A financial services company hosts an investment tracking application on AWS. The application's transaction ledger is stored on an Amazon Aurora MySQL database cluster with one writer and two reader instances. During end-of-month reporting cycles, read queries on the ledger spike significantly, causing CPU utilization on the reader instances to reach 100%, resulting in query timeouts. Additionally, the application requires a caching layer to store session state tokens and transient calculations. The cached data must be replicated across multiple Availability Zones to ensure high availability, and must survive potential cache node failures. Which combination of database and caching optimization strategies should the solutions architect implement to address the performance degradation and satisfy the durability and scaling requirements? (Select TWO.)
- Deploy Amazon RDS Proxy for the Aurora cluster, and configure the application to direct read-intensive ledger queries to the proxy's read-only endpoint.Cevap
- Implement Amazon ElastiCache for Redis to store session state tokens, configuring Multi-AZ with automatic failover.Cevap
- CDeploy Amazon ElastiCache for Memcached to store session state tokens, enabling Multi-AZ replication to ensure the cached tokens survive node failures.
- DMigrate the ledger database to an Amazon RDS for MySQL database in a Multi-AZ deployment, and route read queries to the standby replica to scale read capacity.
- EConfigure the application to connect to the Aurora cluster endpoint for read operations, and configure Aurora Auto Scaling to dynamically add reader replicas.