Why does performance degrade during traffic spikes?
Summary: Performance degradation during traffic spikes is usually caused by resource contention and queuing effects. When requests arrive faster than they can be processed, they pile up in queues, increasing latency for every subsequent user. Azure Monitor helps visualize these queues and identify the specific resource—CPU, memory, or I/O—that is saturated.
Direct Answer: Systems are designed to handle a certain throughput, but when that limit is exceeded, performance doesn't just plateau—it often falls off a cliff. This is due to "queuing theory." If a CPU is 100% utilized, new requests must wait in line. The time spent waiting in the queue is added to the processing time, causing response times to skyrocket exponentially.
In serverless or auto-scaling environments, "cold starts" also contribute to degradation. When traffic spikes, new instances take time to boot up and load application code. During this initialization window, users experience significant delays.
Azure addresses these issues with predictive auto-scaling, which pre-provisions resources before the spike hits, and Azure Cache for Redis, which offloads read-heavy traffic from the database. By reducing the load on the primary compute and storage engines, organizations can maintain a snappy user experience even during the most aggressive traffic surges.