Amazon Web Services DVA-C02 Exam With Confidence Using Practice Dumps

Amazon API Gateway is a service that enables developers to create, publish, maintain, monitor, and secure APIs at any scale. The developer can define a development stage on the API Gateway API and instruct the other developers to point the endpoints to the development stage. This way, the developer can provide beta access to the new version of the API without affecting customers who use the production stage. This solution will meet the requirements with the least operational overhead.

To monitor end-to-end requests and debug issues across microservices, you need distributed tracing. Among AWS tools, AWS X-Ray is specifically built for this use case.

Step-by-Step Breakdown:

Step 1: Understand the Requirement

The developer needs:

End-to-end request tracing across microservices

Debugging capability for performance issues or failures

This points directly to a distributed tracing solution rather than just logs or metrics.

Step 2: Evaluate the Options

Option A: Amazon CloudWatch

CloudWatch is powerful for metrics, logs, and alerts.

But it does not provide distributed tracing or request path visualization between microservices.

So, it ' s not sufficient alone for the requirement.

Option B: AWS CloudTrail

CloudTrail tracks API calls made through the AWS Management Console, CLI, SDKs.

It is meant for auditing and governance, not microservices request tracing.

Not suitable for debugging microservices interactions.

Option C: AWS X-Ray SDK with X-Ray service map

Purpose-built for distributed tracing

Automatically collects data about requests as they travel through your microservices

You can instrument your code with the AWS X-Ray SDK in Java, Node.js, Python, Go, .NET, etc.

Visualizes requests using a service map, showing latency, errors, and time spent in downstream services.

How it works:

Instrument each microservice using the AWS X-Ray SDK.

Use the SDK to trace requests, propagate trace headers across services.

The X-Ray daemon collects and sends trace data to the X-Ray service.

You can view the service map, see bottlenecks, error rates, etc.

Option D: AWS Health

AWS Health provides information on AWS service outages or account-level events.

It does not monitor your application or microservices health or request flows.

Correct Choice: C is the only option that meets the developer ' s requirement to monitor end-to-end request paths and debug issues in a microservices architecture.

AWS Developer References:

AWS X-Ray Documentation:

Instrumenting your application:

Viewing the Service Map:

Tracing Microservices with AWS X-Ray:

Amazon S3 event notifications can invoke AWS Lambda functions at very high rates during traffic spikes. In this scenario, up to 500 objects per minute can result in hundreds of concurrent Lambda invocations. By default, Lambda functions share the account’s unreserved concurrency pool , which can cause throttling if the pool is exhausted by sudden bursts.

AWS Lambda reserved concurrency guarantees a specific number of concurrent executions for a function. By configuring reserved concurrency, the developer ensures that sufficient execution capacity is always available for this specific function, regardless of other Lambda workloads in the account. This prevents throttling during high-volume S3 event bursts.

Increasing the timeout (Option A) does not address concurrency limits. Adding a layer (Option B) does not solve invocation throttling. Decreasing memory (Option D) can actually worsen performance and increase execution time.

AWS documentation explicitly recommends reserved concurrency when workloads experience unpredictable or bursty invocation patterns and must run reliably. Therefore, reserving concurrency is the correct and AWS-recommended solution.