A live-events company is designing a scaling solution for its ticket application on AWS. The application has high peaks of utilization during sale events. Each sale event is a one-time event that is…

Predictive scaling is primarily for forecasting and scaling based on continuously learned patterns, not for specific, one-time scheduled events where scheduled scaling is more direct and efficient.

While scheduled scaling for EC2 is correct, Amazon RDS for PostgreSQL generally offers less scalability and performance for extremely high-peak workloads compared to Amazon Aurora, which is optimized for high-performance databases.

Predictive scaling is less appropriate for one-time scheduled events, and Amazon RDS for PostgreSQL is generally less performant than Aurora for the demands of high-peak sale events.

Scheduled scaling policies for Amazon EC2 Auto Scaling groups are ideal for predictably increasing capacity ahead of known, one-time scheduled events, maximizing availability. Hosting the database on Amazon Aurora provides a highly available, performant, and scalable PostgreSQL-compatible database solution suitable for high-traffic sale events.