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Difficulty: MediumHigh-Performing Database Solutions

A global logistics company tracks package delivery statuses using an Amazon Aurora MySQL database cluster. The database handles a steady write volume of 120120 transactions per second (TPS) from regional scanning devices. Customer queries for tracking updates create read spikes of up to 7,5007,500 queries per second (QPS), causing read query latency to exceed the target threshold of 15 ms15\text{ ms}. The database writes remain stable. A solutions architect must design a high-performing and highly available database architecture that ensures read queries have low latency.

Which two actions should the solutions architect take to meet these requirements? (Select TWO.)

  1. Add Aurora Replicas to the database cluster and configure the application to use the reader endpoint for tracking query traffic.Answer
  2. Deploy an Amazon ElastiCache cluster to cache frequently accessed package shipment queries.Answer
  3. C
    Migrate the database to Amazon DynamoDB and use the package scan timestamp as the partition key.
  4. D
    Configure a PostgreSQL Read Replica in a different AWS Region and configure it as the automatic failover target for the primary Aurora MySQL instance.
  5. E
    Enable Amazon DynamoDB Accelerator (DAX) to cache the queries coming from the Aurora database cluster.

Answer

To resolve the read latency issues and ensure high performance and availability, the solutions architect should add Aurora Replicas to the database cluster and use the reader endpoint, and deploy an Amazon ElastiCache cluster to cache frequently accessed queries.
The correct options involve adding Aurora Replicas to scale read operations horizontally and using the cluster's reader endpoint to load-balance queries. Additionally, introducing Amazon ElastiCache caches frequently requested package history, reducing latency to the sub-millisecond range and offloading the primary database cluster.

Step-by-Step Solution

1
Analyze read/write patterns and identify bottlenecks.
Write volume (120120 TPS) is low and stable, but read volume is extremely high (7,5007,500 QPS), resulting in degraded read latency that exceeds 15 ms15\text{ ms}.
This confirms the database is read-heavy and requires optimization at the read and caching layers.
2
Implement database-level read scaling.
Add Aurora Replicas to the database cluster and direct read queries to the reader endpoint.
Aurora Replicas offload the query load from the primary instance, and the reader endpoint automatically balances connections among the reader instances.
3
Implement database caching.
Deploy an Amazon ElastiCache cluster to cache frequently accessed query results.
ElastiCache provides sub-millisecond latencies for cached data, further shielding the database from repetitive read queries.

Key Concept

Scaling database reads using read replicas (reader endpoints) and implementing in-memory caching (ElastiCache) are standard patterns for optimizing database read performance and achieving low latency.
Estimated Time:2m 0s
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High-Performing Database Solutions

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