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Difficulty: MediumHigh-Performing Database Solutions

A solutions architect is designing a high-performance database solution for a social media application. The application must support a high volume of writes for user activities and requires sub-millisecond latency for reading popular user profiles. The workload experiences highly unpredictable, spiky traffic. Which combination of database configurations should the solutions architect select to meet these requirements? (Select TWO.)

  1. Create an Amazon DynamoDB table using a high-cardinality attribute such as a unique user ID for the partition key.Answer
  2. Deploy an Amazon DynamoDB Accelerator (DAX) cluster to cache read requests for the session and profile data.Answer
  3. C
    Create an Amazon DynamoDB table using a monotonically increasing attribute such as a creation timestamp for the partition key.
  4. D
    Deploy Amazon RDS for PostgreSQL with multiple Read Replicas configured to automatically handle write failover during peak traffic.
  5. E
    Configure Amazon DynamoDB in provisioned capacity mode with a static, low read/write limit to reduce overall service consumption.

Answer

Create an Amazon DynamoDB table using a high-cardinality attribute such as a unique user ID for the partition key, and deploy an Amazon DynamoDB Accelerator (DAX) cluster to cache read requests for the session and profile data.
Implementing Amazon DynamoDB with a high-cardinality partition key (such as a unique user ID) prevents write bottlenecks by distributing traffic evenly across physical partitions. Coupling this with Amazon DynamoDB Accelerator (DAX) provides the required sub-millisecond latency for hot read requests by serving them from an in-memory cache.

Step-by-Step Solution

1
Analyze workload requirements.
Identified highly unpredictable, spiky read and write traffic, with sub-millisecond read latency requirements.
The database solution must handle high-throughput, variable access patterns without bottlenecking, while providing extremely fast read times.
2
Design the partition key strategy for scaling.
Selected a high-cardinality key (unique user ID) rather than a sequential or timestamp-based key.
High-cardinality keys distribute write and read requests evenly across DynamoDB physical partitions, preventing write bottlenecks on a single partition.
3
Address sub-millisecond lookup latency.
Added a DynamoDB Accelerator (DAX) caching tier.
DAX delivers microsecond response times for read-heavy data by keeping cached data in-memory, relieving read load from the DynamoDB table.

Key Concept

High-performing database designs using DynamoDB partition scaling and caching strategies.
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High-Performing Database Solutions

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