VALID DOP-C02 EXAM PDF | VALID DOP-C02 EXAM PAPERS

Valid DOP-C02 Exam Pdf | Valid DOP-C02 Exam Papers

Valid DOP-C02 Exam Pdf | Valid DOP-C02 Exam Papers

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Amazon DOP-C02 or AWS Certified DevOps Engineer - Professional Exam is a certification exam offered by Amazon Web Services (AWS) for experienced DevOps professionals. DOP-C02 exam is designed to validate the candidate's technical expertise in managing, provisioning, and operating AWS environments using DevOps practices and principles. DOP-C02 exam is intended for professionals who have a minimum of two years of experience in DevOps and have experience working with AWS.

To take the DOP-C02 exam, candidates must have already obtained the AWS Certified Developer - Associate or AWS Certified SysOps Administrator - Associate certification. Additionally, candidates must have a minimum of two years of hands-on experience designing, deploying, and managing AWS applications and infrastructure at scale using DevOps principles and practices. AWS Certified DevOps Engineer - Professional certification exam is recognized by industry experts and employers as a benchmark of excellence for DevOps engineers and validates that an individual has the necessary skills and knowledge to design, manage, and maintain DevOps systems on AWS.

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Amazon AWS Certified DevOps Engineer - Professional Sample Questions (Q226-Q231):

NEW QUESTION # 226
A company recently launched multiple applications that use Application Load Balancers. Application response time often slows down when the applications experience problems A DevOps engineer needs to Implement a monitoring solution that alerts the company when the applications begin to perform slowly The DevOps engineer creates an Amazon Simple Notification Semce (Amazon SNS) topic and subscribe the company's email address to the topic What should the DevOps engineer do next to meet the requirements?

  • A. Create an Amazon CloudWatch Synthetics canary that runs a custom script to query the applications on a 5-minute interval. Configure the canary to use the SNS topic when the applications return errors.
  • B. Create an Amazon CloudWatch alarm that uses the AWS/AppljcabonELB namespace RequestCountPerTarget metric Configure the CloudWatch alarm to send a notification when the number of connections becomes greater than the configured number of threads that the application supports Configure the CloudWatch alarm to use the SNS topic.
  • C. Create an Amazon CloudWatch alarm that uses the AWS/ApplicationELB namespace RequestCountPerTarget metric Configure the CloudWatch alarm to send a notification when the average response time becomes greater than the longest response time that the application supports Configure the CloudWatch alarm to use the SNS topic
  • D. Create an Amazon EventBridge rule that invokes an AWS Lambda function to query the applications on a 5-minute interval Configure the Lambda function to publish a notification to the SNS topic when the applications return errors.

Answer: A

Explanation:
Option A is incorrect because creating an Amazon EventBridge rule that invokes an AWS Lambda function to query the applications on a 5-minute interval is not a valid solution. EventBridge rules can only trigger Lambda functions based on events, not on time intervals. Moreover, querying the applications on a 5-minute interval might incur unnecessary costs and network overhead, and might not detect performance issues in real time.
Option B is correct because creating an Amazon CloudWatch Synthetics canary that runs a custom script to query the applications on a 5-minute interval is a valid solution. CloudWatch Synthetics canaries are configurable scripts that monitor endpoints and APIs by simulating customer behavior. Canaries can run as often as once per minute, and can measure the latency and availability of the applications. Canaries can also send notifications to an Amazon SNS topic when they detect errors or performance issues1.
Option C is incorrect because creating an Amazon CloudWatch alarm that uses the AWS/ApplicationELB namespace RequestCountPerTarget metric is not a valid solution. The RequestCountPerTarget metric measures the number of requests completed or connections made per target in a target group2. This metric does not reflect the application response time, which is the requirement. Moreover, configuring the CloudWatch alarm to send a notification when the number of connections becomes greater than the configured number of threads that the application supports is not a valid way to measure the application performance, as it depends on the application design and implementation.
Option D is incorrect because creating an Amazon CloudWatch alarm that uses the AWS/ApplicationELB namespace RequestCountPerTarget metric is not a valid solution, for the same reason as option C. The RequestCountPerTarget metric does not reflect the application response time, which is the requirement. Moreover, configuring the CloudWatch alarm to send a notification when the average response time becomes greater than the longest response time that the application supports is not a valid way to measure the application performance, as it does not account for variability or outliers in the response time distribution.
References:
1: Using synthetic monitoring
2: Application Load Balancer metrics


NEW QUESTION # 227
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 tasks to write log data in the embedded metric format. Store the logs in Amazon CloudWatch Logs. Monitor the ContainerInstanceCount metric for changes.
  • B. 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.
  • C. 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.
  • 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: C

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.
Creating a CloudWatch Events Rule That Triggers on an Event - Amazon Elastic Container Service Sending and Receiving Events Between AWS Accounts - Amazon EventBridge Working with Log Data - Amazon CloudWatch Logs Analyzing Log Data with CloudWatch Logs Insights - Amazon CloudWatch Logs Embedded Metric Format - Amazon CloudWatch Amazon EC2 Auto Scaling Lifecycle Hooks - Amazon EC2 Auto Scaling


NEW QUESTION # 228
A company needs a strategy for failover and disaster recovery of its data and application. The application uses a MySQL database and Amazon EC2 instances. The company requires a maximum RPO of 2 hours and a maximum RTO of 10 minutes for its data and application at all times.
Which combination of deployment strategies will meet these requirements? (Select TWO.)

  • A. Create an Amazon Aurora global database in two AWS Regions as the data store. In the event of a failure, promote the secondary Region to the primary for the application. Update the application to use the Aurora cluster endpoint in the secondary Region.
  • B. Create an Amazon Aurora Single-AZ cluster in multiple AWS Regions as the data store. Use Aurora's automatic recovery capabilities in the event of a disaster.
  • C. Set up the application in two AWS Regions. Use Amazon Route 53 failover routing that points to Application Load Balancers in both Regions. Use health checks and Auto Scaling groups in each Region.
  • D. Create an Amazon Aurora cluster in multiple AWS Regions as the data store. Use a Network Load Balancer to balance the database traffic in different Regions.
  • E. Set up the application in two AWS Regions. Configure AWS Global Accelerator to point to Application Load Balancers (ALBs) in both Regions. Add both ALBs to a single endpoint group. Use health checks and Auto Scaling groups in each Region.

Answer: A,E

Explanation:
To meet the requirements of failover and disaster recovery, the company should use the following deployment strategies:
* Create an Amazon Aurora global database in two AWS Regions as the data store. In the event of a failure, promote the secondary Region to the primary for the application. Update the application to use the Aurora cluster endpoint in thesecondary Region.This strategy can provide a low RPO and RTO for the data, as Aurora global database replicates data with minimal latency across Regions and allows fast and easy failover12.The company can use the Amazon Aurora cluster endpoint to connect to the current primary DB cluster without needing to change any application code1.
* Set up the application in two AWS Regions. Configure AWS Global Accelerator to point to Application Load Balancers (ALBs) in both Regions. Add both ALBs to a single endpoint group. Use health checks and Auto Scaling groups in each Region.This strategy can provide high availability and performance for the application, as AWS Global Accelerator uses the AWS global network to route traffic to the closest healthy endpoint3.The company can also use static IP addresses that are assigned by Global Accelerator as a fixed entry point for their application1.By using health checks and Auto Scaling groups, the company can ensure that their application can scale up or down based on demand and handle any instance failures4.
The other options are incorrect because:
* Creating an Amazon Aurora Single-AZ cluster in multiple AWS Regions as the data store would not provide a fast failover or disaster recovery solution, as the company would need to manually restore data from backups or snapshots in another Region in case of a failure.
* Creating an Amazon Aurora cluster in multiple AWS Regions as the data store and using a Network Load Balancer to balance the database traffic in different Regions would not work, as Network Load Balancers do not support cross-Region routing. Moreover, this strategy would not provide a consistent view of the data across Regions, as Aurora clusters do not replicate data automatically between Regions unless they are part of a global database.
* Setting up the application in two AWS Regions and using Amazon Route 53 failover routing that points to Application Load Balancers in both Regions would not provide a low RTO, as Route 53 failover routing relies on DNS resolution, which can take time to propagate changes across different DNS servers and clients. Moreover, this strategy would not provide deterministic routing, as Route 53 failover routing depends on DNS caching behavior, which can vary depending on different factors.


NEW QUESTION # 229
A company runs a workload on Amazon EC2 instances. The company needs a control that requires the use of Instance Metadata Service Version 2 (IMDSv2) on all EC2 instances in the AWS account. If an EC2 instance does not prevent the use of Instance Metadata Service Version 1 (IMDSv1), the EC2 instance must be terminated.
Which solution will meet these requirements?

  • A. Create a permissions boundary that prevents the ec2:Runlnstance action if the ec2:MetadataHttpTokens condition key is not set to a value of required. Attach the permissions boundary to the IAM role that was used to launch the instance.
  • B. Set up AWS Config in the account. Use a managed rule to check EC2 instances. Configure the rule to remediate the findings by using AWS Systems Manager Automation to terminate the instance.
  • C. Create an Amazon EventBridge rule for the EC2 instance launch successful event. Send the event to an AWS Lambda function to inspect the EC2 metadata and to terminate the instance.
  • D. Set up Amazon Inspector in the account. Configure Amazon Inspector to activate deep inspection for EC2 instances. Create an Amazon EventBridge rule for an Inspector2 finding. Set an AWS Lambda function as the target to terminate the instance.

Answer: A

Explanation:
Explanation
To implement a control that requires the use of IMDSv2 on all EC2 instances in the account, the DevOps engineer can use a permissions boundary. A permissions boundary is a policy that defines the maximum permissions that an IAM entity can have. The DevOps engineer can create a permissions boundary that prevents the ec2:RunInstance action if the ec2:MetadataHttpTokens condition key is not set to a value of required. This condition key enforces the use of IMDSv2 on EC2 instances. The DevOps engineer can attach the permissions boundary to the IAM role that was used to launch the instance. This way, any attempt to launch an EC2 instance without using IMDSv2 will be denied by the permissions boundary.


NEW QUESTION # 230
A DevOps engineer used an AWS CloudFormation custom resource to set up AD Connector. The AWS Lambda function ran and created AD Connector, but CloudFormation is not transitioning from CREATE_IN_PROGRESS to CREATE_COMPLETE. Which action should the engineer take to resolve this issue?

  • A. Ensure the Lambda function IAM role has cloudformation:UpdateStack permissions for the stack ARN.
  • B. Ensure the Lambda function code has exited successfully.
  • C. Ensure the Lambda function code returns a response to the pre-signed URL.
  • D. Ensure the Lambda function IAM role has ds:ConnectDirectory permissions for the AWS account.

Answer: C


NEW QUESTION # 231
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