AWS Certified Solutions Architect - Associate
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A company has a mobile chat application with a data store based in Amazon DynamoDB. Users would like new messages to be read with as little latency as possible. A solutions architect needs to design an optimal solution that requires minimal application changes.
Which method should the solutions architect select?
Other
Community
UAnonymous
A
Configure Amazon DynamoDB Accelerator (DAX) for the new messages table. Update the code to use the DAX endpoint.
B
Add DynamoDB read replicas to handle the increased read load. Update the application to point to the read endpoint for the read replicas.
C
Double the number of read capacity units for the new messages table in DynamoDB. Continue to use the existing DynamoDB endpoint.
D
Add an Amazon ElastiCache for Redis cache to the application stack. Update the application to point to the Redis cache endpoint instead of DynamoDB.
Explanation:
Explanation
Correct Answer: A
Amazon DynamoDB Accelerator (DAX) is specifically designed for this use case. Here's why:
Why DAX is the best solution:
- Minimal latency: DAX provides microsecond latency for read operations by caching frequently accessed data in memory.
- Minimal application changes: The application only needs to change the endpoint from DynamoDB to DAX - DAX is fully compatible with DynamoDB API calls.
- Seamless integration: DAX sits between the application and DynamoDB, automatically caching read responses and handling cache invalidation.
- Optimized for DynamoDB: DAX is purpose-built for DynamoDB, providing better performance than generic caching solutions.
Why other options are not optimal:
B. DynamoDB read replicas:
- Global Tables (read replicas) are for geographic distribution, not primarily for latency reduction
- They still have DynamoDB latency characteristics (single-digit milliseconds)
- More complex to manage than DAX
C. Doubling read capacity units:
- This only addresses throughput, not latency
- DynamoDB latency is generally consistent regardless of provisioned capacity
- Does not provide the microsecond latency users want
D. ElastiCache for Redis:
- Requires significant application changes (different API, cache invalidation logic)
- Application needs to implement cache-aside pattern manually
- More complex to implement and maintain than DAX
- Not purpose-built for DynamoDB
Key Benefits of DAX:
- In-memory caching: Provides microsecond read latency
- API compatibility: Uses the same API as DynamoDB
- Write-through caching: Automatically invalidates cache on writes
- Managed service: AWS handles scaling, patching, and maintenance
- Minimal code changes: Just change the endpoint in your application
For a chat application where users expect near-real-time message delivery, DAX provides the optimal balance of low latency and minimal application changes.
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