DVA-C02 Troubleshooting and Optimization Practice Question

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

• ✗

  Enable S3 Transfer Acceleration

  Why it's wrong here

  Enabling S3 Transfer Acceleration improves the speed of data transfers between clients and S3 buckets, particularly over geographical distances, by routing data through CloudFront's edge network. However, this feature is specific to Amazon S3 and has no impact on the performance or throughput capacity of an Amazon DynamoDB table. Therefore, it does not address any potential performance bottlenecks within a DynamoDB application.

• ✓

  Use on-demand capacity or configure autoscaling/scheduled scaling for the table

  Why this is correct

  Utilizing DynamoDB's on-demand capacity mode automatically scales read and write throughput to accommodate varying workloads without requiring capacity planning. Alternatively, configuring autoscaling for the table dynamically adjusts provisioned read and write capacity units (RCUs/WCUs) based on actual traffic patterns or target utilization, preventing throttling errors during peak loads. Scheduled scaling further allows for pre-planned capacity adjustments for predictable traffic spikes, ensuring the application always has sufficient resources.

• ✗

  Disable CloudWatch metrics

  Why it's wrong here

  Disabling CloudWatch metrics for a DynamoDB table would remove critical visibility into its operational performance, including key metrics like consumed read/write capacity units, throttled requests, and latency. While CloudWatch itself consumes minimal resources, disabling it does not enhance DynamoDB's throughput or resolve underlying performance issues. Instead, it prevents effective monitoring and troubleshooting, making it impossible to identify the root cause of any application performance problems.

• ✗

  Move all reads to strongly consistent mode

  Why it's wrong here

  Moving all reads to strongly consistent mode in DynamoDB ensures that a read always returns the most up-to-date data, reflecting all prior successful write operations. However, strongly consistent reads consume twice the read capacity units (RCUs) compared to eventually consistent reads for the same amount of data, and they can also incur higher latency. This change would likely *increase* the demand on the table's provisioned capacity, potentially leading to more throttling errors rather than resolving performance issues.