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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Security | 26% | - Application authentication and authorization
|
| Topic 2: Development with AWS Services | 32% | - AWS core services development
|
| Topic 3: Deployment | 24% | - Infrastructure as code
|
| Topic 4: Troubleshooting and Optimization | 18% | - Performance optimization
|
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NEW QUESTION # 367
A developer is working on a serverless application that needs to process any changes to an Amazon DynamoDB table with an AWS Lambda function.
How should the developer configure the Lambda function to detect changes to the DynamoDB table?
Answer: D
Explanation:
Explanation
Amazon DynamoDB is a fully managed NoSQL database service that provides fast and consistent performance with seamless scalability. DynamoDB Streams is a feature that captures data modification events in DynamoDB tables. The developer can enable DynamoDB Streams on the table and create a trigger to connect the DynamoDB stream to the Lambda function. This solution will enable the Lambda function to detect changes to the DynamoDB table in near real time.
References:
[Amazon DynamoDB]
[DynamoDB Streams - Amazon DynamoDB]
[Using AWS Lambda with Amazon DynamoDB - AWS Lambda]
NEW QUESTION # 368
A developer wants to deploy a new version of an AWS Elastic Beanstalk application. During deployment, the application must maintain full capacity and avoid service interruption. Additionally, the developer must minimize the cost of additional resources that support the deployment.
Which deployment method should the developer use to meet these requirements?
Answer: D
Explanation:
Explanation
The immutable deployment method is the best option for this scenario, because it meets the requirements of maintaining full capacity, avoiding service interruption, and minimizing the cost of additional resources.
The immutable deployment method creates a new set of instances in a separate Auto Scaling group and deploys the new version of the application to them. Then, it swaps the new instances with the old ones and terminates the old instances. This way, the application maintains full capacity during the deployment and avoids any downtime. The cost of additional resources is also minimized, because the new instances are only created for a short time and then replaced by the old ones.
The other deployment methods do not meet all the requirements:
The all at once method deploys the new version to all instances simultaneously, which causes a short period of downtime and reduced capacity.
The rolling with additional batch method deploys the new version in batches, but for the first batch it creates new instances instead of using the existing ones. This increases the cost of additional resources and reduces the capacity of the original environment.
The blue/green method creates a new environment with a new set of instances and deploys the new version to them. Then, it swaps the URLs between the old and new environments. This method maintains full capacity and avoids service interruption, but it also increases the cost of additional resources significantly, because it duplicates the entire environment.
NEW QUESTION # 369
A developer is building an event-driven application by using AWS Lambda and Amazon EventBridge. The Lambda function needs to push events to an EventBridge event bus. The developer uses an SDK to run the PutEvents EventBridge action and specifies no credentials in the code. After deploying the Lambda function, the developer notices that the function is failing and there are AccessDeniedException errors in the logs.
How should the developer resolve this issue?
Answer: A
NEW QUESTION # 370
A retail company runs a sales analytics application that uses an AWS Lambda function to process transaction data that is stored in Amazon DocumentDB. The application aggregates daily sales data across 500 stores and uses the data to generate reports for senior managers.
Application users report that the application is taking longer to generate reports and that their requests sometimes time out. A developer investigates and notices that the application's average response time for report generation has increased from 3 seconds to over 25 seconds.
The developer needs to identify the application's performance bottlenecks.
Which solution will meet this requirement with the LEAST operational overhead?
Answer: A
Explanation:
The goal is to identify performance bottlenecks across a Lambda function that calls a database (DocumentDB). The most operationally efficient way to pinpoint where time is being spent-without building custom logging/metrics pipelines-is to use distributed tracing. AWS X-Ray provides end-to-end request traces, timing breakdowns, and service maps that help identify whether latency is dominated by Lambda initialization, downstream calls, or database queries.
By enabling X-Ray tracing on the Lambda function, the developer can capture traces for report-generation requests and examine segments that show duration spent inside the function and in downstream dependencies.
To specifically diagnose database time, the developer can add custom subsegments around DocumentDB operations (query execution, connection acquisition, cursor iteration). This produces precise timing data for each step, making it straightforward to identify slow queries, excessive connection setup time, or serialization overhead. Because X-Ray aggregates and visualizes traces, the developer can quickly compare "fast" and
"slow" traces and isolate the bottleneck.
Option B focuses on errors and generic metrics dashboards; it's useful for monitoring, but it won't precisely attribute the extra 22+ seconds to a particular downstream call path. Option C proposes performance improvements (pooling/async), but the question asks to identify bottlenecks first, and it also requires code changes and validation without confirming the root cause. Option D requires adding detailed logging statements and then querying logs; this is more development effort and more ongoing log volume/cost than turning on X-Ray and using trace analysis, especially when the intent is bottleneck identification rather than permanent instrumentation.
Therefore, A is the best choice: enable AWS X-Ray for the Lambda function and trace DocumentDB interactions with custom subsegments to quickly and efficiently identify the specific source(s) of increased latency.
NEW QUESTION # 371
A developer has created a repository in AWS CodeArtifact. The development team needs to receive notifications when new packages are published to the repository.
Which solution will meet this requirement with the LEAST operational overhead?
Answer: C
Explanation:
AWS CodeArtifact emits events when repository actions occur, such as publishing a new package. AWS documentation recommends Amazon EventBridge as the native service for routing AWS service events to targets with minimal configuration and no infrastructure to manage.
By creating an EventBridge rule that matches CodeArtifact package publication events and routing those events directly to an Amazon SNS topic, the developer can notify the team immediately. SNS provides built- in email subscriptions, retries, and delivery guarantees without custom code.
Option C is the most operationally efficient because it uses fully managed, serverless services and requires no custom compute, code maintenance, or orchestration. EventBridge directly supports SNS as a target, making the configuration straightforward.
Option A is invalid because CodeArtifact does not directly publish notifications to SNS topics. Options B and D introduce unnecessary complexity by adding Lambda or Step Functions and Amazon SES, increasing operational overhead without added value.
Therefore, using EventBridge to route CodeArtifact events to SNS is the AWS-recommended and simplest solution.
NEW QUESTION # 372
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