An international flight search and booking platform uses a Multi-AZ Amazon RDS for PostgreSQL DB instance to store flight schedules and seat availability. During peak vacation booking periods, the platform experiences significant read latency spikes and query timeouts on the primary database due to a high volume of flight search queries and connection exhaustion. The booking engine also requires a caching tier for flight search result packages. This cache must support sub-millisecond response times and provide high availability with automatic failover and cross-AZ data replication to prevent cache cold-starts in the event of a node failure. Which three actions should the Solutions Architect take to improve database and caching efficiency while meeting these requirements? (Select THREE.)
- Deploy an Amazon RDS Proxy instance between the application and the RDS DB instance to manage database connection pooling.Cevap
- Deploy an Amazon ElastiCache for Redis cluster in Multi-AZ mode with replication enabled to cache search results.Cevap
- Deploy one or more Amazon RDS for PostgreSQL read replicas and configure the application to route read-intensive flight search queries to the read replica endpoints.Cevap
- DDeploy an Amazon ElastiCache for Memcached cluster to cache the flight search result packages and enable node auto-recovery.
- EConfigure the application's search queries to target the endpoint of the standby database instance in the secondary Availability Zone of the RDS PostgreSQL Multi-AZ deployment.
- FRequest ELB pre-warming for the Application Load Balancer to prevent database connection timeouts by absorbing instant spikes in database connection attempts.