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AWS DevOps Engineer Professional Exam formate below
Format: Multiple choices, multiple answers
- Language: English
- Passing score: 750
- Length of Examination: 180 minutes
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Policies and Standards Automation (10%)
- Determining how to optimize the cost through automation;
- Applying the concepts required to implement the governance strategies;
- Applying the concepts that are required to implement standards for logging, security, testing, monitoring & metrics.
Amazon AWS Certified DevOps Engineer - Professional (DOP-C01) Sample Questions (Q266-Q271):
NEW QUESTION # 266
You have written a server-side Node.Js application and a web application with an HTML/JavaScript front end that uses the Angular.js framework.
The server-side application connects to an Amazon Redshift cluster, issues queries, and then returns the results to the front end for display.
Your user base is very large and distributed, but it is important to keep the cost of running this application low.
Which deployment strategy is both technically valid and the most cost-effective?
- A. Upload the HTML, CSS, images, and JavaScript for the front end to an Amazon S3 bucket.
Use AWS Elastic Beanstalk to deploy the Node.js application.
Launch an Amazon Redshift cluster, and point your application to its JDBC endpoint. - B. Upload the HTML, CSS, images, and JavaScript for the front end, plus the Node.js code for the server-side application, to an Amazon S3 bucket.
Create a CloudFront distribution with this bucket as its origin.
Launch an Amazon Redshift cluster, and point your application to its JDBC endpoint. - C. Upload the HTML, CSS, images, and JavaScript for the front end to an Amazon Simple Storage Service (S3) bucket.
Create an Amazon CloudFront distribution with this bucket as its origin. Use AWS Elastic Beanstalk to deploy the Node.js application.
Launch an Amazon Redshift cluster, and point your application to its JDBC endpoint. - D. Deploy an AWS OpsWorks stack with three layers: a static web server layer for your front end, a Node.js app server layer for your server-side application, and a Redshift DB layer for your Amazon Redshift duster.
- E. Deploy an AWS Elastic Beanstalk application with two environments: one for the Node.js application and another for the web front end.
Launch an Amazon Redshift cluster, and point your application to its Java Database Connectivity (JDBC) endpoint.
Answer: C
NEW QUESTION # 267
A Solutions Architect is about to deploy an API on multiple EC2 instances in an Auto Scaling group behind an
ELB. The support team has the following operational requirements:
1 They get an alert when the requests per second go over 50,000
2 They get an alert when latency goes over 5 seconds
3 They can validate how many times a day users call the API requesting highly-sensitive data
Which combination of steps does the Architect need to take to satisfy these operational requirements? (Select
two.)
- A. Ensure that detailed monitoring for the EC2 instances is enabled.
- B. Ensure that CloudTrail is enabled.
- C. Create an application to export and save CloudWatch metrics for longer term trending analysis.
- D. Create a custom CloudWatch metric to monitor the API for data access.
- E. Configure CloudWatch alarms for any metrics the support team requires.
Answer: A,D
NEW QUESTION # 268
Your social media marketing application has a component written in Ruby running on AWS Elastic Beanstalk.
This application component posts messages to social media sites in support of various marketing campaigns.
Your management now requires you to record replies to these social media messages to analyze the effectiveness of the marketing campaign in comparison to past and future efforts. You have already developed a new application component to interface with the social media site APIs in order to read the replies.
Which process should you use to record the social media replies in a durable data store that can be accessed at any time for analysis of historical data?
- A. Deploy the new application component as an Amazon Elastic Beanstalk application, read the data from the social media site, store it with Amazon Elastic Block Store, and use Amazon Kinesis to stream the data to Amazon CloudWatch for analytics.
- B. Deploy the new application component in an Auto Scaling group of Amazon Elastic Compute Cloud (EC2) Instances, read the data from the social media sites, store it with Amazon Elastic Block Store, and use AWS Data Pipeline to publish it to Amazon Kinesis for analytics.
- C. Deploy the new application component as an Elastic Beanstalk application, read the data from the social media sites, store it in Amazon DynamoDB, and use Apache Hive with Amazon Elastic MapReduce for analytics.
- D. Deploy the new application component in an Auto Scaling group of Amazon EC2 instances, read the data from the social media sites, store it in Amazon Glacier, and use AWS Data Pipeline to publish it to Amazon Redshift for analytics.
Answer: C
NEW QUESTION # 269
Amazon Inspector agent collects telemetry data during assessment run and sends this data to Amazon Inspector dedicated S3 bucket for analysis. How can you access telemetry data out of Amazon Inspector and how can you benefit from this data in securing your resources?
- A. Telemetry data is stored in Amazon Inspector dedicated S3 bucket that does NOT belong to your account, Amazon Inspector currently does NOT provide an API or an S3 bucket access mechanism to collected telemetry. Data is retained temporarily only to allow for assistance with support requests.
- B. Telemetry data is saved on S3 bucket in your account, therefore telemetry data is accessible with proper permissions on that bucket.
- C. Telemetry data is kept in S3 and encrypted with a pre-assessment test key configured in KMS, as long as you have access to that key you can download and decrypt telemetry data.
- D. Telemetry data is deleted immediately after assessment run, therefore data can NOT be accessed or analyzed by any other tools.
Answer: A
Explanation:
The telemetry data stored in S3 is retained only to allow for assistance with support requests and is not used or aggregated by Amazon for any other purpose. After 30 days, telemetry data is permanently deleted per a standard Amazon Inspector-dedicated S3 bucket lifecycle policy. At present, Amazon Inspector does not provide an API or an S3 bucket access mechanism to collected telemetry.
Reference: https://docs.aws.amazon.com/inspector/latest/userguide/inspector_agents.html
NEW QUESTION # 270
A company is using AWS CodeDeploy to manage its application deployments. Recently, the Development team decided to use GitHub for version control, and the team is looking for ways to integrate the GitHub repository with CodeDeploy. The team also needs to develop a way to automate deployment whenever there is a new commit on that repository. The team is currently deploying new application revisions by manually indicating the Amazon S3 location.
How can the integration be achieved in the MOST efficient way?
- A. Create an AWS Lambda function to check periodically if there has been a new commit within the GitHub repository. If a new commit is found, trigger a CreateDeployment API call to AWS CodeDeploy to start a new deployment based on the last commit ID within the deployment group.
- B. Create a GitHub webhook to replicate the repository to AWS CodeCommit. Create an AWS CodePipeline pipeline that uses CodeCommit as a source provider and AWS CodeDeploy as a deployment provider.
Once configured, commit a change to the GitHub repository to start the first deployment. - C. Create an AWS CodePipeline pipeline that uses GitHub as a source provider and AWS CodeDeploy as a deployment provider. Connect this new pipeline with the GitHub account and instruct CodePipeline to use webhooks in GitHub to automatically start the pipeline when a change occurs.
- D. Create an AWS CodeDeploy custom deployment configuration to associate the GitHub repository with the deployment group. During the association process, authenticate the deployment group with GitHub to obtain the GitHub security authentication token. Configure the deployment group options to automatically deploy if a new commit is found. Perform a new commit to the GitHub repository to trigger the first deployment.
Answer: D
NEW QUESTION # 271
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