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| Section | Weight | Objectives |
|---|
| Security | 26% | - Secure application data
- 1. Implement encryption at rest and in transit
- 2. Manage secrets and credentials securely
- Apply security best practices
- 1. Validate application security configurations
- 2. Follow AWS Well-Architected Framework security principles
- Implement authentication and authorization
- 1. Use Amazon Cognito for identity management
- 2. Manage IAM roles, policies, and permissions
|
| Troubleshooting and Optimization | 18% | - Troubleshoot application issues
- 1. Analyze logs, metrics, and traces
- 2. Use Amazon CloudWatch, AWS X-Ray for monitoring
- Debug and resolve errors
- 1. Resolve integration and configuration problems
- 2. Identify and fix code defects
- Optimize application performance
- 1. Optimize resource usage and costs
- 2. Improve latency and throughput
|
| Deployment | 24% | - Prepare application artifacts for deployment
- 1. Package code and dependencies
- 2. Use infrastructure as code (AWS CloudFormation, AWS SAM)
- Implement CI/CD pipelines
- 1. Automate deployment and testing workflows
- 2. Use AWS CodePipeline, CodeBuild, CodeDeploy
- Deploy applications on AWS
- 1. Deploy to AWS Lambda, Amazon EC2, Elastic Beanstalk
- 2. Perform safe updates and rollbacks
|
| Development with AWS Services | 32% | - Write code for applications hosted on AWS
- 1. Develop serverless applications
- 2. Use AWS SDKs and APIs
- 3. Implement architectural patterns
- Integrate AWS services into applications
- 1. Use AWS Lambda, API Gateway, Amazon EventBridge
- 2. Implement messaging and event-driven workflows
- Interact with AWS data services
- 1. Work with Amazon DynamoDB, Amazon S3
- 2. Implement caching and data storage strategies
|
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Amazon AWS Certified Developer - Associate Sample Questions (Q543-Q548):
NEW QUESTION # 543
A developer is trying get data from an Amazon DynamoDB table called demoman-table. The developer configured the AWS CLI to use a specific IAM use's credentials and ran the following command.

The command returned errors and no rows were returned.
What is the MOST likely cause of these issues?
- A. The command is incorrect; it should be rewritten to use put-item with a string argument
- B. The developer needs to log a ticket with AWS Support to enable access to the demoman-table
- C. The IAM user needs an associated policy with read access to demoman-table
- D. Amazon DynamoOB cannot be accessed from the AWS CLI and needs to called via the REST API
Answer: C
Explanation:
Explanation
This solution will most likely solve the issues because it will grant the IAM user the necessary permission to access the DynamoDB table using the AWS CLI command. The error message indicates that the IAM user does not have sufficient access rights to perform the scan operation on the table. Option A is not optimal because it will change the command to use put-item instead of scan, which will not achieve the desired result of getting data from the table. Option B is not optimal because it will involve contacting AWS Support, which may not be necessary or efficient for this issue. Option C is not optimal because it will state that DynamoDB cannot be accessed from the AWS CLI, which is incorrect as DynamoDB supports AWS CLI commands.
References: AWS CLI for DynamoDB, [IAM Policies for DynamoDB]
NEW QUESTION # 544
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?
- A. Create an Amazon Kinesis Data Firehose delivery stream, and attach it to the DynamoDB table. Configure the delivery stream destination as the Lambda function.
- B. Enable DynamoDB Streams on the table. Create a trigger to connect the DynamoDB stream to the Lambda function.
- C. Create an Amazon EventBridge rule to invoke the Lambda function on a regular schedule. Conned to the DynamoDB table from the Lambda function to detect changes.
- D. Create an Amazon Kinesis data stream, and attach it to the DynamoDB table. Create a trigger to connect the data stream to the Lambda function.
Answer: B
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.
Reference:
[Amazon DynamoDB]
[DynamoDB Streams - Amazon DynamoDB]
[Using AWS Lambda with Amazon DynamoDB - AWS Lambda]
NEW QUESTION # 545
A developer is designing a serverless application with two AWS Lambda functions to process photos. One Lambda function stores objects in an Amazon S3 bucket and stores the associated metadata in an Amazon DynamoDB table. The other Lambda function fetches the objects from the S3 bucket by using the metadata from the DynamoDB table. Both Lambda functions use the same Python library to perform complex computations and are approaching the quota for the maximum size of zipped deployment packages.
What should the developer do to reduce the size of the Lambda deployment packages with the LEAST operational overhead?
- A. Package each Python library in its own .zip file archive. Deploy each Lambda function with its own copy of the library.
- B. Download the Python library to an S3 bucket. Program the Lambda functions to reference the object URLs.
- C. Create a Lambda layer with the required Python library. Use the Lambda layer in both Lambda functions.
- D. Combine the two Lambda functions into one Lambda function. Deploy the Lambda function as a single .
zip file archive.
Answer: C
Explanation:
AWS Lambda is a service that lets developers run code without provisioning or managing servers. Lambda layers are a distribution mechanism for libraries, custom runtimes, and other dependencies. The developer can create a Lambda layer with the required Python library and use the layer in both Lambda functions. This will reduce the size of the Lambda deployment packages and avoid reaching the quota for the maximum size of zipped deployment packages. The developer can also benefit from using layers to manage dependencies separately from function code.
References:
* [What Is AWS Lambda? - AWS Lambda]
* [AWS Lambda Layers - AWS Lambda]
NEW QUESTION # 546
A company has on-premises data centers that run an image processing service. The service consists of containerized applications that run on Kubernetes clusters. All the applications have access to the same NFS share for files and data storage.
The company is running out of NFS capacity in the data centers and needs to migrate to AWS as soon as possible. The Kubernetes clusters must be highly available on AWS.
Which combination of actions will meet these requirements? (Choose two.)
- A. Transfer the information that is in the NFS share to an Amazon Elastic File System (Amazon EFS) volume. Upload the container images to Amazon Elastic Container Registry (Amazon ECR).
- B. Create an Amazon Elastic Kubernetes Service (Amazon EKS) cluster to run the applications.Configure each node of the cluster to mount the Amazon Elastic File System (Amazon EFS) volume at the required path for the container images.
- C. Transfer the information that is in the NFS share to an Amazon Elastic Block Store (Amazon EBS) volume. Upload the container images to Amazon Elastic Container Registry (Amazon ECR).
- D. Create an Amazon Elastic Kubernetes Service (Amazon EKS) cluster to run the applications.
Configure each node of the cluster to mount the Amazon Elastic Block Store (Amazon EBS) volume at the required path for the container images. - E. Create an Amazon Elastic Container Service (Amazon ECS) cluster to run the applications.
Configure each node of the cluster to mount the Amazon Elastic Block Store (Amazon EBS) volume at the required path for the container images.
Answer: A,B
Explanation:
https://docs.aws.amazon.com/efs/latest/ug/efs-onpremises.html
NEW QUESTION # 547
A developer manages an AWS Lambda function written in the latest version of .NET. The function processes data from an Amazon S3 bucket sporadically throughout the day. The function experiences cold start times of up to 10 seconds, negatively affecting latency-sensitive downstream workloads.
The developer needs to improve the function's performance.
Which solution will meet this requirement?
- A. Publish the function and create an alias. Enable Lambda SnapStart on the published version.
- B. Add the Lambda function to a VPC and configure an S3 gateway endpoint.
- C. Enable reserved concurrency on the function.
- D. Configure Lambda layers to separate .NET dependencies from the function code.
Answer: A
Explanation:
AWS Lambda SnapStart is designed specifically to reduce cold start latency for Java and .NET runtimes.
SnapStart works by initializing the function once, taking a snapshot of the execution environment, and then reusing that snapshot for future cold starts. This dramatically reduces startup time, often from several seconds to milliseconds.
SnapStart requires the function to be published as a version, and an alias must reference that version. AWS documentation clearly states that SnapStart is the recommended solution for latency-sensitive Lambda workloads with infrequent invocations.
Reserved concurrency (Option B) limits scaling but does not eliminate cold starts. Lambda layers (Option C) improve code organization but have minimal impact on cold start latency. Adding the function to a VPC (Option D) typically increases cold start time due to network interface initialization.
Therefore, enabling SnapStart on a published .NET Lambda function is the correct and AWS-endorsed solution.
NEW QUESTION # 548
......
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