Handling a sudden doubling of user load starts with horizontal scaling and caching, since those give the fastest relief without requiring a redesign of the application.
Key Points: • Add more instances behind a load balancer to distribute the increased traffic horizontally. • Introduce or expand caching for frequently accessed, read-heavy data to reduce database load. • Review and optimize slow database queries and missing indexes, which tend to be the first thing to buckle under increased concurrency. • Check connection pool sizes (HikariCP, thread pools) since default settings are often tuned for lower load. • Use a load balancer with health checks so traffic only routes to healthy, ready instances.
Example: Doubling instance count behind an existing load balancer combined with caching the product catalog in Redis can absorb a traffic spike within minutes, buying time to investigate and fix any deeper architectural bottlenecks afterward.
Interview Tip: A concise interview answer is:
"My first move is horizontal scaling -- add instances behind the load balancer -- combined with caching hot read paths to take pressure off the database. In parallel I'd check for slow queries, missing indexes, and undersized connection pools, since those are the most common things that break first under doubled load."