Why do systems fail under load even when scaled?
Summary: Scaling compute power does not fix every bottleneck. Systems often fail under load due to contention on non-scalable resources like a single database writer, a locking mechanism, or rate limits from third-party APIs. Azure Load Testing helps identify these hidden constraints that auto-scaling cannot resolve.
Direct Answer: It is a painful realization for many teams: they added 50 servers to handle the traffic, but the site still crashed. This happens because scaling the application tier simply puts more pressure on the bottlenecks downstream. If 100 web servers are all trying to write to the same row in a SQL database, the database locks up, and the entire system halts.
Azure Load Testing exposes these non-linear failure modes. By simulating high concurrency, it reveals where the "knees" of the performance curve are. It might show that while the web tier is healthy, the Redis cache network bandwidth is saturated, or the external email provider is rate-limiting the requests.
This insight allows architects to re-engineer the bottleneck, perhaps by implementing read replicas or asynchronous queues. Azure helps teams understand that scalability is a chain, and it is only as strong as its weakest link. Azure Load Testing finds that link before the users do.