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To pass the DOP-C02 exam, candidates need to have a deep understanding of AWS services, DevOps best practices, and how to deploy and manage AWS environments at scale. They also need to demonstrate their ability to design, implement, and automate AWS architectures for diverse use cases. Overall, the DOP-C02 Certification is an essential requirement for anyone who wants to establish themselves as a credible and skilled DevOps professional in the industry.
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Amazon DOP-C02 exam is designed to test the skills and knowledge of professionals who work in DevOps roles. AWS Certified DevOps Engineer - Professional certification is intended for individuals who have a deep understanding of the AWS platform and are experienced in delivering and managing applications on AWS. DOP-C02 exam is designed to validate the skills needed to manage, operate, and deploy applications on AWS, and to demonstrate expertise in DevOps practices and methodologies.
Amazon DOP-C02 (AWS Certified DevOps Engineer - Professional) certification exam is a highly sought after certification that validates the skills and knowledge required to manage and deploy applications on the AWS platform. AWS Certified DevOps Engineer - Professional certification is designed for DevOps engineers who have experience in developing, provisioning, operating and managing applications on the AWS platform. DOP-C02 Exam Tests the candidate's ability to design, deploy, manage, and maintain AWS-based applications using DevOps practices and principles.
Amazon AWS Certified DevOps Engineer - Professional Sample Questions (Q213-Q218):
NEW QUESTION # 213
A company is building a web and mobile application that uses a serverless architecture powered by AWS Lambda and Amazon API Gateway The company wants to fully automate the backend Lambda deployment based on code that is pushed to the appropriate environment branch in an AWS CodeCommit repository The deployment must have the following:
* Separate environment pipelines for testing and production
* Automatic deployment that occurs for test environments only
Which steps should be taken to meet these requirements'?
- A. Create two AWS CodePipeline configurations for test and production environments Configure the production pipeline to have a manual approval step Create aCodeCommit repository for each environment Set up each CodePipeline to retrieve the source code from the appropriate repository Set up the deployment step to deploy the Lambda functions with AWS CloudFormation.
- B. Configure a new AWS CodePipelme service Create a CodeCommit repository for each environment Set up CodePipeline to retrieve the source code from the appropriate repository Set up the deployment step to deploy the Lambda functions with AWS CloudFormation.
- C. Create an AWS CodeBuild configuration for test and production environments Configure the production pipeline to have a manual approval step. Create one CodeCommit repository with a branch for each environment Push the Lambda function code to an Amazon S3 bucket Set up the deployment step to deploy the Lambda functions from the S3 bucket.
- D. Create two AWS CodePipeline configurations for test and production environments Configure the production pipeline to have a manual approval step. Create one CodeCommit repository with a branch for each environment Set up each CodePipeline to retrieve the source code from the appropriate branch in the repository. Set up the deployment step to deploy the Lambda functions with AWS CloudFormation
Answer: D
Explanation:
The correct approach to meet the requirements for separate environment pipelines and automatic deployment for test environments is to create two AWS CodePipeline configurations, one for each environment. The production pipeline should have a manual approval step to ensure that changes are reviewed before being deployed to production. A single AWS CodeCommit repository with separate branches for each environment allows for organized and efficient code management. Each CodePipeline retrieves the source code from the appropriate branch in the repository. The deployment step utilizes AWS CloudFormation to deploy the Lambda functions, ensuring that the infrastructure as code is maintained and version-controlled.
AWS Lambda with Amazon API Gateway: Using AWS Lambda with Amazon API Gateway Tutorial on using Lambda with API Gateway: Tutorial: Using Lambda with API Gateway AWS CodePipeline automatic deployment: Set Up a Continuous Deployment Pipeline Using AWS CodePipeline Building a pipeline for test and production stacks: Walkthrough: Building a pipeline for test and production stacks
NEW QUESTION # 214
A company deploys an API by using an Application Load Balancer (ALB) that targets an AWS Lambda function. The API takes a list of tasks as an input and typically processes the tasks in 40 seconds. The API is CPU intensive and performs writes to an Amazon Aurora PostgreSQL DB cluster. The API also performs frequent large-scale Amazon S3 object PUT requests to the same prefix of an S3 bucket.
The API usage and the number of input tasks is increasing significantly. The increased demand is causing the API response time to increase, and some API requests fail because the database connection quota is being exceeded. A DevOps engineer must improve the performance of the API.
Which combination of solutions will meet this requirement? (Select THREE.)
- A. Update the Lambda function to distribute S3 object PUT requests to multiple prefixes.
- B. Create an Amazon RDS Proxy and configure the Lambda function to use it to perform database operations.
- C. Add a read replica for the Aurora DB cluster.
- D. Refactor the API to use Amazon API Gateway instead of the ALB.
- E. Deploy a Network Load Balancer (NLB) and set the ALB as the target group for the NLB.
- F. Increase the amount of memory for the Lambda function.
Answer: A,B,F
Explanation:
The failures come from three separate pressure points: database connection exhaustion, CPU-bound Lambda execution, and high-volume S3 writes to one prefix. RDS Proxy is designed to improve database connection management, scalability, availability, and security, so it addresses the Aurora connection quota issue.
Increasing Lambda memory is also correct because AWS allocates CPU proportionally with memory; CPU- bound functions can improve dramatically when memory is increased. For S3, AWS documents at least 3,500 PUT/COPY/POST/DELETE requests per second per partitioned prefix and notes that write performance can be scaled by writing across multiple prefixes. NLB in front of ALB adds no value, API Gateway does not solve the listed bottlenecks, and an Aurora read replica does not help a write-heavy workload.
NEW QUESTION # 215
A company is using an AWS CodeBuild project to build and package an application. The packages are copied to a shared Amazon S3 bucket before being deployed across multiple AWS accounts.
The buildspec.yml file contains the following:
The DevOps engineer has noticed that anybody with an AWS account is able to download the artifacts.
What steps should the DevOps engineer take to stop this?
- A. Configure a default ACL for the S3 bucket that defines the set of authenticated users as the relevant AWS accounts only and grants read-only access.
- B. Create an S3 bucket policy that grants read access to the relevant AWS accounts and denies read access to the principal "*".
- C. Modify the post_build command to remove --acl authenticated-read and configure a bucket policy that allows read access to the relevant AWS accounts only.
- D. Modify the post_build command to use --acl public-read and configure a bucket policy that grants read access to the relevant AWS accounts only.
Answer: C
Explanation:
Explanation
When setting the flag authenticated-read in the command line, the owner gets FULL_CONTROL. The AuthenticatedUsers group (Anyone with an AWS account) gets READ access. Reference:
https://docs.aws.amazon.com/AmazonS3/latest/userguide/acl-overview.html
NEW QUESTION # 216
A company is using AWS to run digital workloads. Each application team in the company has its own AWS account for application hosting. The accounts are consolidated in an organization in AWS Organizations.
The company wants to enforce security standards across the entire organization. To avoid noncompliance because of security misconfiguration, the company has enforced the use of AWS CloudFormation. A production support team can modify resources in the production environment by using the AWS Management Console to troubleshoot and resolve application-related issues.
A DevOps engineer must implement a solution to identify in near real time any AWS service misconfiguration that results in noncompliance. The solution must automatically remediate the issue within 15 minutes of identification. The solution also must track noncompliant resources and events in a centralized dashboard with accurate timestamps.
Which solution will meet these requirements with the LEAST development overhead?
- A. Turn on the configuration recorder in AWS Config in all the AWS accounts to identify noncompliant resources. Enable AWS Security Hub with the ~no-enable-default-standards option in all the AWS accounts. Set up AWS Config managed rules and custom rules. Set up automatic remediation by using AWS Config conformance packs. For tracking, set up a dashboard on Security Hub in a designated Security Hub administrator account.
- B. Turn on AWS CloudTrail in the AWS accounts. Analyze CloudTrail logs by using Amazon Athena to identify noncompliant resources. Use AWS Step Functions to track query results on Athena for drift detection and to invoke an AWS Lambda function for remediation. For tracking, set up an Amazon QuickSight dashboard that uses Athena as the data source.
- C. Use CloudFormation drift detection to identify noncompliant resources. Use drift detection events from CloudFormation to invoke an AWS Lambda function for remediation. Configure the Lambda function to publish logs to an Amazon CloudWatch Logs log group. Configure an Amazon CloudWatch dashboard to use the log group for tracking.
- D. Turn on AWS CloudTrail in the AWS accounts. Analyze CloudTrail logs by using Amazon CloudWatch Logs to identify noncompliant resources. Use CloudWatch Logs filters for drift detection. Use Amazon EventBridge to invoke the Lambda function for remediation. Stream filtered CloudWatch logs to Amazon OpenSearch Service. Set up a dashboard on OpenSearch Service for tracking.
Answer: A
Explanation:
The best solution is to use AWS Config and AWS Security Hub to identify and remediate noncompliant resources across multiple AWS accounts. AWS Config enables continuous monitoring of the configuration of AWS resources and evaluates them against desired configurations. AWS Config can also automatically remediate noncompliant resources by using conformance packs, which are a collection of AWS Config rules and remediation actions that can be deployed as a single entity. AWS Security Hub provides a comprehensive view of the security posture of AWS accounts and resources. AWS Security Hub can aggregate and normalize the findings from AWS Config and other AWS services, as well as from partner solutions. AWS Security Hub can also be used to create a dashboard for tracking noncompliant resources and events in a centralized location.
The other options are not optimal because they either require more development overhead, do not provide near real time detection and remediation, or do not provide a centralized dashboard for tracking.
Option A is not optimal because CloudFormation drift detection is not a near real time solution. Drift detection has to be manually initiated on each stack or resource, or scheduled using a cron expression. Drift detection also does not provide remediation actions, so a custom Lambda function has to be developed and invoked. CloudWatch Logs and dashboard can be used for tracking, but they do not provide a comprehensive view of the security posture of the AWS accounts and resources.
Option B is not optimal because CloudTrail logs analysis using Athena is not a near real time solution. Athena queries have to be manually run or scheduled using a cron expression. Athena also does not provide remediation actions, so a custom Lambda function has to be developed and invoked. Step Functions can be used to orchestrate the query and remediation workflow, but it adds more complexity and cost. QuickSight dashboard can be used for tracking, but it does not provide a comprehensive view of the security posture of the AWS accounts and resources.
Option D is not optimal because CloudTrail logs analysis using CloudWatch Logs is not a near real time solution. CloudWatch Logs filters have to be manually created or updated for each resource type and configuration change. CloudWatch Logs also does not provide remediation actions, so a custom Lambda function has to be developed and invoked. EventBridge can be used to trigger the Lambda function, but it adds more complexity and cost. OpenSearch Service dashboard can be used for tracking, but it does not provide a comprehensive view of the security posture of the AWS accounts and resources.
:
AWS Config conformance packs
Introducing AWS Config conformance packs
Managing conformance packs across all accounts in your organization
NEW QUESTION # 217
A company has deployed a new platform that runs on Amazon Elastic Kubernetes Service (Amazon EKS).
The new platform hosts web applications that users frequently update. The application developers build the Docker images for the applications and deploy the Docker images manually to the platform.
The platform usage has increased to more than 500 users every day. Frequent updates, building the updated Docker images for the applications, and deploying the Docker images on the platform manually have all become difficult to manage.
The company needs to receive an Amazon Simple Notification Service (Amazon SNS) notification if Docker image scanning returns any HIGH or CRITICAL findings for operating system or programming language package vulnerabilities.
Which combination of steps will meet these requirements? (Select TWO.)
- A. Create an AWS CodeBuild project that scans the Dockerfile. Configure the project to build the Docker images and store the Docker images in an Amazon Elastic Container Registry (Amazon ECR) repository if the scan is successful. Configure an SNS topic to provide notification if the scan returns any vulnerabilities.
- B. Create an AWS CodeCommit repository to store the Dockerfile and Kubernetes deployment files.
Create a pipeline in AWS CodePipeline. Use an Amazon EvenlBridge event to invoke the pipeline when a newer version of the Dockerfile is committed. Add a step to the pipeline to initiate the AWS CodeBuild project. - C. Create an AWS CodeBuild project that builds the Docker images and stores the Docker images in an Amazon Elastic Container Registry (Amazon ECR) repository. Turn on basic scanning for the ECR repository. Create an Amazon EventBridge rule that monitors Amazon GuardDuty events. Configure the EventBridge rule to send an event to an SNS topic when the finding-severity-counts parameter is more than 0 at a CRITICAL or HIGH level.
- D. Create an AWS CodeCommit repository to store the Dockerfile and Kubernetes deployment files.
Create a pipeline in AWS CodePipeline. Use an Amazon S3 event to invoke the pipeline when a newer version of the Dockerfile is committed. Add a stop to the pipeline to initiate the AWS CodeBuild project. - E. Create an AWS CodeBuild project that builds the Docker images and stores the Docker images in an Amazon Elastic Container Registry (Amazon ECR) repository. Turn on enhanced scanning for the ECR repository. Create an Amazon EventBridge rule that monitors ECR image scan events. Configure the EventBridge rule to send an event to an SNS topic when the finding-severity-counts parameter is more than 0 at a CRITICAL or HIGH level.
Answer: B,E
Explanation:
Step 1: Automate Docker Image Deployment using AWS CodePipelineThe first challenge is the manual process of building and deploying Docker images. To address this, you can use AWS CodePipeline to automate the process. AWS CodePipeline integrates with CodeCommit (for source code and Dockerfile storage) and CodeBuild (to build Docker images and store them in Amazon Elastic Container Registry (ECR)).
* Action:Create an AWS CodeCommit repository to store the Dockerfile and Kubernetes deployment files. Then, create a pipeline in AWS CodePipeline that triggers on new commits via an Amazon EventBridge event.
* Why:This automation significantly reduces the manual effort of building and deploying Docker images when updates are made to the codebase.
NEW QUESTION # 218
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