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DOP-C02 Questions and Answers

Question # 1

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?

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.

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 onLambda 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 onAmazon 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 toOption 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 # 2

A DevOps engineer is working on a project that is hosted on Amazon Linux and has failed a security review. The DevOps manager has been asked to review the company buildspec. yaml die for an AWS CodeBuild project and provide recommendations. The buildspec. yaml file is configured as follows:

Whatchanges should be recommended to comply with AWS security best practices? (Select THREE.)

Add a post-build command to remove the temporary files from the container before termination to ensure they cannot be seen by other CodeBuild users.

Update the CodeBuild project role with the necessary permissions and then remove the AWS credentials from the environment variable.

Store thedb_passwordas a SecureString value in AWS Systems Manager Parameter Store and then remove thedb_passwordfrom the environment variables.

Move the environment variables to the 'db.-deploy-bucket ‘Amazon S3 bucket, add a prebuild stage to download then export the variables.

Use AWS Systems Manager run command versus sec and ssh commands directly to the instance.

Question # 3

A company manages an application that stores logs in Amazon CloudWatch Logs. The company wants to archive the logs to an Amazon S3 bucket Logs are rarely accessed after 90 days and must be retained tor 10 years.

Which combination of steps should a DevOps engineer take to meet these requirements? (Select TWO.)

Configure a CloudWatch Logs subscription filter to use AWS Glue to transfer all logs to an S3 bucket.

Configure a CloudWatch Logs subscription filter to use Amazon Kinesis Data Firehose to stream all logs to an S3 bucket.

Configure a CloudWatch Logs subscription fitter to stream all logs to an S3 bucket.

Configure the S3 bucket lifecycle policy to transition logs to S3 Glacier after 90 days and to expire logs after 3.650 days.

Configure the S3 bucket lifecycle policy to transition logs to Reduced Redundancy after 90 days and to expire logs after 3.650 days.

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