A company runs a web application on Amazon EC2 instances in an Auto Scaling group. The application uses an Amazon RDS for PostgreSQL DB instance. The application slows when traffic increases because the database has a heavy read load during peak traffic. Which actions should a solutions architect take to resolve these performance issues? (Choose two.)

The problem describes a heavy read load on the database during peak traffic, causing the application to slow down. Creating a read replica for the DB instance offloads read traffic from the primary database, distributing the read burden and improving performance. The application must be configured to direct read queries to this replica. Creating an Amazon ElastiCache cluster and configuring the application to cache query results significantly reduces the number of direct database reads. Frequently accessed data can be served from the fast in-memory cache, alleviating the database's read load. Turning on auto scaling for the DB instance is not a native feature for RDS instances in the same way it is for EC2. While storage can auto-scale, the compute capacity of the DB instance itself does not automatically scale out for read traffic. Converting to a Multi-AZ deployment provides high availability and disaster recovery but does not inherently distribute read traffic; the standby instance is not typically used for direct read access. Configuring Auto Scaling group subnets to match the DB instance's Availability Zone might reduce network latency but does not address the fundamental issue of excessive read load on the database.