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Amazon DOP-C01 exam is a 180-minute exam consisting of 75 multiple-choice and multiple-response questions. AWS-DevOps exam is available in English, Japanese, Korean, and Simplified Chinese. AWS-DevOps Exam Fee is $300, and it can be taken at a testing center or online through Pearson VUE.

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Amazon AWS Certified DevOps Engineer - Professional Sample Questions (Q38-Q43):

NEW QUESTION # 38
Am Amazon EC2 instance with no internet access is running in a Virtual Private Cloud (VPC) and needs to download an object from a restricted Amazon S3 bucket. When the DevOps Engineer tries to gain access to the object, an Access Denied error is received. What are the possible causes for this error? (Select THREE.)

A. There is an error in the VPC endpoint policy.
B. The S3 bucket default encryption is enabled.
C. There is an error in the IAM role configuration.
D. The object has been moved to Amazon Glacier.
E. S3 versioning is enabled.
F. There is an error in the S3 bucket policy.

Answer: A,C,F

NEW QUESTION # 39
If you're trying to configure an AWS Elastic Beanstalk worker tier for easy debugging if there are problems
finishing queue jobs, what should you configure?

A. ConfigureRolling Deployments.
B. ConfigureEnhanced Health Reporting.
C. ConfigureBlue-Green Deployments.
D. Configure a Dead Letter Queue.

Answer: D

Explanation:
Explanation
The AWS documentation mentions the following on dead-letter queues
Amazon SQS supports dead-letter queues. A dead-letter queue is a queue that other (source) queues can target
for messages that can't be processed (consumed)
successfully. You can set aside and isolate these messages in the dead-letter queue to determine why their
processing doesn't succeed.
For more information on dead letter queues please visit the below link
http://docs.aws.amazon.com/AWSSimpleQueueService/latest/SQSDeveloperGuide/sqs-dead-letter-queues.
html

NEW QUESTION # 40
You work for a company that automatically tags photographs using artificial neural networks (ANNs), which run on GPUs using C++. You receive millions of images at a time, but only 3 times per day on average. These images are loaded into an AWS S3 bucket you control for you in a batch, and then the customer publishes a JSON-formatted manifest into another S3 bucket you control as well. Each image takes 10 milliseconds to process using a full GPU. Your neural network software requires 5 minutes to bootstrap. Image tags are JSON objects, and you must publish them to an S3 bucket. Which of these is the best system architectures for this system?

A. Deploy your artificial neural network code to AWS Lambda as a bundled binary for the C++ extension.
Make an S3 notification configuration on the manifest, which publishes to another AWS Lambda running controller code. This controller code publishes all the images in the manifest to AWS Kinesis.
Your ANN code Lambda Function uses the Kinesis as an Event Source. The system automatically scales when the stream contains image events.
B. Make an S3 notification configuration which publishes to AWS Lambda on the manifest bucket. Make the Lambda create a CloudFormation Stack which contains the logic to construct an autoscaling worker tier of EC2 G2 instances with the artificial neural network code on each instance. Create an SQS queue of the images in the manifest. Tear the stack down when the queue is empty.
C. Create an Auto Scaling Load Balanced Elastic Beanstalk worker tier Application and Environment.
Deploy the artificial neural network code to G2 instances in this tier. Set the desired capacity to 1. Make the code periodically check S3 for new manifests. When a new manifest is detected, push all of the images in the manifest into the SQS queue associated with the Elastic Beanstalk worker tier.
D. Create an OpsWorks Stack with two Layers. The first contains lifecycle scripts for launching and bootstrapping an HTTP API on G2 instances for image processing, and the second has an always-on instance which monitors the S3 manifest bucket for new files. When a new file is detected, request instances to boot on the artificial neural network layer. When the instances are booted and the HTTP APIs are up, submit processing requests to individual instances.

Answer: B

Explanation:
Explanation
The best way to get notified when the images get sent to the bucket is the S3 Events. Here you don't need to provision infrastructure beforehand, and also since the source of S3 provides Event Handling, this should be used.
The AWS Documentation mentions the following on AWS S3 and Lambda
Amazon S3 can publish events (for example, when an object is created in a bucket) to AWS Lambda and invoke your Lambda function by passing the event data as a parameter. This integration enables you to write Lambda functions that process Amazon S3 events. In Amazon S3, you add bucket notification configuration that identifies the type of event that you want Amazon S3 to publish and the Lambda function that you want to invoke.
For more information on AWS Lambda and S3 Events, please visit the link:
* http://docs.aws.amazon.com/lambda/latest/dg/with-s3,html

NEW QUESTION # 41
For auditing, analytics, and troubleshooting purposes, a DevOps Engineer for a data analytics application needs to collect all of the application and Linux system logs from the Amazon EC2 instances before termination. The company, on average, runs 10,000 instances in an Auto Scaling group. The company requires the ability to quickly find logs based on instance IDs and date ranges.
Which is the MOST cost-effective solution?

A. Create an EC2 Instance-terminate Lifecycle Action on the group, create an Amazon CloudWatch Events rule based on it to trigger an AWS Lambda function for storing the logs in Amazon S3, and create a catalog of log files in an Amazon DynamoDB table with the primary key being Instance ID and sort key being Instance Termination Date.
B. Create an EC2 Instance-terminate Lifecycle Actionon the group, push the logs into Amazon Kinesis Data Firehose, and select Amazon ES as the destination for providing storage and search capability.
C. Create an EC2 Instance-terminate Lifecycle Actionon the group, write a termination script for pushing logs into Amazon S3, and trigger an AWS Lambda function based on S3 PUT to create a catalog of log files in an Amazon DynamoDB table with the primary key being Instance ID and sort key being Instance Termination Date.
D. Create an EC2 Instance-terminate Lifecycle Actionon the group, write a termination script for pushing logs into Amazon CloudWatch Logs, create a CloudWatch Events rule to trigger an AWS Lambda function to create a catalog of log files in an Amazon DynamoDB table with the primary key being Instance ID and sort key being Instance Termination Date.

Answer: B

Explanation:
Explanation/Reference:

NEW QUESTION # 42
A company is using AWS CodeDeploy to automate software deployment. The deployment must meet these requirements:
- A number of instances must be available to serve traffic during the
deployment. Traffic must be balanced across those instances, and the
instances must automatically heal in the event of failure.
- A new fleet of instances must be launched for deploying a new
revision automatically, with no manual provisioning.
- Traffic must be rerouted to the new environment to half of the new
instances at a time. The deployment should succeed if traffic is
rerouted to at least half of the instances; otherwise, it should fail.
- Before routing traffic to the new fleet of instances, the temporary
files generated during the deployment process must be deleted.
- At the end of a successful deployment, the original instances in the
deployment group must be deleted immediately to reduce costs.
How can a DevOps Engineer meet these requirements?

A. Use an Application Load Balancer and a blue/green deployment. Associate the Auto Scaling group and the Application Load Balancer target group with the deployment group. Use the Automatically option, create a custom deployment configuration with minimum copy Auto Scaling group healthy hosts defined as 50%, and assign the configuration to the deployment group. Instruct AWS CodeDeploy to terminate the original instances in the deployment group, and use the BeforeBlock Traffic hook within appsec.yml to delete the temporary files.
B. Use an Application Load Balancer and a blue/green deployment. Associate the Auto Scaling group and the Application Load Balancer target group with the deployment group. Use the Automatically option, and use CodeDeployDefault HalfAtAtime as the deployment copy Auto Scaling group configuration. Instruct AWS CodeDeploy to terminate the original isntances in the deployment group, and use the BeforeAllowTraffic hook within appspec.yml to delete the temporary files.
C. Use an Application Load Balancer and an in-place deployment. Associate the Auto Scaling group with the deployment group. Use the Automatically copy Auto Scaling group option, and use CodeDeployDefault.OneAtAtime as the deployment configuration. Instruct AWS CodeDeploy to terminate the original instances in the deployment group, and use the AllowTraffic hook within appspec.yml to delete the temporary files.
D. Use an Application Load Balancer and an in-place deployment. Associate the Auto Scaling group and Application Load Balancer target group with the deployment group. Use the Automatically copy option, and use CodeDeployDefault AllatOnce as a deployment configuration.
Auto Scaling group
Instruct AWS CodeDeploy to terminate the original instances in the deployment group, and use the BlockTraffic hook within appsec.yml to delete the temporary files.

Answer: C

NEW QUESTION # 43
......

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