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Amazon AWS Certified DevOps Engineer - Professional Sample Questions (Q152-Q157):
NEW QUESTION # 152
A company deploys a web application on Amazon EC2 instances that are behind an Application Load Balancer (ALB). The company stores the application code in an AWS CodeCommit repository. When code is merged to the main branch, an AWS Lambda function invokes an AWS CodeBuild project. The CodeBuild project packages the code, stores the packaged code in AWS CodeArtifact, and invokes AWS Systems Manager Run Command to deploy the packaged code to the EC2 instances.
Previous deployments have resulted in defects, EC2 instances that are not running the latest version of the packaged code, and inconsistencies between instances.
Which combination of actions should a DevOps engineer take to implement a more reliable deployment solution? (Select TWO.)
- A. Create a pipeline in AWS CodePipeline that uses the CodeCommit repository as a source provider.
Create separate pipeline stages that run a CodeBuild project to build and then test the application. In the pipeline, pass the CodeBuild project output artifact to an AWS CodeDeploy action. - B. Create an Amazon S3 bucket. Modify the CodeBuild project to store the packages in the S3 bucket instead of in CodeArtifact. Use deploy actions in CodeDeploy to deploy the artifact to the EC2 instances.
- C. Create a pipeline in AWS CodePipeline that uses the CodeCommit repository as a source provider.
Configure pipeline stages that run the CodeBuild project in parallel to build and test the application. In the pipeline, pass the CodeBuild project output artifact to an AWS CodeDeploy action. - D. Create an AWS CodeDeploy application and a deployment group to deploy the packaged code to the EC2 instances. Configure the ALB for the deployment group.
- E. Create individual Lambda functions that use AWS CodeDeploy instead of Systems Manager to run build, test, and deploy actions.
Answer: C,D
Explanation:
Explanation
To implement a more reliable deployment solution, a DevOps engineer should take the following actions:
* Create a pipeline in AWS CodePipeline that uses the CodeCommit repository as a source provider.
Configure pipeline stages that run the CodeBuild project in parallel to build and test the application. In the pipeline, pass the CodeBuild project output artifact to an AWS CodeDeploy action. This action will improve the deployment reliability by automating the entire process from code commit to deployment, reducing human errors and inconsistencies. By running the build and test stages in parallel, the pipeline can also speed up the delivery time and provide faster feedback. By using CodeDeploy as the deployment action, the pipeline can leverage the features of CodeDeploy, such as traffic shifting, health checks, rollback, and deployment configuration123
* Create an AWS CodeDeploy application and a deployment group to deploy the packaged code to the EC2 instances. Configure the ALB for the deployment group. This action will improve the deployment reliability by using CodeDeploy to orchestrate the deployment across multiple EC2 instances behind an ALB. CodeDeploy can perform blue/green deployments or in-place deployments with traffic shifting, which can minimize downtime and reduce risks. CodeDeploy can also monitor the health of the instances during and after the deployment, and automatically roll back if any issues are detected. By configuring the ALB for the deployment group, CodeDeploy can register and deregister instances from the load balancer as needed, ensuring that only healthy instances receive traffic45 The other options are not correct because they do not improve the deployment reliability or follow best practices. Creating separate pipeline stages that run a CodeBuild project to build and then test the application is not a good option because it will increase the pipeline execution time and delay the feedback loop. Creating individual Lambda functions that use CodeDeploy instead of Systems Manager to run build, test, and deploy actions is not a valid option because it will add unnecessary complexity and cost to the solution. Lambda functions are not designed for long-running tasks such as building or deploying applications. Creating an Amazon S3 bucket and modifying the CodeBuild project to store the packages in the S3 bucket instead of in CodeArtifact is not a necessary option because it will not affect the deployment reliability. CodeArtifact is a secure, scalable, and cost-effective package management service that can store and share software packages for application development67 References:
* 1: What is AWS CodePipeline? - AWS CodePipeline
* 2: Create a pipeline in AWS CodePipeline - AWS CodePipeline
* 3: Deploy an application with AWS CodeDeploy - AWS CodePipeline
* 4: What is AWS CodeDeploy? - AWS CodeDeploy
* 5: Configure an Application Load Balancer for your blue/green deployments - AWS CodeDeploy
* 6: What is AWS Lambda? - AWS Lambda
* 7: What is AWS CodeArtifact? - AWS CodeArtifact
NEW QUESTION # 153
A company is using AWS to run digital workloads. Each application team in the company has its own AWS account for application hosting. The accounts are consolidated in an organization in AWS Organizations.
The company wants to enforce security standards across the entire organization. To avoid noncompliance because of security misconfiguration, the company has enforced the use of AWS CloudFormation. A production support team can modify resources in the production environment by using the AWS Management Console to troubleshoot and resolve application-related issues.
A DevOps engineer must implement a solution to identify in near real time any AWS service misconfiguration that results in noncompliance. The solution must automatically remediate the issue within 15 minutes of identification. The solution also must track noncompliant resources and events in a centralized dashboard with accurate timestamps.
Which solution will meet these requirements with the LEAST development overhead?
- A. Use CloudFormation drift detection to identify noncompliant resources. Use drift detection events from CloudFormation to invoke an AWS Lambda function for remediation. Configure the Lambda function to publish logs to an Amazon CloudWatch Logs log group. Configure an Amazon CloudWatch dashboard to use the log group for tracking.
- B. Turn on AWS CloudTrail in the AWS accounts. Analyze CloudTrail logs by using Amazon CloudWatch Logs to identify noncompliant resources. Use CloudWatch Logs filters for drift detection. Use Amazon EventBridge to invoke the Lambda function for remediation. Stream filtered CloudWatch logs to Amazon OpenSearch Service. Set up a dashboard on OpenSearch Service for tracking.
- C. Turn on the configuration recorder in AWS Config in all the AWS accounts to identify noncompliant resources. Enable AWS Security Hub with the ~no-enable-default-standards option in all the AWS accounts. Set up AWS Config managed rules and custom rules. Set up automatic remediation by using AWS Config conformance packs. For tracking, set up a dashboard on Security Hub in a designated Security Hub administrator account.
- D. Turn on AWS CloudTrail in the AWS accounts. Analyze CloudTrail logs by using Amazon Athena to identify noncompliant resources. Use AWS Step Functions to track query results on Athena for drift detection and to invoke an AWS Lambda function for remediation. For tracking, set up an Amazon QuickSight dashboard that uses Athena as the data source.
Answer: C
NEW QUESTION # 154
A company has multiple development teams in different business units that work in a shared single AWS account All Amazon EC2 resources that are created in the account must include tags that specify who created the resources. The tagging must occur within the first hour of resource creation.
A DevOps engineer needs to add tags to the created resources that Include the user ID that created the resource and the cost center ID The DevOps engineer configures an AWS Lambda function With the cost center mappings to tag the resources. The DevOps engineer also sets up AWS CloudTrail in the AWS account. An Amazon S3 bucket stores the CloudTrail event logs Which solution will meet the tagging requirements?
- A. Enable server access logging on the S3 bucket. Create an S3 event notification on the S3 bucket for s3. ObjectTaggIng.* events
- B. Create a recurring hourly Amazon EventBridge scheduled rule that invokes the Larnbda function. Modify the Lambda function to read the logs from the S3 bucket
- C. Create an S3 event notification on the S3 bucket to invoke the Lambda function for s3.ObJectTagging:Put events. Enable bucket versioning on the S3 bucket.
- D. Create an Amazon EventBridge rule that uses Amazon EC2 as the event source. Configure the rule to match events delivered by CloudTraiI. Configure the rule to target the Lambda function
Answer: D
Explanation:
Option A is incorrect because S3 event notifications do not support s3.ObjectTagging:Put events. S3 event notifications only support events related to object creation, deletion, replication, and restore. Moreover, enabling bucket versioning on the S3 bucket is not relevant to the tagging requirements, as it only keeps multiple versions of objects in the bucket.
Option B is incorrect because enabling server access logging on the S3 bucket does not help with tagging the resources. Server access logging only records requests for access to the bucket or its objects. It does not capture the user ID or the cost center ID of the resources. Furthermore, creating an S3 event notification on the S3 bucket for s3.ObjectTagging:Put events is not possible, as explained in option A.
Option C is incorrect because creating a recurring hourly Amazon EventBridge scheduled rule that invokes the Lambda function is not efficient or timely. The Lambda function would have to read the logs from the S3 bucket every hour and tag the resources accordingly, which could incur unnecessary costs and delays. A better solution would be to trigger the Lambda function as soon as a resource is created, rather than waiting for an hourly schedule.
Option D is correct because creating an Amazon EventBridge rule that uses Amazon EC2 as the event source and matches events delivered by CloudTrail is a valid way to tag the resources. CloudTrail records all API calls made to AWS services, including EC2, and delivers them as events to EventBridge. The EventBridge rule can filter the events based on the user ID and the resource type, and then target the Lambda function to tag the resources with the cost center ID. This solution meets the tagging requirements in a timely and efficient manner.
References:
S3 event notifications
Server access logging
Amazon EventBridge rules
AWS CloudTrail
NEW QUESTION # 155
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. 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.
- B. 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.
- C. Configure tasks to write log data in the embedded metric format. Store the logs in Amazon CloudWatch Logs. Monitor the ContainerInstanceCount metric for changes.
- D. 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.
Answer: B
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 # 156
A company is using an Amazon Aurora cluster as the data store for its application. The Aurora cluster is configured with a single DB instance. The application performs read and write operations on the database by using the cluster's instance endpoint.
The company has scheduled an update to be applied to the cluster during an upcoming maintenance window. The cluster must remain available with the least possible interruption during the maintenance window.
What should a DevOps engineer do to meet these requirements?
- A. Turn on the Multi-AZ option on the Aurora cluster. Create a custom ANY endpoint for the cluster. Update the application to use the Aurora cluster's custom ANY endpoint for read and write operations.
- B. Add a reader instance to the Aurora cluster. Update the application to use the Aurora cluster endpoint for write operations. Update the Aurora cluster's reader endpoint for reads.
- C. Add a reader instance to the Aurora cluster. Create a custom ANY endpoint for the cluster. Update the application to use the Aurora cluster's custom ANY endpoint for read and write operations.
- D. Turn on the Multi-AZ option on the Aurora cluster. Update the application to use the Aurora cluster endpoint for write operations. Update the Aurora cluster's reader endpoint for reads.
Answer: D
Explanation:
To meet the requirements, the DevOps engineer should do the following:
Turn on the Multi-AZ option on the Aurora cluster.
Update the application to use the Aurora cluster endpoint for write operations.
Update the Aurora cluster's reader endpoint for reads.
Turning on the Multi-AZ option will create a replica of the database in a different Availability Zone. This will ensure that the database remains available even if one of the Availability Zones is unavailable.
Updating the application to use the Aurora cluster endpoint for write operations will ensure that all writes are sent to both the primary and replica databases. This will ensure that the data is always consistent.
Updating the Aurora cluster's reader endpoint for reads will allow the application to read data from the replica database. This will improve the performance of the application during the maintenance window.
NEW QUESTION # 157
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