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Difficulty: MediumHigh-Performing Database Solutions

A retail company is launching a high-traffic flash sale website. The application requirements specify:
- Highly unpredictable read traffic spikes for the product catalog requiring sub-millisecond latency.
- High-volume write traffic for customer order processing that exhibits sudden, massive spikes, where write throttling must be avoided.
- A requirement to maintain high availability and performance during database failover events.

Which two strategies should the solutions architect implement to achieve a high-performing and resilient database architecture? (Select two.)

  1. Deploy Amazon DynamoDB Accelerator (DAX) to cache read queries for the product catalog table, reducing read latency to microseconds.Answer
  2. Configure the customer order processing table in Amazon DynamoDB with On-Demand capacity mode to automatically handle sudden write spikes without manual provisioning.Answer
  3. C
    Use DynamoDB Provisioned capacity mode for the order table, employing a partition key based on monotonically increasing order timestamps to guarantee sequential sorting of writes.
  4. D
    Configure the order table in DynamoDB using Provisioned capacity mode set to average baseline usage to optimize costs, relying on standard auto-scaling to handle the sudden sub-second flash sale peaks.
  5. E
    Deploy Amazon RDS for MySQL with Read Replicas, and configure the Read Replicas as the primary target for automatic failover and writer promotion to handle peak write traffic spikes.

Answer

Deploy Amazon DynamoDB Accelerator (DAX) to cache read queries for the product catalog table, and configure the customer order processing table with On-Demand capacity mode to scale writes automatically.
To meet the performance goals, the solutions architect should implement Amazon DynamoDB Accelerator (DAX) and DynamoDB On-Demand capacity mode. DAX serves read requests from cache with microsecond latency, satisfying the sub-millisecond catalog query requirement. On-Demand capacity mode handles unpredictable write traffic spikes instantly without manual intervention or throttling, ensuring orders are processed successfully during peak flash sale moments.

Step-by-Step Solution

1
Analyze read latency and traffic patterns for the product catalog.
Identify that the catalog has highly unpredictable read spikes requiring sub-millisecond response times, indicating a need for an in-memory cache like DAX.
DAX provides microsecond latency and offloads read pressure from the database table.
2
Evaluate write scaling requirements for order processing.
Identify that the order table requires rapid scaling to handle sudden, massive spikes without throttling, which indicates On-Demand capacity mode.
On-Demand capacity scales instantly to accommodate sudden peaks, whereas Provisioned Auto Scaling requires time to adjust throughput.
3
Eliminate database configurations that introduce bottlenecks or failover misconceptions.
Discard strategies involving monotonically increasing partition keys (which cause hot partitions) and RDS MySQL replicas for write failover (replicas scale reads, not writes, and do not automate failover in this manner).
Ensures the selected architecture is optimal for both high performance and resiliency.

Key Concept

High-performing database architectures on AWS leverage in-memory caching (DAX) for low-latency read performance and flexible scaling modes (On-Demand capacity) to handle highly unpredictable write traffic spikes.
Estimated Time:2m 0s
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Topics

High-Performing Database Solutions

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