Backend and API Development with .NET

Danijel Balog
By Danijel Balog
Founder, Fragon Studios

Robust backend systems and APIs with C# and .NET. Hosted at Hetzner in Germany.

The Foundation for Your Success

Fragon Studios builds backend systems primarily with C# and .NET 10 on PostgreSQL; for SME projects we recommend a modular monolith as default rather than microservices, because in over 80 percent of cases microservice complexity creates more problems than it solves. Microservices or monolith? The modular monolith is the right default for most SME applications. Easier to develop, easier to deploy, easier to debug, and it scales comfortably for five-figure user counts. Microservices pay off when teams need to work independently, when individual components have different scaling profiles, or when a polyglot language stack is necessary. 'Microservices from day one' is almost always an expensive mistake. Databases: PostgreSQL is our default. Relational, transactional, with JSON support for what isn't schema-fixed. Redis for cache and session store, MySQL when existing systems require it. For vector search we use Milvus or Qdrant, or pgvector as a lighter extension, depending on volume. Observability isn't a luxury. We instrument with OpenTelemetry for distributed traces, Prometheus for metrics, Grafana for dashboards, and Loki for logs. All on our own infrastructure, no data sent to external APM providers. When something goes wrong, we know in minutes, not hours. Language flexibility: we work primarily in C# with .NET 10, but we keep Node.js with NestJS and Python with FastAPI in the toolkit. If your team already runs on a stack, we build on it.

Development + Operations = One Team

We build AND operate the system. No finger-pointing, fast reaction times, real responsibility.

Enterprise Infrastructure

Your application runs on enterprise-grade infrastructure. AMD EPYC processors, NVMe storage, redundant connectivity.

Data Stays in Germany

Fragon Cloud runs on Hetzner servers. No AWS, Azure, or GCP. Full control over your data.

Backend Development with Us

Transparent, agile, and goal-oriented to success.

1

Architecture Workshop

We analyze requirements, define interfaces, and create an architecture concept.

2

API Design

We document all endpoints before development. So frontend teams have something to work with early.

3

Development & Testing

Development with automated tests. Every pull request is tested before it's merged.

4

Deployment on Fragon Cloud

Automatic deployment to our Kubernetes clusters. Monitoring and alerting included.

Technical Standards

C# with .NET 10 as primary stack
PostgreSQL, Redis, Milvus, Qdrant
REST, gRPC, GraphQL, and SignalR
OpenTelemetry, Prometheus, Grafana, Loki
Docker and Kubernetes on Fragon Cloud
Node.js with NestJS or Python with FastAPI on request

Typical projects

Four recurring backend engagements. Not exhaustive, just a sense of the range.

Multi-tenant API with role system

Problem: A SaaS vendor is growing past a single customer and needs clean tenant separation and a role-based API.

Solution: Six to ten weeks of .NET 10 API with schema-per-tenant on PostgreSQL, an RBAC layer, rate limiting, and OpenAPI docs, deployed on Fragon Cloud.

Legacy integration via adapter layer

Problem: A mid-market company wants to connect new apps without rebuilding the legacy ERP and needs a stable API facade.

Solution: Four to six weeks of adapter layer in C#, caching for expensive calls, asynchronous replication into a modern PostgreSQL view, monitoring with OpenTelemetry.

Realtime system with WebSocket

Problem: A logistics platform needs to show status changes to dispatchers in realtime; today the frontend polls every five seconds.

Solution: Four to six weeks of backend with a SignalR hub for WebSocket streaming, an event-driven status model, and horizontal scaling via a Redis backplane.

ETL pipeline for data consolidation

Problem: A sales team pulls reports from three different tools every Monday and burns half a day on it.

Solution: Three to five weeks of ETL pipeline in .NET with a nightly batch job, a deduplicated target table, and a slim reporting API for an existing BI tool.

Frequently Asked Questions

Both, depending on the use case. REST for classic CRUD and public APIs, GraphQL when the frontend needs many data combinations or mobile clients must optimize bandwidth. We decide together during the architecture phase, not ideologically.