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To be eligible for the Amazon DOP-C02 Certification Exam, individuals must have a minimum of two years of experience working with AWS services and at least one year of experience working with DevOps practices. Additionally, candidates must hold the AWS Certified Developer - Associate or AWS Certified SysOps Administrator - Associate certification.
The AWS Certified DevOps Engineer - Professional certification exam is intended for professionals with at least two years of experience in DevOps and AWS. Candidates should have a strong grasp of AWS services, automation techniques, and best practices for continuous integration and delivery (CI/CD) pipelines. AWS Certified DevOps Engineer - Professional certification exam is a comprehensive test of the skills required to design, implement, and manage DevOps systems on AWS.
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Amazon DOP-C02 (AWS Certified DevOps Engineer - Professional) Certification Exam is a professional-level certification offered by Amazon Web Services (AWS), which is designed to validate the skills and knowledge of individuals working in DevOps roles. DOP-C02 exam focuses on the advanced concepts and best practices of DevOps, such as continuous integration and deployment, infrastructure as code, monitoring, and automation. DOP-C02 Exam is intended for individuals with at least two years of experience in DevOps and familiarity with AWS services.
NEW QUESTION # 351
A company runs an application with an Amazon EC2 and on-premises configuration. A DevOps engineer needs to standardize patching across both environments. Company policy dictates that patching only happens during non-business hours.
Which combination of actions will meet these requirements? (Choose three.)
Answer: A,E,F
NEW QUESTION # 352
A company has an organization in AWS Organizations. A DevOps engineer needs to maintain multiple AWS accounts that belong to different OUs in the organization. All resources, including 1AM policies and Amazon S3 policies within an account, are deployed through AWS CloudFormation. All templates and code are maintained in an AWS CodeCommit repository Recently, some developers have not been able to access an S3 bucket from some accounts in the organization.
The following policy is attached to the S3 bucket.
What should the DevOps engineer do to resolve this access issue?
Answer: B
Explanation:
Verify No SCP Blocking Access:
Ensure that no Service Control Policy (SCP) is blocking access for developers to the S3 bucket. SCPs are applied at the organization or organizational unit (OU) level in AWS Organizations and can restrict what actions users and roles in the affected accounts can perform.
Verify No IAM Policy Permissions Boundaries Blocking Access:
IAM permissions boundaries can limit the maximum permissions that a user or role can have. Verify that these boundaries are not restricting access to the S3 bucket.
Make Necessary Changes to SCP and IAM Policy Permissions Boundaries:
Adjust the SCPs and IAM permissions boundaries if they are found to be the cause of the access issue. Make sure these changes are reflected in the code maintained in the AWS CodeCommit repository.
Invoke Deployment Through CloudFormation:
Commit the updated policies to the CodeCommit repository.
Use AWS CloudFormation to deploy the changes across the relevant accounts and resources to ensure that the updated permissions are applied consistently.
By ensuring no SCPs or IAM policy permissions boundaries are blocking access and making necessary changes if they are, the DevOps engineer can resolve the access issue for developers trying to access the S3 bucket.
References:
AWS SCPs
IAM Permissions Boundaries
Deploying CloudFormation Templates
NEW QUESTION # 353
A DevOps engineer has created an AWS CloudFormation template that deploys an application on Amazon EC2 instances The EC2 instances run Amazon Linux The application is deployed to the EC2 instances by using shell scripts that contain user data. The EC2 instances have an 1AM instance profile that has an 1AM role with the AmazonSSMManagedlnstanceCore managed policy attached The DevOps engineer has modified the user data in the CloudFormation template to install a new version of the application. The engineer has also applied the stack update. However, the application was not updated on the running EC2 instances. The engineer needs to ensure that the changes to the application are installed on the running EC2 instances.
Which combination of steps will meet these requirements? (Select TWO.)
Answer: A,E
Explanation:
Refactor User Data to Use cfn-init and cfn-hup:
* cfn-inithelps to bootstrap the instance, installing packages and starting services.
* cfn-hupis a daemon that can monitor metadata changes and re-apply configurations when necessary.
Example user data script withcfn-init:
#!/bin/bash
yum update -y
yum install -y aws-cfn-bootstrap
/opt/aws/bin/cfn-init -v --stack ${AWS::StackName} --resource WebServer --region ${AWS::Region}
/opt/aws/bin/cfn-hup
Use Systems Manager State Manager:
* State Manager can automatically apply an AWS Systems Manager document to instances at regular intervals, ensuring configurations are kept up-to-date.
Steps:
* Create an SSM document that installs and configures your application.
* Use State Manager to associate this document with your EC2 instances.
Example SSM document:
{
"schemaVersion": "2.2",
"description": "Install My Application",
"mainSteps": [
{
"action": "aws:runShellScript",
"name": "installApplication",
"inputs": {
"runCommand": [
"yum install -y my-application"
]
}
}
]
}
Create State Manager association:
aws ssm create-association --name "InstallMyApplication" --instance-id <instance-id> --document-version
"\$LATEST"
References:
* Using cfn-init and cfn-hup
* AWS Systems Manager State Manager
NEW QUESTION # 354
A company provides an application to customers. The application has an Amazon API Gateway REST API that invokes an AWS Lambda function. On initialization, the Lambda function loads a large amount of data from an Amazon DynamoDB table. The data load process results in long cold-start times of 8-10 seconds.
The DynamoDB table has DynamoDB Accelerator (DAX) configured.
Customers report that the application intermittently takes a long time to respond to requests. The application receives thousands of requests throughout the day. In the middle of the day, the application experiences 10 times more requests than at any other time of the day. Near the end of the day, the application's request volume decreases to 10% of its normal total.
A DevOps engineer needs to reduce the latency of the Lambda function at all times of the day.
Which solution will meet these requirements?
Answer: B
Explanation:
The following are the steps that the DevOps engineer should take to reduce the latency of the Lambda function at all times of the day:
* Configure provisioned concurrency on the Lambda function.
* Configure AWS Application Auto Scaling on the Lambda function with provisioned concurrency values set to a minimum of 1 and a maximum of 100.
The provisioned concurrency setting ensures that there is always a minimum number of Lambda function instances available to handle requests. The Application Auto Scalingsetting will automatically scale the number of Lambda function instances up or down based on the demand for the application.
This solution will ensure that the Lambda function is able to handle the increased load during the middle of the day, while also keeping the cold-start latency low.
The following are the reasons why the other options are not correct:
* Option A is incorrect because it will not reduce the cold-start latency of the Lambda function.
* Option B is incorrect because it will not scale the number of Lambda function instances up or down based on demand.
* Option D is incorrect because it will only configure reserved concurrency on the API Gateway API, which will not affect the Lambda function.
NEW QUESTION # 355
A company recently deployed its web application on AWS. The company is preparing for a large-scale sales event and must ensure that the web application can scale to meet the demand The application's frontend infrastructure includes an Amazon CloudFront distribution that has an Amazon S3 bucket as an origin. The backend infrastructure includes an Amazon API Gateway API. several AWS Lambda functions, and an Amazon Aurora DB cluster The company's DevOps engineer conducts a load test and identifies that the Lambda functions can fulfill the peak number of requests However, the DevOps engineer notices request latency during the initial burst of requests Most of the requests to the Lambda functions produce queries to the database A large portion of the invocation time is used to establish database connections Which combination of steps will provide the application with the required scalability? (Select TWO)
Answer: C,D
Explanation:
The correct answer is B and E. Configuring a higher provisioned concurrency for the Lambda functions will ensure that the functions are ready to respond to the initial burst of requests without any cold start latency. Using Amazon RDS Proxy to create a proxy for the Aurora database will enable the Lambda functions to reuse existing database connections and reduce the overhead of establishing new ones. This will also improve the scalability and availability of the database by managing the connection pool size and handling failovers. Option A is incorrect because reserved concurrency only limits the number of concurrent executions for a function, not pre-warms them. Option C is incorrect because converting the DB cluster to an Aurora global database will not address the issue of database connection latency, and may introduce additional costs and complexity. Option D is incorrect because moving the code blocks that initialize database connections into the function handlers will not improve the performance or scalability of the Lambda functions, and may actually worsen the cold start latency. References:
AWS Lambda Provisioned Concurrency
Using Amazon RDS Proxy with AWS Lambda
Certified DevOps Engineer - Professional (DOP-C02) Study Guide (page 173)
NEW QUESTION # 356
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