When we started building Astronify, we made a deliberate decision: design for the traffic we don't have yet, not just the traffic we have today.
That bet has paid off. Here's a look at the architectural decisions that let us scale without scrambling.
The Database Bottleneck Everyone Hits
Most early-stage platforms start with a single database and hit a wall somewhere between 10,000 and 100,000 concurrent users. The fixes at that stage are painful — migrations under load, schema changes with zero downtime, read replicas that need to catch up.
We avoided this by separating write-heavy workloads (course progress, event tracking) from read-heavy ones (course catalogs, search) from day one.
Video Delivery: Don't Build What Already Exists
Video infrastructure is one of the most expensive and complex problems in the EdTech space. We made an early decision to not solve it ourselves.
By delegating video storage, transcoding, and CDN delivery to purpose-built services, we freed the engineering team to focus on the things that differentiate us: the learning experience, the creator tools, the community layer.
“The best engineering decision is often knowing what not to build. Your competitive advantage is never in reinventing solved infrastructure.”
— Internal engineering philosophy
What We Got Wrong (And Fixed)
- Over-indexed on microservices too early — consolidated back to a modular monolith
- Search was an afterthought; rebuilt it properly with dedicated indexing
- Real-time features needed WebSockets earlier than we expected
- Caching strategy was reactive, not proactive — cost us during traffic spikes
Scale isn't a destination you reach — it's a continuous process of identifying the next bottleneck before it becomes a crisis. The goal is to make the failures boring and predictable.
