DVA-C02 Development with AWS Services Practice Question
This DVA-C02 practice question tests your understanding of development with aws services. Match the stated requirement to the specific cloud service, access model, or configuration option — many options are valid in isolation but not for this scenario. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
A developer is using AWS X-Ray to trace a serverless application. The application uses an AWS Lambda function to query a DynamoDB table. The trace shows that the DynamoDB subsegment takes a significant portion of the total response time. The developer wants to reduce the DynamoDB query latency. Which service should the developer integrate with the Lambda function to achieve the lowest latency for repeated read queries?
Correct. DAX is a fully managed, highly available, in-memory cache for DynamoDB that delivers up to 10x read performance improvement by caching frequently accessed data.
B
Amazon ElastiCache for Redis
Why wrong: Incorrect. While ElastiCache can cache data, it requires custom code to manage caching logic and is not as tightly integrated with DynamoDB as DAX.
C
DynamoDB Global Tables
Why wrong: Incorrect. Global Tables replicate data across regions for disaster recovery and low-latency reads in multiple regions, but they do not cache data for repeated reads in a single region.
D
DynamoDB Streams
Why wrong: Incorrect. DynamoDB Streams capture modifications to the table, not caching, and would not reduce read latency.
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
DynamoDB Accelerator (DAX)
DynamoDB Accelerator (DAX) is a fully managed, highly available, in-memory cache for DynamoDB that delivers up to 10x read performance improvement by reducing response times from milliseconds to microseconds for repeated read queries. By integrating DAX with the Lambda function, the developer can cache the results of frequent DynamoDB queries directly in memory, bypassing the read capacity units and the underlying storage engine, which directly addresses the latency bottleneck shown in the X-Ray trace.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
✓
DynamoDB Accelerator (DAX)
Why this is correct
Correct. DAX is a fully managed, highly available, in-memory cache for DynamoDB that delivers up to 10x read performance improvement by caching frequently accessed data.
Related concept
Read the scenario before looking for a memorised answer.
✗
Amazon ElastiCache for Redis
Why it's wrong here
Incorrect. While ElastiCache can cache data, it requires custom code to manage caching logic and is not as tightly integrated with DynamoDB as DAX.
✗
DynamoDB Global Tables
Why it's wrong here
Incorrect. Global Tables replicate data across regions for disaster recovery and low-latency reads in multiple regions, but they do not cache data for repeated reads in a single region.
✗
DynamoDB Streams
Why it's wrong here
Incorrect. DynamoDB Streams capture modifications to the table, not caching, and would not reduce read latency.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often choose ElastiCache for Redis because it is a well-known caching solution, but they overlook that DAX is purpose-built for DynamoDB and provides lower latency with zero application-level cache management, making it the correct choice for reducing DynamoDB query latency in a serverless application.
Detailed technical explanation
How to think about this question
DAX operates as a write-through cache that intercepts DynamoDB API calls at the SDK level, meaning the Lambda function uses the same DynamoDB API calls but points to the DAX cluster endpoint instead of the DynamoDB table endpoint. Under the hood, DAX maintains a distributed in-memory cache using a cluster of nodes, and it automatically handles cache hits and misses, TTL-based expiration, and eventual consistency for reads, which is ideal for repeated read-heavy workloads like session stores or product catalogs. A subtle behavior is that DAX does not support all DynamoDB operations (e.g., transactions, certain scan filters) and requires the application to use the DAX SDK client, which is a drop-in replacement for the standard DynamoDB client.
KKey Concepts to Remember
Read the scenario before looking for a memorised answer.
Find the constraint that changes the correct option.
Eliminate answers that are true in general but not in this case.
TExam Day Tips
→Watch for words such as best, first, most likely and least administrative effort.
→Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A media company stores terabytes of video archives that are accessed once a year for audit purposes. Moving these objects to a cold storage tier (Azure Archive, S3 Glacier, or Google Nearline) costs a fraction of hot storage. Questions like this test whether you understand storage tiers, access frequency tradeoffs, and retrieval latency requirements.
What to study next
Got this wrong? Here's your next step.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Development with AWS Services — This question tests Development with AWS Services — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: DynamoDB Accelerator (DAX) — DynamoDB Accelerator (DAX) is a fully managed, highly available, in-memory cache for DynamoDB that delivers up to 10x read performance improvement by reducing response times from milliseconds to microseconds for repeated read queries. By integrating DAX with the Lambda function, the developer can cache the results of frequent DynamoDB queries directly in memory, bypassing the read capacity units and the underlying storage engine, which directly addresses the latency bottleneck shown in the X-Ray trace.
What should I do if I get this DVA-C02 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Question Discussion
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