Amazon Web Services Updated DVA-C02 Exam Questions and Answers by nahla

Tracing Distributed Systems: AWS X-Ray is designed to trace requests across services, helping identify bottlenecks in distributed applications like this one.

No Code Changes: Enabling X-Ray tracing often requires minimal code changes, meeting the requirement.

Identifying Bottlenecks: Analyzing X-Ray traces and logs will reveal latency in communications between different AWS services, leading to the high duration time.

The core requirement is to perform a one-time deployment for testing without impacting the existing pre-production stack that other team members rely on. The safest way to avoid disruption is to deploy into an isolated AWS account (a dedicated development/testing account) instead of modifying the shared pre-production environment.

Option C achieves this with the least effort: use the AWS SAM CLI to package and deploy the same SAM application into a new AWS account designated for development. This creates an isolated copy of the stack (Lambda + SNS topics) where the developer can validate changes without affecting the shared pre-production deployment or the release pipeline.

Option A still deploys into pre-production, which directly violates the requirement to avoid impacting the existing application. A “debug parameter” does not prevent resource updates or side effects.

Option B is inconsistent: a CloudFormation change set is created against a specific account/stack. You cannot create a change set in one account and “execute it” in a different account as stated. Cross-account execution would require different credentials and a separate deployment process.

Option D introduces additional pipeline/stage complexity and is not necessary for a one-time test; it also implies changing the existing stack/pipeline, which can itself cause disruption.

Maximum concurrency for SQS as an event source allows customers to control the maximum concurrent invokes by the SQS event source1. When multiple SQS event sources are configured to a function, customers can control the maximum concurrent invokes of individual SQS event source1.

In this scenario, the developer needs to resolve the issue of the third-party API frequently returning an HTTP 429 Too Many Requests error message, which prevents a significant number of messages from being processed successfully. To achieve this, the developer can follow these steps:

Find out the documented rate limits of the third-party API, which specify how many requests can be made in a given time period.

Configure maximum concurrency on the SQS event source based on the rate limits of the third-party API. This will limit the number of concurrent invokes by the SQS event source and prevent exceeding the rate limits of the third-party API.

Test and monitor the application performance and adjust the maximum concurrency value as needed.

By using this solution, the developer can reduce the frequency of HTTP 429 errors and improve the message processing success rate. The developer can also avoid throttling or blocking by the third-party API.

Amazon S3 Glacier storage classes are designed for cost-effective archival with varying retrieval times. S3 Glacier Instant Retrieval provides millisecond access, making it suitable for workloads that require immediate access but at a lower cost than S3 Standard.

For the first 90 days, instant access is required, which rules out S3 Glacier Deep Archive and S3 Glacier Flexible Retrieval as primary storage because they have minutes-to-hours retrieval times. After 90 days, the requirement allows retrieval times exceeding 10 minutes, making S3 Glacier Flexible Retrieval appropriate.

Option D uses Instant Retrieval initially and transitions to Flexible Retrieval, optimizing both performance and cost. EFS and EBS (Options A and C) are significantly more expensive for large objects and are not intended for massive archival workloads. Option B reverses the access requirements and is invalid.

AWS documentation explicitly recommends using S3 lifecycle policies to transition objects between Glacier storage classes based on access requirements.

Therefore, Option D is the most cost-effective and AWS-aligned solution.