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Amazon AWS Certified DevOps Engineer - Professional Sample Questions (Q194-Q199):

NEW QUESTION # 194
To run an application, a DevOps engineer launches an Amazon EC2 instance with public IP addresses in a public subnet. A user data script obtains the application artifacts and installs them on the instances upon launch. A change to the security classification of the application now requires the instances to run with no access to the internet. While the instances launch successfully and show as healthy, the application does not seem to be installed.
Which of the following should successfully install the application while complying with the new rule?

A. Set up a NAT gateway. Deploy the EC2 instances to a private subnet. Update the private subnet's route table to use the NAT gateway as the default route.
B. Launch the instances in a public subnet with Elastic IP addresses attached. Once the application is installed and running, run a script to disassociate the Elastic IP addresses afterwards.
C. Publish the application artifacts to an Amazon S3 bucket and create a VPC endpoint for S3. Assign an IAM instance profile to the EC2 instances so they can read the application artifacts from the S3 bucket.
D. Create a security group for the application instances and allow only outbound traffic to the artifact repository. Remove the security group rule once the install is complete.

Answer: C

Explanation:
EC2 instances running in private subnets of a VPC can now have controlled access to S3 buckets, objects, and API functions that are in the same region as the VPC. You can use an S3 bucket policy to indicate which VPCs and which VPC Endpoints have access to your S3 buckets 1- https://aws.amazon.com/pt/blogs/aws/new-vpc-endpoint-for-amazon-s3/

NEW QUESTION # 195
A company runs a microservices application on Amazon Elastic Kubernetes Service (Amazon EKS). Users recently reported significant delays while accessing an account summary feature, particularly during peak business hours.
A DevOps engineer used Amazon CloudWatch metrics and logs to troubleshoot the issue. The logs indicated normal CPU and memory utilization on the EKS nodes. The DevOps engineer was not able to identify where the delays occurred within the microservices architecture.
The DevOps engineer needs to increase the observability of the application to pinpoint where the delays are occurring.
Which solution will meet these requirements?

A. Enable CloudWatch Container Insights for the EKS cluster. Use the Container Insights data to diagnose the delays.
B. Deploy the AWS X-Ray daemon as a DaemonSet in the EKS cluster. Use the X-Ray SDK to instrument the application code. Redeploy the application.
C. Create alarms based on the existing CloudWatch metrics. Set up an Amazon Simple Notification Service (Amazon SNS) topic to send email alerts.
D. Increase the timeout settings in the application code for network operations to allow more time for operations to finish.

Answer: B

Explanation:
AWS X-Ray provides distributed tracing for microservice-based applications. Deploying the X-Ray daemon as a DaemonSet in the EKS cluster and instrumenting the application with the X-Ray SDK enables end-to-end tracing across microservices, helping identify performance bottlenecks. This method is documented in "Using AWS X-Ray with Amazon EKS" (AWS Observability Guide).

NEW QUESTION # 196
A company has a single developer writing code for an automated deployment pipeline. The developer is storing source code in an Amazon S3 bucket for each project. The company wants to add more developers to the team but is concerned about code conflicts and lost work The company also wants to build a test environment to deploy newer versions of code for testing and allow developers to automatically deploy to both environments when code is changed in the repository.
What is the MOST efficient way to meet these requirements?

A. Enable versioning and branching on each S3 bucket, use the main branch for production code, and create a testing branch for code deployed to testing. Have developers use each branch for developing in each environment.
B. Create another S3 bucket for each project for testing code, and use an AWS Lambda function to promote code changes between testing and production buckets Enable versioning on all buckets to prevent code conflicts.
C. Create an AWS CodeCommit repository for each project, and use the main branch for production and test code with different deployment pipelines for each environment Use feature branches to develop new features.
D. Create an AWS CodeCommit repository tor each project, use the mam branch for production code: and create a testing branch for code deployed to testing Use feature branches to develop new features and pull requests to merge code to testing and main branches.

Answer: D

Explanation:
Creating an AWS CodeCommit repository for each project, using the main branch for production code, and creating a testing branch for code deployed to testing will meet the requirements. AWS CodeCommit is a managed revision control service that hosts Git repositories and works with all Git-based tools1. By using feature branches to develop new features and pull requests to merge code to testing and main branches, the developers can avoid code conflicts and lost work, and also implement code reviews and approvals. Option B is incorrect because creating another S3 bucket for each project for testing code and using an AWS Lambda function to promote code changes between testing and production buckets will not provide the benefits of revision control, such as tracking changes, branching, merging, and collaborating. Option C is incorrect because using the main branch for production and test code with different deployment pipelines for each environment will not allow the developers to test their code changes before deploying them to production.
Option D is incorrect because enabling versioning and branching on each S3 bucket will not work with Git- based tools and will not provide the same level of revision control as AWS CodeCommit. References:
* AWS CodeCommit
* Certified DevOps Engineer - Professional (DOP-C02) Study Guide (page 182)

NEW QUESTION # 197
A company deploys an application to Amazon EC2 instances. The application runs Amazon Linux 2 and uses AWS CodeDeploy. The application has the following file structure for its code repository:

The appspec.yml file has the following contents in the files section:

What will the result be for the deployment of the config.txt file?

A. The config.txt file will be deployed to /usr/local/src/config.txt and to /var/www/html/config/config txt.
B. The config.txt file will be deployed to only /var/www/html/config/config txt
C. The config txt file will be deployed to /usr/local/src/config.txt and to /var/www/html/application/web/config txt
D. The config.txt file will be deployed to only /usr/local/src/config txt

Answer: D

Explanation:
Deployment of config.txt file based on the appspec.yml:
The appspec.yml file specifies that config/config.txt should be copied to /usr/local/src/config.txt.
The source: / directive in the appspec.yml indicates that the entire directory structure starting from the root of the application source should be copied to the specified destination, which is /var/www/html.
Result of the Deployment:
The config.txt file will be specifically deployed to /usr/local/src/config.txt as per the explicit file mapping.
The entire directory structure including application/web will be copied to /var/www/html, but this does not include config/config.txt since it has a specific destination defined.
Thus, the config.txt file will be deployed only to /usr/local/src/config.txt.
Therefore, the correct answer is:
C . The config.txt file will be deployed to only /usr/local/src/config.txt.
Reference:
AWS CodeDeploy AppSpec File Reference
AWS CodeDeploy Deployment Process

NEW QUESTION # 198
A DevOps engineer is building an application that uses an AWS Lambda function to query an Amazon Aurora MySQL DB cluster. The Lambda function performs only read queries. Amazon EventBridge events invoke the Lambda function.
As more events invoke the Lambda function each second, the database's latency increases and the database's throughput decreases. The DevOps engineer needs to improve the performance of the application.
Which combination of steps will meet these requirements? (Select THREE.)

A. Implement the database connection opening outside the Lambda event handler code.
B. Connect to the Aurora cluster endpoint from the Lambda function.
C. Connect to the proxy endpoint from the Lambda function.
D. Implement database connection pooling inside the Lambda code. Set a maximum number of connections on the database connection pool.
E. Implement the database connection opening and closing inside the Lambda event handler code.
F. Use Amazon RDS Proxy to create a proxy. Connect the proxy to the Aurora cluster reader endpoint. Set a maximum connections percentage on the proxy.

Answer: A,C,F

Explanation:
Explanation
Verified answer: A, C, and E.
Short Explanation: To improve the performance of the application, the DevOps engineer should use Amazon RDS Proxy, implement the database connection opening outside the Lambda event handler code, and connect to the proxy endpoint from the Lambda function.
References:
* Amazon RDS Proxy is a fully managed, highly available database proxy for Amazon Relational Database Service (RDS) that makes applications more scalable, more resilient to database failures, and more secure1. By using Amazon RDS Proxy, the DevOps engineer can reduce the overhead of opening and closing connections to the database, which can improve latency and throughput2.
* The DevOps engineer should connect the proxy to the Aurora cluster reader endpoint, which allows read-only connections to one of the Aurora Replicas in the DB cluster3. This can help balance the load across multiple read replicas and improve performance for read-intensive workloads4.
* The DevOps engineer should implement the database connection opening outside the Lambda event handler code, which means using a global variable to store the database connection object5. This can enable connection reuse across multiple invocations of the Lambda function, which can reduce latency and improve performance.
* The DevOps engineer should connect to the proxy endpoint from the Lambda function, which is a unique URL that represents the proxy. This can allow the Lambda function to access the database through the proxy, which can provide benefits such as connection pooling, load balancing, failover handling, and enhanced security.
* The other options are incorrect because:
* Implementing database connection pooling inside the Lambda code is unnecessary and redundant when using Amazon RDS Proxy, which already provides connection pooling as a service.
* Implementing the database connection opening and closing inside the Lambda event handler code is inefficient and costly, as it can increase latency and consume more resources for each invocation of the Lambda function.
* Connecting to the Aurora cluster endpoint from the Lambda function is not optimal for read-only queries, as it can direct traffic to either the primary instance or one of the Aurora Replicas in the DB cluster. This can result in inconsistent performance and potential conflicts with write operations on the primary instance.

NEW QUESTION # 199
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