most critical for a user to take? Where does the system need to be most reliable? I then design the database schema, API contracts, and system components to directly support those business objectives. I provide diagrams and clear explanations at every step, ensuring the technical solution is always aligned with your business goals.
My project involves complex data. Which database will you choose and why?
The database is the heart of the application, and the choice is critical. I don't have a single "favorite." For most structured data needs, I default to PostgreSQL for its rock-solid reliability, rich features, and scalability. For caching or real-time needs, Redis is unparalleled. If your project demands massive, unpredictable scale, we'd architect around a managed NoSQL solution like DynamoDB. The choice is never based on my preference, but is always a carefully considered decision based on your specific data access patterns, and I will always explain the trade-offs to you in plain English.
Build a Backend That Lasts.
Don't let a weak foundation limit your growth. Let's design a high-performance backend that gives your application the speed, reliability, and scale it deserves. Schedule a free, no-obligation technical consultation today.
Book My Free Backend Consultation