Amazon Web Services passguide aws Certified Professional Dop-c02 Passing Score by Ari q60 vce pdf

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Exam Name:	AWS Certified DevOps Engineer - Professional
Exam Code:	DOP-C02 Dumps
Vendor:	Amazon Web Services	Certification:	AWS Certified Professional
Questions:	425 Q&A's	Shared By:	ari

Question 84

A company is performing vulnerability scanning for all Amazon EC2 instances across many accounts. The accounts are in an organization in AWS Organizations. Each account ' s VPCs are attached to a shared transit gateway. The VPCs send traffic to the internet through a central egress VPC. The company has enabled Amazon Inspector in a delegated administrator account and has enabled scanning for all member accounts.

A DevOps engineer discovers that some EC2 instances are listed in the " not scanning " tab in Amazon Inspector.

Which combination of actions should the DevOps engineer take to resolve this issue? (Choose three.)

Options:

Verify that AWS Systems Manager Agent is installed and is running on the EC2 instances that Amazon Inspector is not scanning.

Associate the target EC2 instances with security groups that allow outbound communication on port 443 to the AWS Systems Manager service endpoint.

Grant inspector: StartAssessmentRun permissions to the IAM role that the DevOps engineer is using.

Configure EC2 Instance Connect for the EC2 instances that Amazon Inspector is not scanning.

Associate the target EC2 instances with instance profiles that grant permissions to communicate with AWS Systems Manager.

Create a managed-instance activation. Use the Activation Code and the Activation ID to register the EC2 instances.

Discussion

Question 85

A company has configured an Amazon S3 event source on an AWS Lambda function The company needs the Lambda function to run when a new object is created or an existing object IS modified In a particular S3 bucket The Lambda function will use the S3 bucket name and the S3 object key of the incoming event to read the contents of the created or modified S3 object The Lambda function will parse the contents and save the parsed contents to an Amazon DynamoDB table.

The Lambda function ' s execution role has permissions to read from the S3 bucket and to write to the DynamoDB table, During testing, a DevOps engineer discovers that the Lambda

function does not run when objects are added to the S3 bucket or when existing objects are modified.

Which solution will resolve this problem?

Options:

Increase the memory of the Lambda function to give the function the ability to process large files from the S3 bucket.

Create a resource policy on the Lambda function to grant Amazon S3 the permission to invoke the Lambda function for the S3 bucket

Configure an Amazon Simple Queue Service (Amazon SQS) queue as an OnFailure destination for the Lambda function

Provision space in the /tmp folder of the Lambda function to give the function the ability to process large files from the S3 bucket

Discussion

Answer:

Explanation:

Option A is incorrect because increasing the memory of the Lambda function does not address the root cause of the problem, which is that the Lambda function is not triggered by the S3 event source. Increasing the memory of the Lambda function might improve its performance or reduce its execution time, but it does not affect its invocation. Moreover, increasing the memory of the Lambda function might incur higher costs, as Lambda charges based on the amount of memory allocated to the function.

Option B is correct because creating a resource policy on the Lambda function to grant Amazon S3 the permission to invoke the Lambda function for the S3 bucket is a necessary step to configure an S3 event source. A resource policy is a JSON document that defines who can access a Lambda resource and under what conditions. By granting Amazon S3 permission to invoke the Lambda function, the company ensures that the Lambda function runs when a new object is created or an existing object is modified in the S3 bucket1.

Option C is incorrect because configuring an Amazon Simple Queue Service (Amazon SQS) queue as an On-Failure destination for the Lambda function does not help with triggering the Lambda function. An On-Failure destination is a feature that allows Lambda to send events to another service, such as SQS or Amazon Simple Notification Service (Amazon SNS), when a function invocation fails. However, this feature only applies to asynchronous invocations, and S3 event sources use synchronous invocations. Therefore, configuring an SQS queue as an On-Failure destination would have no effect on the problem.

Option D is incorrect because provisioning space in the /tmp folder of the Lambda function does not address the root cause of the problem, which is that the Lambda function is not triggered by the S3 event source. Provisioning space in the /tmp folder of the Lambda function might help with processing large files from the S3 bucket, as it provides temporary storage for up to 512 MB of data. However, it does not affect the invocation of the Lambda function.

[References:, Using AWS Lambda with Amazon S3, Lambda resource access permissions, AWS Lambda destinations, [AWS Lambda file system], , , ]

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Question 86

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?

Options:

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.

Reduce the Lambda function ' s batch size. Increase the SOS message throughput quota. Request a Lambda concurrency increase in the AWS Region.

Increase the Lambda function ' s batch size. Configure S3 Transfer Acceleration on the S3 bucket. Configure an SOS dead-letter queue.

Keep the Lambda function ' s batch size the same. Configure the Lambda function to report failed batch items. Configure an SOS dead-letter queue.

Discussion

Answer:

Explanation:

Step 1: Handling Invalid Data with Failed Batch ItemsThe 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: AWS documentation on Lambda batch item failure handling., 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., Reference: AWS documentation on Amazon SQS Dead-Letter Queues., Step 3: Maintaining the Lambda Function’s Batch SizeKeeping 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., , , , ]

Question 87

A DevOps engineer notices that all Amazon EC2 instances running behind an Application Load Balancer in an Auto Scaling group are failing to respond to user requests. The EC2 instances are also failing target group HTTP health checks

Upon inspection, the engineer notices the application process was not running in any EC2 instances. There are a significant number of out of memory messages in the system logs. The engineer needs to improve the resilience of the application to cope with a potential application memory leak. Monitoring and notifications should be enabled to alert when there is an issue

Which combination of actions will meet these requirements? (Select TWO.)

Options:

Change the Auto Scaling configuration to replace the instances when they fail the load balancer ' s health checks.

Change the target group health check HealthChecklntervalSeconds parameter to reduce the interval between health checks.

Change the target group health checks from HTTP to TCP to check if the port where the application is listening is reachable.

Enable the available memory consumption metric within the Amazon CloudWatch dashboard for the entire Auto Scaling group Create an alarm when the memory utilization is high Associate an Amazon SNS topic to the alarm to receive notifications when the alarm goes off

Use the Amazon CloudWatch agent to collect the memory utilization of the EC2 instances in the Auto Scaling group Create an alarm when the memory utilization is high and associate an Amazon SNS topic to receive a notification.