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Amazon DOP-C02 (AWS Certified DevOps Engineer - Professional) certification exam is designed for individuals who possess a deep understanding of various DevOps practices and how to implement them on the AWS platform. AWS Certified DevOps Engineer - Professional certification validates the ability of an individual to design, deploy, operate, and manage highly available, scalable, and fault-tolerant systems on AWS.

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Amazon DOP-C02 exam consists of multiple-choice and multiple-response questions that assess the candidate's ability to design, deploy, and manage highly available, fault-tolerant, and scalable systems on the AWS platform. DOP-C02 exam is timed, and candidates have 180 minutes to complete it. To pass the exam, candidates must achieve a minimum score of 750 out of 1000.

Amazon DOP-C02 exam is designed for IT professionals who want to validate their skills and knowledge in developing and deploying applications on the Amazon Web Services (AWS) platform. AWS Certified DevOps Engineer - Professional certification is intended for individuals who have experience working with AWS technologies and services, and who are proficient in DevOps practices and principles. The DOP-C02 Exam is the updated version of the AWS Certified DevOps Engineer - Professional certification, which was first introduced in 2018.

Amazon AWS Certified DevOps Engineer - Professional Sample Questions (Q12-Q17):

NEW QUESTION # 12
A company runs an application on one Amazon EC2 instance. Application metadata is stored in Amazon S3 and must be retrieved if the instance is restarted. The instance must restart or relaunch automatically if the instance becomes unresponsive.
Which solution will meet these requirements?

A. Configure AWS OpsWorks, and use the auto healing feature to stop and start the instance. Use a lifecycle event in OpsWorks to pull the metadata from Amazon S3 and update it on the instance.
B. Create an Amazon CloudWatch alarm for the StatusCheckFailed metric. Use the recover action to stop and start the instance. Use an S3 event notification to push the metadata to the instance when the instance is back up and running.
C. Use EC2 Auto Recovery to automatically stop and start the instance in case of a failure. Use an S3 event notification to push the metadata to the instance when the instance is back up and running.
D. Use AWS CloudFormation to create an EC2 instance that includes the UserData property for the EC2 resource. Add a command in UserData to retrieve the application metadata from Amazon S3.

Answer: A

Explanation:
https://aws.amazon.com/blogs/mt/how-to-set-up-aws-opsworks-stacks-auto-healing-notifications-in-amazon-cloudwatch-events/

NEW QUESTION # 13
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 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.
B. 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.
C. 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.
D. 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

Answer: C

Explanation:
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 # 14
A company releases a new application in a new AWS account. The application includes an AWS Lambda function that processes messages from an Amazon Simple Queue Service (Amazon SOS) standard queue. The Lambda function stores the results in an Amazon S3 bucket for further downstream processing. The Lambda function needs to process the messages within a specific period of time after the messages are published. The Lambda function has a batch size of 10 messages and takes a few seconds to process a batch of messages.
As load increases on the application's first day of service, messages in the queue accumulate at a greater rate than the Lambda function can process the messages. Some messages miss the required processing timelines. The logs show that many messages in the queue have data that is not valid. The company needs to meet the timeline requirements for messages that have valid data.
Which solution will meet these requirements?

A. Reduce the Lambda function's batch size. Increase the SOS message throughput quota. Request a Lambda concurrency increase in the AWS Region.
B. Increase the Lambda function's batch size. Change the SOS standard queue to an SOS FIFO queue. Request a Lambda concurrency increase in the AWS Region.
C. Keep the Lambda function's batch size the same. Configure the Lambda function to report failed batch items. Configure an SOS dead-letter queue.
D. Increase the Lambda function's batch size. Configure S3 Transfer Acceleration on the S3 bucket. Configure an SOS dead-letter queue.

Answer: C

Explanation:
Step 1: Handling Invalid Data with Failed Batch Items
The Lambda function is processing batches of messages, and some messages contain invalid data, causing processing delays. Lambda provides the capability to report failed batch items, which allows valid messages to be processed while skipping invalid ones. This functionality ensures that the valid messages are processed within the required timeline.
Action: Keep the Lambda function's batch size the same and configure it to report failed batch items.
Why: By reporting failed batch items, the Lambda function can skip invalid messages and continue processing valid ones, ensuring that they meet the processing timeline.
Reference:
Step 2: Using an SQS Dead-Letter Queue (DLQ)
Configuring a dead-letter queue (DLQ) for SQS will ensure that messages with invalid data, or those that cannot be processed successfully, are moved to the DLQ. This prevents such messages from clogging the queue and allows the system to focus on processing valid messages.
Action: Configure an SQS dead-letter queue for the main queue.
Why: A DLQ helps isolate problematic messages, preventing them from continuously reappearing in the queue and causing processing delays for valid messages.
Step 3: Maintaining the Lambda Function's Batch Size
Keeping the current batch size allows the Lambda function to continue processing multiple messages at once. By addressing the failed items separately, there's no need to increase or reduce the batch size.
Action: Maintain the Lambda function's current batch size.
Why: Changing the batch size is unnecessary if the invalid messages are properly handled by reporting failed items and using a DLQ.
This corresponds to Option D: Keep the Lambda function's batch size the same. Configure the Lambda function to report failed batch items. Configure an SQS dead-letter queue.

NEW QUESTION # 15
A company's application uses a fleet of Amazon EC2 On-Demand Instances to analyze and process dat a. The EC2 instances are in an Auto Scaling group. The Auto Scaling group is a target group for an Application Load Balancer (ALB). The application analyzes critical data that cannot tolerate interruption. The application also analyzes noncritical data that can withstand interruption.
The critical data analysis requires quick scalability in response to real-time application demand. The noncritical data analysis involves memory consumption. A DevOps engineer must implement a solution that reduces scale-out latency for the critical data. The solution also must process the noncritical data.
Which combination of steps will meet these requirements? (Select TWO.)

A. For the critical data, modify the existing Auto Scaling group. Create a warm pool instance in the stopped state. Define the warm pool size. Create a new
B. For the critical data. modify the existing Auto Scaling group. Create a lifecycle hook to ensure that bootstrap scripts are completed successfully. Ensure that the application on the instances is ready to accept traffic before the instances are registered. Create a new version of the launch template that has detailed monitoring enabled.
C. For the noncritical data, create a second Auto Scaling group that uses a launch template. Configure the launch template to install the unified Amazon CloudWatch agent and to configure the CloudWatch agent with a custom memory utilization metric. Use Spot Instances. Add the new Auto Scaling group as the target group for the ALB. Modify the application to use two target groups for critical data and noncritical data.
D. For the critical data, modify the existing Auto Scaling group. Create a warm pool instance in the stopped state. Define the warm pool size. Create a new
E. For the noncritical data, create a second Auto Scaling group. Choose the predefined memory utilization metric type for the target tracking scaling policy. Use Spot Instances. Add the new Auto Scaling group as the target group for the ALB. Modify the application to use two target groups for critical data and noncritical data.

Answer: C,D

Explanation:
For the critical data, using a warm pool1 can reduce the scale-out latency by having pre-initialized EC2 instances ready to serve the application traffic. Using On-Demand Instances can ensure that the instances are always available and not interrupted by Spot interruptions2.
For the noncritical data, using a second Auto Scaling group with Spot Instances can reduce the cost and leverage the unused capacity of EC23. Using a launch template with the CloudWatch agent4 can enable the collection of memory utilization metrics, which can be used to scale the group based on the memory demand. Adding the second group as a target group for the ALB and modifying the application to use two target groups can enable routing the traffic based on the data type.

NEW QUESTION # 16
A company's DevOps engineer is working in a multi-account environment. The company uses AWS Transit Gateway to route all outbound traffic through a network operations account. In the network operations account all account traffic passes through a firewall appliance for inspection before the traffic goes to an internet gateway.
The firewall appliance sends logs to Amazon CloudWatch Logs and includes event seventies of CRITICAL, HIGH, MEDIUM, LOW, and INFO. The security team wants to receive an alert if any CRITICAL events occur.
What should the DevOps engineer do to meet these requirements?

A. Create an Amazon CloudWatch metric filter by using a search for CRITICAL events Publish a custom metric for the finding. Use a CloudWatch alarm based on the custom metric to publish a notification to an Amazon Simple Notification Service (Amazon SNS) topic. Subscribe the security team's email address to the topic.
B. Use AWS Firewall Manager to apply consistent policies across all accounts. Create an Amazon.EventBridge event rule that is invoked by Firewall Manager events that are CRITICAL Define an Amazon Simple Notification Service (Amazon SNS) topic as a target Subscribe the security team's email address to the topic.
C. Enable Amazon GuardDuty in the network operations account. Configure GuardDuty to monitor flow logs Create an Amazon EventBridge event rule that is invoked by GuardDuty events that are CRITICAL Define an Amazon Simple Notification Service (Amazon SNS) topic as a target Subscribe the security team's email address to the topic.
D. Create an Amazon CloudWatch Synthetics canary to monitor the firewall state. If the firewall reaches a CRITICAL state or logs a CRITICAL event use a CloudWatch alarm to publish a notification to an Amazon Simple Notification Service (Amazon SNS) topic Subscribe the security team's email address to the topic.

Answer: A

Explanation:
Explanation
"The firewall appliance sends logs to Amazon CloudWatch Logs and includes event severities of CRITICAL, HIGH, MEDIUM, LOW, and INFO"

NEW QUESTION # 17
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Zachary Howard Zachary Howard

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