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Amazon AWS Certified Developer - Associate Sample Questions (Q216-Q221):
NEW QUESTION # 216
A developer is working on a Python application that runs on Amazon EC2 instances. The developer wants to enable tracing of application requests to debug performance issues in the code.
Which combination of actions should the developer take to achieve this goal? (Select TWO)
- A. Configure the application to write JSON-formatted togs to /var/log/cloudwatch.
- B. Install and configure the AWS X-Ray SDK for Python in the application.
- C. Install the AWS X-Ray daemon on the EC2 instances.
- D. Configure the application to write trace data to /Var/log-/xray.
- E. Install the Amazon CloudWatch agent on the EC2 instances.
Answer: B,C
Explanation:
This solution will meet the requirements by using AWS X-Ray to enable tracing of application requests to debug performance issues in the code. AWS X-Ray is a service that collects data about requests that the applications serve, and provides tools to view, filter, and gain insights into that data. The developer can install the AWS X-Ray daemon on the EC2 instances, which is a software that listens for traffic on UDP port 2000, gathers raw segment data, and relays it to the X-Ray API. The developer can also install and configure the AWS X-Ray SDK for Python in the application, which is a library that enables instrumenting Python code to generate and send trace data to the X-Ray daemon. Option A is not optimal because it will install the Amazon CloudWatch agent on the EC2 instances, which is a software that collects metrics and logs from EC2 instances and on-premises servers, not application performance data. Option C is not optimal because it will configure the application to write JSON-formatted logs to /var/log/cloudwatch, which is not a valid path or destination for CloudWatch logs. Option D is not optimal because it will configure the application to write trace data to /var/log/xray, which is also not a valid path or destination for X-Ray trace data.
References: [AWS X-Ray], [Running the X-Ray Daemon on Amazon EC2]
NEW QUESTION # 217
A developer uses Amazon S3 Event Notifications to invoke AWS Lambda functions. The Lambda functions process images after the images are uploaded to S3 buckets. The developer has set up a development S3 bucket, a production S3 bucket, a development Lambda function, and a production Lambda function in the same AWS account.
The developer notices that uploads to the development S3 bucket wrongly invoke the production Lambda function. The developer must prevent development data from affecting the production Lambda function.
What should the developer do to meet these requirements?
- A. Separate the development environment and the production environment into their own AWS accounts. Add a resource policy to the Lambda functions to allow only S3 bucket events in the same account to invoke the functions.
- B. Update the execution role for the production Lambda function. Add a policy that allows the execution role to read from only the production S3 bucket.
- C. Separate the development environment and the production environment into their own AWS accounts. Update the execution role for each Lambda function. Add a policy that allows the execution role to read from only the S3 bucket that is in the same account.
- D. Update the S3 bucket policy for the production S3 bucket to invoke the production Lambda function. Update the S3 bucket policy for the development S3 bucket to invoke the development Lambda function.
Answer: D
NEW QUESTION # 218
A developer is creating an AWS Lambda function in VPC mode An Amazon S3 event will invoke the Lambda function when an object is uploaded into an S3 bucket The Lambda function will process the object and produce some analytic results that will be recorded into a file Each processed object will also generate a log entry that will be recorded into a file.
Other Lambda functions. AWS services, and on-premises resources must have access to the result files and log file. Each log entry must also be appended to the same shared log file. The developer needs a solution that can share files and append results into an existing file.
Which solution should the developer use to meet these requirements?
- A. Create an Amazon Elastic File System (Amazon EFS) file system. Mount the EFS file system in Lambda. Store the result files and log file in the mount point. Append the log entries to the log file.
- B. Create an Amazon Elastic Block Store (Amazon EBS) Multi-Attach enabled volume Attach the EBS volume to all Lambda functions. Update the Lambda function code to download the log file, append the log entries, and upload the modified log file to Amazon EBS
- C. Create a reference to the /opt storage directory Store the result files and log file by using the directory reference Append the log entry to the log file
- D. Create a reference to the /tmp local directory. Store the result files and log file by using the directory reference. Append the log entry to the log file.
Answer: A
Explanation:
* Amazon EFS: A network file system (NFS) providing shared, scalable storage across multiple Lambda functions and other AWS resources.
* Lambda Mounting: EFS file systems can be mounted within Lambda functions to access a shared storage space.
* Log Appending: EFS supports appending data to existing files, making it ideal for the log file scenario.
References:
* Amazon EFS Documentation: https://docs.aws.amazon.com/efs/
* Using Amazon EFS with AWS Lambda: https://docs.aws.amazon.com/lambda/latest/dg/services-efs.
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NEW QUESTION # 219
A company is using Amazon OpenSearch Service to implement an audit monitoring system. A developer needs to create an AWS Cloudformation custom resource that is associated with an AWS Lambda function to configure the OpenSearch Service domain. The Lambda function must access the OpenSearch Service domain by using Open Search Service internal master user credentials.
What is the MOST secure way to pass these credentials to the Lambdas function?
- A. Use a CloudFormation parameter to pass the master user credentials at deployment to the OpenSearch Service domain's MasterUserOptions and to create a parameter. In AWS Systems Manager Parameter Store. Set the No Echo attribute to true. Create an 1AM role that has the ssm GetParameter permission.
Assign me role to the Lambda function. Store me parameter name as the Lambda function's environment variable. Resolve the parameter's value at runtime. - B. Use CloudFoimalion to create an AWS Secrets Manager Secret. Use a CloudFormation dynamic reference to retrieve the secret's value for the OpenSearch Service domain's MasterUserOptions. Create an 1AM role that has the secrets manager. GetSecretvalue permission. Assign the role to the Lambda Function Store the secrets name as the Lambda function's environment variable. Resole the secret's value at runtime.
- C. Use a CloudFormation parameter to pass the master uses credentials at deployment to the OpenSearch Service domain's MasterUserOptions and the Lambda function's environment varleWe Encrypt the parameters value by using the AWS Key Management Service (AWS KMS) encrypt command.
- D. Use a CloudFormation parameter to pass the master user credentials at deployment to the OpenSearch Service domain's MasterUserOptions and the Lambda function's environment variable. Set the No Echo attenuate to true.
Answer: B
Explanation:
Explanation
The solution that will meet the requirements is to use CloudFormation to create an AWS Secrets Manager secret. Use a CloudFormation dynamic reference to retrieve the secret's value for the OpenSearch Service domain's MasterUserOptions. Create an IAM role that has the secretsmanager:GetSecretValue permission.
Assign the role to the Lambda function. Store the secret's name as the Lambda function's environment variable. Resolve the secret's value at runtime. This way, the developer can pass the credentials to the Lambda function in a secure way, as AWS Secrets Manager encrypts and manages the secrets. The developer can also use a dynamic reference to avoid exposing the secret's value in plain text in the CloudFormation template. The other options either involve passing the credentials as plain text parameters, which is not secure, or encrypting them with AWS KMS, which is less convenient than using AWS Secrets Manager.
NEW QUESTION # 220
A web application is using Amazon Kinesis Data Streams for clickstream data that may not be consumed for up to 12 hours.
How can the developer implement encryption at rest for data within the Kinesis Data Streams?
- A. Enable server-side encryption in Kinesis Data Streams.
- B. Use Amazon Kinesis Consumer Library.
- C. Encrypt the data once it is at rest with a Lambda function.
- D. Enable SSL connections to Kinesis.
Answer: A
Explanation:
Amazon Kinesis Data Streams is designed for real-time data streaming and allows multiple consumers to process data concurrently and in real-time. It can handle millions of events and provides a scalable and cost-effective solution for handling high-throughput data streams.
NEW QUESTION # 221
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