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Amazon AWS Certified DevOps Engineer - Professional Sample Questions (Q19-Q24):

NEW QUESTION # 19
A company has an AWS CodePipeline pipeline that is configured with an Amazon S3 bucket in the eu-west-1 Region. The pipeline deploys an AWS Lambda application to the same Region. The pipeline consists of an AWS CodeBuild project build action and an AWS CloudFormation deploy action.
The CodeBuild project uses the aws cloudformation package AWS CLI command to build an artifact that contains the Lambda function code's .zip file and the CloudFormation template. The CloudFormation deploy action references the CloudFormation template from the output artifact of the CodeBuild project's build action.
The company wants to also deploy the Lambda application to the us-east-1 Region by using the pipeline in eu- west-1. A DevOps engineer has already updated the CodeBuild project to use the aws cloudformation package command to produce an additional output artifact for us-east-1.
Which combination of additional steps should the DevOps engineer take to meet these requirements? (Choose two.)

A. Create a new CloudFormation deploy action for us-east-1 in the pipeline. Configure the new deploy action to use the CloudFormation template from the us-east-1 output artifact.
B. Modify the CloudFormation template to include a parameter for the Lambda function code's zip file location. Create a new CloudFormation deploy action for us-east-1 in thepipeline. Configure the new deploy action to pass in the us-east-1 artifact location as a parameter override.
C. Modify the pipeline to include the S3 bucket for us-east-1 as an artifact store. Create a new CloudFormation deploy action for us-east-1 in the pipeline. Configure the new deploy action to use the CloudFormation template from the us-east-1 output artifact.
D. Create an S3 bucket in us-east-1. Configure S3 Cross-Region Replication (CRR) from the S3 bucket in eu-west-1 to the S3 bucket in us-east-1.
E. Create an S3 bucket in us-east-1. Configure the S3 bucket policy to allow CodePipeline to have read and write access.

Answer: A,B

Explanation:
A: The CloudFormation template should be modified to include a parameter that indicates the location of the .
zip file containing the Lambda function's code. This allows the CloudFormation deploy action to use the correct artifact depending on the region. This is critical because Lambda functions need to reference their code artifacts from the same region they are being deployed in. B. You would also need to create a new CloudFormation deploy action for the us-east-1 Region within the pipeline. This action should be configured to use the CloudFormation template from the artifact that was specifically created for us-east-1.

NEW QUESTION # 20
A company's web app publishes JSON logs with transaction status to CloudWatch Logs. The company wants a dashboard showing the number of successful transactions with the least operational overhead.
Which solution meets this?

A. Create a Kinesis data stream subscribed to the log group; filter logs by success; send to Lambda; Lambda publishes custom metrics; dashboard uses metric graph.
B. Create an OpenSearch cluster and subscription filter to send logs; create OpenSearch dashboard with queries for success.
C. Create a CloudWatch metric filter on the log group with a pattern matching success; create CloudWatch dashboard with metric graph.
D. Create a CloudWatch subscription filter with Lambda to parse logs and publish custom metrics; create CloudWatch dashboard with metric graph.

Answer: C

Explanation:
* CloudWatchmetric filterscan parse logs directly to create metrics without additional infrastructure.
* Metric filters combined with CloudWatch dashboards provide the simplest and most operationally efficient solution.
* Options A, B, and D add complexity with additional services (OpenSearch, Lambda, Kinesis).
References:
CloudWatch Logs Metric Filters
CloudWatch Dashboards

NEW QUESTION # 21
A DevOps engineer manages a company's Amazon Elastic Container Service (Amazon ECS) cluster. The cluster runs on several Amazon EC2 instances that are in an Auto Scaling group. The DevOps engineer must implement a solution that logs and reviews all stopped tasks for errors.
Which solution will meet these requirements?

A. Create an Amazon EventBridge rule to capture task state changes. Send the event to Amazon CloudWatch Logs. Use CloudWatch Logs Insights to investigate stopped tasks.
B. Configure tasks to write log data in the embedded metric format. Store the logs in Amazon CloudWatch Logs. Monitor the ContainerInstanceCount metric for changes.
C. Configure the EC2 instances to store logs in Amazon CloudWatch Logs. Create a CloudWatch Contributor Insights rule that uses the EC2 instance log data. Use the Contributor Insights rule to investigate stopped tasks.
D. Configure an EC2 Auto Scaling lifecycle hook for the EC2_INSTANCE_TERMINATING scale-in event. Write the SystemEventLog file to Amazon S3. Use Amazon Athena to query the log file for errors.

Answer: A

Explanation:
Explanation
The best solution to log and review all stopped tasks for errors is to use Amazon EventBridge and Amazon CloudWatch Logs. Amazon EventBridge allows the DevOps engineer to create a rule that matches task state change events from Amazon ECS. The rule can then send the event data to Amazon CloudWatch Logs as the target. Amazon CloudWatch Logs can store and monitor the log data, and also provide CloudWatch Logs Insights, a feature that enables the DevOps engineer to interactively search and analyze the log data. Using CloudWatch Logs Insights, the DevOps engineer can filter and aggregate the log data based on various fields, such as cluster, task, container, and reason. This way, the DevOps engineer can easily identify and investigate the stopped tasks and their errors.
The other options are not as effective or efficient as the solution in option A. Option B is not suitable because the embedded metric format is designed for custom metrics, not for logging task state changes. Option C is not feasible because the EC2 instances do not store the task state change events in their logs. Option D is not relevant because the EC2_INSTANCE_TERMINATING lifecycle hook is triggered when an EC2 instance is terminated by the Auto Scaling group, not when a task is stopped by Amazon ECS.
References:
1: Creating a CloudWatch Events Rule That Triggers on an Event - Amazon Elastic Container Service
2: Sending and Receiving Events Between AWS Accounts - Amazon EventBridge
3: Working with Log Data - Amazon CloudWatch Logs
4: Analyzing Log Data with CloudWatch Logs Insights - Amazon CloudWatch Logs
5: Embedded Metric Format - Amazon CloudWatch
6: Amazon EC2 Auto Scaling Lifecycle Hooks - Amazon EC2 Auto Scaling

NEW QUESTION # 22
A video-sharing company stores its videos in an Amazon S3 bucket. The company needs to analyze user access patterns such as the number of users who access a specific video each month.
Which solution will meet these requirements with the LEAST development effort?

A. Record a log message in Amazon CloudWatch Logs for every S3 object access event. Configure a log stream in CloudWatch Logs to write the file access information, including user ID, S3 bucket ID, and file key, to an Amazon Managed Service for Apache Flink application. Perform a sliding window analysis on the user access patterns.
B. Invoke an AWS Lambda function for every S3 object access event. Configure the Lambda function to write the file access information, including user ID, S3 bucket ID, and file key, to an Amazon Aurora database. Run SQL queries on the Aurora database to analyze the user access patterns.
C. Enable Amazon S3 server access logging. Load the access logs into an Amazon Aurora database. Run SQL queries on the Aurora database to analyze the user access patterns.
D. Enable Amazon S3 server access logging. Use Amazon Athena to create an external table that contains the access logs. Run SQL queries on the Athena table to analyze the user access patterns.

Answer: D

Explanation:
Amazon S3 can generate server access logs that record detailed information about each request, including requester, bucket, key, operation, time, and status. These logs are written as objects to an S3 bucket. To analyze access patterns, the simplest and most serverless approach is to use Amazon Athena directly on those logs without building ingestion pipelines or databases.
Option B enables S3 server access logging and then creates an Athena external table over the log bucket.
AWS provides standard log formats and even example schemas for S3 access logs. The analytics team can run ad hoc SQL queries to count the number of accesses per object per time period, filter by user, and perform aggregations, all without provisioning compute or managing databases.
Option A requires ingesting logs into Aurora, which adds ETL complexity and ongoing database management. Option C requires a Lambda function for every access event plus DB writes, which is more complex and potentially expensive at scale. Option D uses CloudWatch Logs and Managed Flink, which is more suited for streaming analytics and is significantly more complex than necessary for monthly summary reports.
Therefore, Option B provides the required analysis with the least development and operational effort.

NEW QUESTION # 23
A company has an application and a CI/CD pipeline. The CI/CD pipeline consists of an AWS CodePipeline pipeline and an AWS CodeBuild project. The CodeBuild project runs tests against the application as part of the build process and outputs a test report. The company must keep the test reports for 90 days.
Which solution will meet these requirements?

A. Add a new stage in the CodePipeline pipeline. Configure a test action type with the appropriate path and format for the reports. Configure the report expiration time to be 90 days in the CodeBuild project buildspec file.
B. Add a report group in the CodeBuild project buildspec file with the appropriate path and format for the reports. Create an Amazon S3 bucket to store the reports. Configure an Amazon EventBridge rule that invokes an AWS Lambda function to copy the reports to the S3 bucket when a build is completed.
Create an S3 Lifecycle rule to expire the objects after 90 days.
C. Add a new stage in the CodePipeline pipeline after the stage that contains the CodeBuild project. Create an Amazon S3 bucket to store the reports. Configure an S3 deploy action type in the new CodePipeline stage with the appropriate path and format for the reports.
D. Add a report group in the CodeBuild project buildspec file with the appropriate path and format for the reports. Create an Amazon S3 bucket to store the reports. Configure the report group as an artifact in the CodeBuild project buildspec file. Configure the S3 bucket as the artifact destination. Set the object expiration to 90 days.

Answer: B

Explanation:
The correct solution is to add a report group in the AWS CodeBuild project buildspec file with the appropriate path and format for the reports. Then, create an Amazon S3 bucket to store the reports. You should configure an Amazon EventBridge rule that invokes an AWS Lambda function to copy the reports to the S3 bucket when a build is completed. Finally, create an S3 Lifecycle rule to expire the objects after 90 days. This approach allows for the automated transfer of reports to long-term storage and ensures they are retained for the required duration without manual intervention1.
AWS CodeBuild User Guide on test reporting1.
AWS CodeBuild User Guide on working with report groups2.
AWS Documentation on using AWS CodePipeline with AWS CodeBuild3.

NEW QUESTION # 24
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