NEW AMAZON DOP-C02 BRAINDUMPS EBOOK & DOP-C02 UPDATED DEMO

New Amazon DOP-C02 Braindumps Ebook & DOP-C02 Updated Demo

New Amazon DOP-C02 Braindumps Ebook & DOP-C02 Updated Demo

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Amazon AWS Certified DevOps Engineer - Professional Sample Questions (Q156-Q161):

NEW QUESTION # 156
A company is storing 100 GB of log data in csv format in an Amazon S3 bucket SQL developers want to query this data and generate graphs to visualize it. The SQL developers also need an efficient automated way to store metadata from the csv file.
Which combination of steps will meet these requirements with the LEAST amount of effort? (Select THREE.)

  • A. Fitter the data through AWS X-Ray to visualize the data.
  • B. Filter the data through Amazon QuickSight to visualize the data.
  • C. Query the data with Amazon Redshift.
  • D. Use the AWS Glue Data Catalog as the persistent metadata store.
  • E. Use Amazon DynamoDB as the persistent metadata store.
  • F. Query the data with Amazon Athena.

Answer: B,D,F

Explanation:
https://docs.aws.amazon.com/glue/latest/dg/components-overview.html


NEW QUESTION # 157
A company has a mission-critical application on AWS that uses automatic scaling The company wants the deployment lilecycle to meet the following parameters.
* The application must be deployed one instance at a time to ensure the remaining fleet continues to serve traffic
* The application is CPU intensive and must be closely monitored
* The deployment must automatically roll back if the CPU utilization of the deployment instance exceeds 85%.
Which solution will meet these requirements?

  • A. Use AWS CloudFormalion to create an AWS Step Functions state machine and Auto Scaling hfecycle hooks to move to one instance at a time into a wait state Use AWS Systems Manager automation to deploy the update to each instance and move it back into the Auto Scaling group using the heartbeat timeout
  • B. Use AWS Systems Manager to perform a blue/green deployment with Amazon EC2 Auto Scaling Configure an alarm tied to the CPU utilization metric Deploy updates one at a time Configure automatic rollbacks within the Auto Scaling group to roll back the deployment if the alarm thresholds are breached
  • C. Use AWS CodeDeploy with Amazon EC2 Auto Scaling. Configure an alarm tied to the CPU utilization metric. Use the CodeDeployDefault OneAtAtime configuration as a deployment strategy Configure automatic rollbacks within the deployment group to roll back the deployment if the alarm thresholds are breached
  • D. Use AWS Elastic Beanstalk for load balancing and AWS Auto Scaling Configure an alarm tied to the CPU utilization metric Configure rolling deployments with a fixed batch size of one instance Enable enhanced health to monitor the status of the deployment and roll back based on the alarm previously created.

Answer: C

Explanation:
https://aws.amazon.com/about-aws/whats-new/2016/09/aws-codedeploy-introduces-deployment-monitoring-with-amazon-cloudwatch-alarms-and-automatic-deployment-rollback/


NEW QUESTION # 158
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?

  • A. Increase the memory of the Lambda function to give the function the ability to process large files from the S3 bucket.
  • B. Configure an Amazon Simple Queue Service (Amazon SQS) queue as an OnFailure destination for the Lambda function
  • C. Create a resource policy on the Lambda function to grant Amazon S3 the permission to invoke the Lambda function for the S3 bucket
  • D. Provision space in the /tmp folder of the Lambda function to give the function the ability to process large files from the S3 bucket

Answer: C

Explanation:
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]


NEW QUESTION # 159
A DevOps team is merging code revisions for an application that uses an Amazon RDS Multi-AZ DB cluster for its production database. The DevOps team uses continuous integration to periodically verify that the application works. The DevOps team needs to test the changes before the changes are deployed to the production database.
Which solution will meet these requirements'?

  • A. Use a buildspec file in AWS CodeBuild to restore the DB cluster from a snapshot of the production database run integration tests, and drop the restored database after verification.
  • B. Ensure that the DB cluster is a Multi-AZ deployment. Deploy the application with the updates. Fail over to the standby instance if verification fails.
  • C. Deploy the application to production. Configure an audit log of data control language (DCL) operations to capture database activities to perform if verification fails.
  • D. Create a snapshot of the DB duster before deploying the application Use the Update requires Replacement property on the DB instance in AWS CloudFormation to deploy the application and apply the changes.

Answer: A

Explanation:
Explanation
This solution will meet the requirements because it will create a temporary copy of the production database using a snapshot, run the integration tests on the copy, and delete the copy after the tests are done. This way, the production database will not be affected by the code revisions, and the DevOps team can test the changes before deploying them to production. A buildspec file is a YAML file that contains the commands and settings that CodeBuild uses to run a build1. The buildspec file can specify the steps to restore the DB cluster from a snapshot, run the integration tests, and drop the restored database2


NEW QUESTION # 160
A company has a legacy application A DevOps engineer needs to automate the process of building the deployable artifact for the legacy application. The solution must store the deployable artifact in an existing Amazon S3 bucket for future deployments to reference Which solution will meet these requirements in the MOST operationally efficient way?

  • A. Create a custom Docker image that contains all the dependencies tor the legacy application Store the custom Docker image in a new Amazon Elastic Container Registry (Amazon ECR) repository Configure a new AWS CodeBuild project to use the custom Docker image to build the deployable artifact and to save the artifact to the S3 bucket.
  • B. Create a custom EC2 Image Builder image Install all the dependencies for the legacy application on the image Launch a new Amazon EC2 instance from the image Use the new EC2 instance to build the deployable artifact and to save the artifact to the S3 bucket.
  • C. Create an Amazon Elastic Kubernetes Service (Amazon EKS) cluster with an AWS Fargate profile that runs in multiple Availability Zones Create a custom Docker image that contains all the dependencies for the legacy application Store the custom Docker image in a new Amazon Elastic Container Registry (Amazon ECR) repository Use the custom Docker image inside the EKS cluster to build the deployable artifact and to save the artifact to the S3 bucket.
  • D. Launch a new Amazon EC2 instance Install all the dependencies (or the legacy application on the EC2 instance Use the EC2 instance to build the deployable artifact and to save the artifact to the S3 bucket.

Answer: A

Explanation:
Explanation
This approach is the most operationally efficient because it leverages the benefits of containerization, such as isolation and reproducibility, as well as AWS managed services. AWS CodeBuild is a fully managed build service that can compile your source code, run tests, and produce deployable software packages. By using a custom Docker image that includes all dependencies, you can ensure that the environment in which your code is built is consistent. Using Amazon ECR to store Docker images lets you easily deploy the images to any environment. Also, you can directly upload the build artifacts to Amazon S3 from AWS CodeBuild, which is beneficial for version control and archival purposes.


NEW QUESTION # 161
......

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