Technology Stack
Our technology stack is intentionally small. Every technology we adopt must reduce operational complexity, improve maintainability, or solve a specific engineering problem.
Selection Principles
We evaluate technology using six operational constraints. We reject tools that add complexity unless their design properties directly resolve constraints around:
- 01 / Maintainability: Long-term readability and codebase lifespan.
- 02 / Operational Simplicity: Clean deployments, minimal base servers.
- 03 / Long-Term Support: Relies on mature, standard-compliant technologies.
- 04 / Performance: Runtime execution speeds, resource efficiency.
- 05 / Clear Ownership: Binaries and databases can be cleanly handed over.
- 06 / Community Maturity: Strong ecosystems with active developer support.
Frontend
We build client-facing interfaces using **SvelteKit**, **TypeScript**, and **Tailwind CSS**. SvelteKit
compiles template code directly to vanilla JavaScript, minimizing client-side rendering overhead.
TypeScript guarantees interface parameter reliability, and Tailwind CSS provides utility styling
without bloated stylesheet dependencies.
**When we avoid it:** We avoid SvelteKit if a client has built their entire internal engineering team
around another library (like React/Next.js). In those cases, we adapt to preserve team maintainability.
Backend
Our default backend language is **Go**. Go compiles into a single, static binary containing no external runtime
dependencies, and its concurrency primitives (goroutines, channels) execute thousands of parallel processes
using very little memory (often <20MB). This ensures high reliability and cost-efficient VPS hosting.
**When Node.js is appropriate:** We use Node.js (via SvelteKit server endpoints) for frontend-adjacent API integration,
dynamic template rendering, or when writing serverless Edge functions where JavaScript runtimes are native.
Data Layer
We select database layers depending on your transaction write concurrency requirements:
SQLite (Edge / Read-Heavy)
Runs in-process on edge servers (Cloudflare D1) or as local files. It removes network roundtrips, returning reads in sub-1ms. Ideal for read-heavy SaaS dashboards and partitioned client databases.
PostgreSQL (Write-Heavy / Relational)
Handles parallel writes, row locks, and complex database joins safely. PostgreSQL is mandatory when data schemas require cross-tenant transactions or high-concurrency database writes.
Infrastructure
We choose hosting environments based on execution budgets and operational constraints:
Cloudflare Pages & Workers: Deploys client-facing code directly to global edge networks. It removes server maintenance, scales automatically, and keeps latency under 50ms. Cloudflare D1 handles local edge databases, and Cloudflare KV handles semantic caching.
Traditional VPS & Containers: VPS instances (AWS/Hetzner) are used when workloads require continuous background compute, long-running math calculations, or Docker-based microservices that exceed serverless worker limits (128MB memory, 30s timeouts).
APIs & Contracts
We enforce contract-first development. We design interfaces using **OpenAPI specifications** before writing code. Client-facing integrations use standard **REST APIs** for caching and third-party compatibility, while internal services utilize **RPC** frameworks for type-safe server-to-server calls. Webhooks and event versions are specified in the schema to ensure backward compatibility.
Applied AI Stack
We focus on system design, semantic caching, and data processing rather than model branding. Our AI pipelines convert unstructured data into vector embeddings, querying them using semantic search extensions (like pgvector in PostgreSQL) or dedicated vector databases. Retrieval-Augmented Generation (RAG) pipelines pass retrieved context to LLMs, applying active schema validations and fallback handlers to protect data privacy.
Developer Experience
We maintain strict standards for code handover. Every client project includes clean Git commit history, automated testing pipelines, infrastructure-as-code configurations, structured logging (JSON format), and deployment scripts to ensure your team has total control.
What We Avoid
Maintaining long-term systems requires avoiding unnecessary complexity:
Trend-Driven Abstractions
We avoid adopt-early libraries that add layers of compile dependencies and break codebase lifespan.
Premature Microservices
We build modular monoliths, separating components into microservices only when domain scaling demands it.
Vendor-Locked Databases
We write SQL standard queries, ensuring database hosting can be migrated to another cloud provider instantly.
Dependencies & Limitations
We believe in being honest about technology boundaries. No tool fits every scenario:
SQLite Writer Serialization
SQLite restricts writes to a single thread. It is not appropriate for systems with high parallel write transactions from millions of sources; PostgreSQL is mandatory in these cases.
Serverless Edge Constraints
Edge workers (Cloudflare) scale instantly but enforce 128MB memory limits and 30s execution timeouts. Traditional VPS compute (AWS/Hetzner) is required for heavy data analysis or Docker containers.
Go Language Constraints
Go compiles to static binaries with fast execution speeds, but lacks the rapid dynamic prototyping flexibility of Python or Node.js for early-stage web page iterations.
Edge Database Sync Latency
Distributed edge databases (like Cloudflare D1) require careful write synchronization models to prevent data stale states across global regions.
Technology Summary Matrix
| Technology | Why We Use It | Primary Strength | Limitations | Typical Use Cases |
|---|---|---|---|---|
| Go | Fast concurrent runtimes, static compiling. | Low memory, zero dependencies. | Harder for rapid dynamic prototyping. | Backend APIs, event proxies. |
| SvelteKit | No client-side hydration bloat. | Compiles to vanilla JS. | Smaller developer hiring pool than React. | SaaS dashboards, portals, site UI. |
| SQLite | Runs in-process on edge server nodes. | Sub-1ms read times, zero networks. | Single-writer lock serialization. | Read-heavy dashboards, tenant isolation. |
| PostgreSQL | Standard relational database for write concurrency. | Complex indices, parallel write execution. | Requires network roundtrip overhead. | Write-heavy apps, cross-tenant tables. |
| Cloudflare | Edge serverless workers global routing. | Flat-rate scale, <50ms response times. | 128MB memory limit, 30s timeout execution. | Edge APIs, Webhooks, SaaS hosting. |
Frequently Asked Questions
Why does CodeNXT Lab prefer Go?
Go compiles to static binaries with zero dependencies. Its goroutine model handles concurrent requests with minimal memory footprint, ensuring cost-efficient and stable backend scaling.
Why not use every new framework?
Chasing framework trends introduces security dependencies and blocks long-term codebase maintainability. We restrict our tools to standard, compilation-first runtimes to maximize stability.
Is SQLite production ready?
Yes. In WAL mode, SQLite handles thousands of read requests/sec at sub-1ms speeds. Deployed at the edge (Cloudflare D1), it is ideal for read-heavy SaaS applications, dashboards, and isolated tenant databases.
Why SvelteKit instead of React?
SvelteKit compiles pages directly to vanilla JS, removing client-side hydration code and virtual DOM overhead. This keeps page sizes small and fast to load.
When should PostgreSQL be used?
PostgreSQL is chosen when the workload requires high parallel write operations, complex cross-table relational joins, or database-level transaction locking rules.
Do you support Node.js?
Yes. We use Node.js (via SvelteKit server endpoints) for API routing, JSON transformations, and edge worker scripts where JavaScript is native.
Can the stack change?
Yes. While SvelteKit, Go, SQLite, PostgreSQL, and Cloudflare Pages are our preferred tools, we adapt to legacy setups or specific developer skillsets if your internal team requires it.
How do you evaluate new technologies?
We evaluate tools based on compile-time footprint, memory overhead, standard compliance, community maturity, and whether they introduce vendor lock-in.
Why Cloudflare?
Cloudflare runs serverless Workers and Pages directly on their global edge CDN, keeping response latencies under 50ms and removing traditional server setup and patch maintenance.
Do clients have to use your preferred stack?
No. We write standard SQL queries, REST APIs, and portable binaries so that all code we ship can be migrated to AWS, Hetzner, or other hosting providers instantly.
Discuss your stack before writing code.
Skip generic agency proposals. Schedule a systems call with our principal architect to analyze your database limits and server runtimes.
Connect with the Principal Architect