DVA-C02 Troubleshooting and Optimization Practice Question
A company's application uses Amazon DynamoDB as its database. The application reads the same item multiple times per second and occasionally sees stale data. The DynamoDB table uses the default eventually consistent reads. What should the developer change to ensure strongly consistent reads?
⚠ Common exam trap
Test-takers frequently confuse throughput scaling (Option A) or caching (Option B) with consistency guarantees, or mistakenly think transactions (Option D) are required for strong consistency, when in fact a simple parameter change on the read operation is the correct and minimal fix.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Set the ConsistentRead parameter to true in the GetItem call.
DynamoDB's default read consistency model is eventually consistent, which can return stale data if an item is updated shortly before the read. By setting the `ConsistentRead` parameter to `true` in the `GetItem` call, the developer forces a strongly consistent read, ensuring the response reflects the most recent write. This directly addresses the stale data issue without changing throughput or adding caching.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Increase the read capacity units of the table.
Why it's wrong here
Increasing Read Capacity Units (RCUs) primarily scales the throughput of a DynamoDB table, allowing it to handle more read requests per second without throttling. However, RCUs do not alter the read consistency model itself. DynamoDB's default eventual consistency is a fundamental characteristic of its distributed architecture, independent of the provisioned capacity, and therefore increasing RCUs will not make reads strongly consistent.
- ✗
Use DynamoDB Accelerator (DAX) to cache the item.
Why it's wrong here
DynamoDB Accelerator (DAX) is a fully managed, highly available, in-memory cache designed to significantly improve read performance for DynamoDB tables. While DAX reduces latency, its cache provides eventually consistent reads by default, meaning cached data might not reflect the absolute latest writes to the underlying DynamoDB table. Therefore, using DAX would not satisfy a requirement for strongly consistent reads for the item, as it prioritizes speed over immediate data freshness.
- ✓
Set the ConsistentRead parameter to true in the GetItem call.
Why this is correct
Setting the ConsistentRead parameter to true in a GetItem API call explicitly instructs DynamoDB to perform a strongly consistent read. This ensures that the data returned reflects all successful write operations that completed before the read request was initiated, providing the most up-to-date version of the item. While this guarantees data freshness, it may incur slightly higher latency and consume more Read Capacity Units compared to an eventually consistent read.
- ✗
Use DynamoDB transactions for all read operations.
Why it's wrong here
DynamoDB transactions are designed to provide atomicity, consistency, isolation, and durability (ACID) properties for multiple item operations, primarily for write operations across one or more tables. While transactions can involve reading items as part of a larger transactional write set, they are not the appropriate mechanism for simply performing a strongly consistent read of a single item. A direct GetItem call with ConsistentRead=true is the correct and more efficient method for that specific requirement.
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