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

The correct answer is D because Amazon API Gateway REST APIs support canary deployments for stages , which allow a developer to send a controlled percentage of production traffic to a new API deployment while the rest of the traffic continues to use the current deployment. Setting the canary percentage to 20% directly satisfies the requirement to route 20% of traffic to the new release and 80% to the existing production release.

This is the best approach because API Gateway canary deployments are specifically designed to reduce the blast radius of new releases in production. AWS documentation explains that canary releases enable testing of a new deployment with a subset of client traffic before promoting it fully. Since the canary runs within the same production stage , this minimizes the number of errors experienced by any single customer compared to less controlled alternatives. It is also cleaner than routing users to the testing stage, because a testing stage often has different configuration, data, or dependencies and is not intended to serve production traffic.

Option A is incorrect because partially deploying only some planned changes is not a safe traffic-routing strategy. Option B is incorrect because weighted Route 53 routing between production and testing stages does not provide the same controlled deployment semantics and may send the same customer to inconsistent backends. Option C is incorrect because placing an ALB in front of API Gateway is unnecessary and not the intended deployment pattern for API Gateway stage traffic shifting.

Therefore, API Gateway stage canary settings are the AWS-native solution that best meets the requirement.

The response from the API call indicates that the ProvisionedThroughputExceededException exception has occurred. This exception means that the rate of incoming requests exceeds the throughput limit for one or more shards in a stream. To mitigate this exception, the developer can use one or more of the following techniques:

Implement retries with exponential backoff. This will introduce randomness in the retry intervals and avoid overwhelming the shards with retries.

Reduce the frequency and/or size of the requests. This will reduce the load on the shards and avoid throttling errors.

Increase the number of shards in the stream. This will increase the throughput capacity of the stream and accommodate higher request rates.

Use a PutRecord API instead of PutRecords. This will reduce the number of records per request and avoid exceeding the payload limit.

Comprehensive and Detailed Step-by-Step Explanation:

To confirm that the HTTP headers, body, and responses meet expectations, you need to test the specific HTTP Task state in isolation and inspect the details.

Option A: TestState API with TRACE:

The TestState API allows developers to test individual states in a state machine without executing the entire workflow.

Setting the inspection level to TRACE provides detailed information about the HTTP request and response, including headers, body, and status codes.

This option provides the precise and granular testing required to verify the HTTP Task functionality.

Why Other Options Are Incorrect:

Option B: The DEBUG inspection level provides less detailed information than TRACE and focuses on general debugging, not a detailed view of HTTP interactions.

Option C: Step Functions does not have a " data flow simulator " to test individual tasks; this option is not valid.

Option D: Changing the state machine’s log level to ALL increases logging granularity for the entire state machine but does not allow isolated testing of a specific HTTP Task.

Comprehensive Detailed Step by Step Explanation with All AWS Developer References:

To ensure that only a specific AWS Step Functions state machine (myStateMachine) can assume the service role, you must configure the correct trust policy in AWS IAM.

Trust Policies: Trust policies determine which entities (services or users) are allowed to assume the role. In this case, we want to restrict the trust policy to only allow the specific state machine (myStateMachine) to assume the role.

Using ArnLike: The condition " ArnLike " is used to specify that the SourceArn (which refers to the ARN of the entity assuming the role) must match a specific ARN. Option A specifies the exact ARN of the myStateMachine state machine, ensuring that only this state machine can assume the role.

Option B: This option is incorrect because it uses a wildcard (*) for the account ID, which would allow any state machine in the ap-south-1 region to assume the role, not just the specific one.

AWS Step Functions IAM Policies