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Amazon DOP-C02 Exam Syllabus Topics:

Section	Weight	Objectives
Incident and Event Response	18%	- Design and implement event and incident management 1. Implement automated response playbooks 2. Implement automated incident detection 3. Design event aggregation and correlation - Design and implement chaos engineering practices 1. Analyze system behavior under failure conditions 2. Implement fault injection experiments (AWS Fault Injection Simulator) 3. Design resilience testing strategies
Monitoring and Logging	12%	- Design and implement monitoring and observability strategies 1. Implement distributed tracing (AWS X-Ray) 2. Implement log aggregation and analysis 3. Design custom metrics and alarms (Amazon CloudWatch) - Design and implement alerting and incident management 1. Create alarm notification strategies 2. Implement automated incident response 3. Design runbook automation
Configuration Management and Infrastructure as Code	22%	- Implement compliance and configuration monitoring 1. Use AWS Config for compliance monitoring 2. Implement AWS CloudTrail for auditing 3. Design remediation automation - Design and implement configuration management 1. Implement AWS Systems Manager for configuration management 2. Implement parameter management (AWS Parameter Store, Secrets Manager) 3. Design patch management strategies - Design and implement data management strategies 1. Design backup and recovery solutions 2. Implement data lifecycle management 3. Implement database migration strategies - Design and implement infrastructure as code 1. Design for scalability and repeatability 2. Develop IaC templates (AWS CloudFormation, Terraform) 3. Implement modular and reusable infrastructure components
Policies and Standards Automation	10%	- Design and implement preventive and detective controls 1. Design and implement security baselines 2. Implement drift detection and remediation 3. Implement AWS Organizations and SCPs - Design and implement governance strategies 1. Implement tagging policies and resource grouping 2. Design cost optimization through policies 3. Implement approval workflows and automation
High Availability and Disaster Recovery	16%	- Design and implement disaster recovery strategies 1. Implement backup and restore mechanisms 2. Design RTO and RPO based DR solutions 3. Implement pilot light and warm standby architectures 4. Implement multi-region active-active architectures - Implement data backup and restore strategies 1. Implement cross-region replication 2. Implement validation testing for backups 3. Design point-in-time recovery solutions - Design and implement high availability and scalability 1. Design multi-AZ and multi-region architectures 2. Implement load balancing and traffic management 3. Implement auto scaling strategies
SDLC Automation	22%	- Design and implement CI/CD pipelines 1. Develop CI/CD pipelines considering testing and security requirements 2. Implement deployment strategies (blue-green, canary, rolling) 3. Design failure handling strategies 4. Determine appropriate CI/CD pipeline architecture - Design and implement source code management strategies 1. Implement repository configurations and hooks 2. Design code review and approval processes 3. Determine branching strategies - Design build and test environments 1. Integrate security scanning and compliance checks 2. Implement build environments (isolated, reproducible) 3. Design test automation frameworks

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Amazon AWS Certified DevOps Engineer - Professional Sample Questions (Q275-Q280):

NEW QUESTION # 275
A company has an application that runs on Amazon EC2 instances in an Auto Scaling group. The application processes a high volume of messages from an Amazon Simple Queue Service (Amazon SQS) queue.
A DevOps engineer noticed that the application took several hours to process a group of messages from the SQS queue. The average CPU utilization of the Auto Scaling group did not cross the threshold of a target tracking scaling policy when processing the messages. The application that processes the SQS queue publishes logs to Amazon CloudWatch Logs.
The DevOps engineer needs to ensure that the queue is processed quickly.
Which solution meets these requirements with the LEAST operational overhead?

A. Create an AWS Lambda function. Configure the Lambda function to publish a custom metric by using the ApproximateNumberOfMessagesVisible SQS queue attribute and the GroupIn-ServiceInstances Auto Scaling group attribute to publish the queue messages for each instance. Create a CloudWatch subscription filter for the application logs with the Lambda function as the target. Create a target tracking scaling policy for the Auto Scaling group that uses the custom metric to scale in and out.
B. Create an AWS Lambda function that logs the ApproximateNumberOfMessagesVisible attribute of the SQS queue to a CloudWatch Logs log group. Schedule an Amazon EventBridge rule to run the Lambda function every 5 minutes. Create a metric filter to count the number of log events from a CloudWatch logs group. Create a target tracking scaling policy for the Auto Scaling group that uses the custom metric to scale in and out.
C. Create an AWS Lambda function. Configure the Lambda function to publish a custom metric by using the ApproximateNumberOfMessagesVisible SQS queue attribute and the GroupIn-ServiceInstances Auto Scaling group attribute to publish the queue messages for each instance. Schedule an Amazon EventBridge rule to run the Lambda function every hour. Create a target tracking scaling policy for the Auto Scaling group that uses the custom metric to scale in and out.
D. Create a target tracking scaling policy for the Auto Scaling group. In the target tracking policy, use the ApproximateNumberOfMessagesVisible SQS queue attribute and the GroupIn-ServiceInstances Auto Scaling group attribute to calculate how many messages are in the queue for each number of instances by using metric math. Use the calculated attribute to scale in and out.

Answer: D

Explanation:
Comprehensive and Detailed Explanation From Exact Extract:
The default CPU utilization metric does not reflect the processing backlog in the SQS queue, so the Auto Scaling group is not scaling properly to handle the workload.
To scale the Auto Scaling group based on queue length, you can create a target tracking scaling policy that uses acustom metricthat combines the SQS queue'sApproximateNumberOfMessagesVisibleand the number of instances (GroupIn-ServiceInstances) metric usingCloudWatch metric math. This allows the scaling policy to calculate the average number of messages per instance and scale accordingly.
This approach requires no additional Lambda functions or log processing, thus minimizing operational overhead.
Option A and B require Lambda functions to publish custom metrics, which increases operational complexity.
Option D also adds complexity with logging and metric filters.
Reference:
Scaling based on SQS queue length using metric math:"You can create CloudWatch metric math expressions combining SQS and Auto Scaling group metrics to enable target tracking scaling policies that respond to queue backlog."(AWS Auto Scaling with SQS) Target Tracking Scaling Policies:"Target tracking policies can use metric math expressions as a source to make scaling decisions."(AWS Auto Scaling Target Tracking)

NEW QUESTION # 276
A Company uses AWS CodeCommit for source code control. Developers apply their changes to various feature branches and create pull requests to move those changes to the main branch when the changes are ready for production.
The developers should not be able to push changes directly to the main branch. The company applied the AWSCodeCommitPowerUser managed policy to the developers' IAM role, and now these developers can push changes to the main branch directly on every repository in the AWS account.
What should the company do to restrict the developers' ability to push changes to the main branch directly?

A. Modify the IAM policy Include a Deny rule for the GitPush and PutFile actions for the specific repositories in the policy statement with a condition that references the main branch.
B. Create an additional policy to include an Allow rule for the GitPush and PutFile actions. Include a restriction for the specific repositories in the policy statement with a condition that references the feature branches.
C. Create an additional policy to include a Deny rule for the GitPush and PutFile actions. Include a restriction for the specific restriction for the specific repositories in the policy repositories in the policy statement with a condition that references the main branch.
A Create an additional policy to include a Deny rule for the GitPush and PutFile actions Include a restriction for the specific repositories in the policy statement with a condition that references the main branch
D. Remove the IAM policy, and add an AWSCodeCommitReadOnly managed policy. Add an Allow rule for the GitPush and PutFile actions for the specific repositories in the policy statement with a condition that references the mam branch.

Answer: C

Explanation:
By default, the AWSCodeCommitPowerUser managed policy allows users to push changes to any branch in any repository in the AWS account. To restrict the developers' ability to push changes to the main branch directly, an additional policy is needed that explicitly denies these actions for the main branch.
The Deny rule should be included in a policy statement that targets the specific repositories and includes a condition that references the main branch. The policy statement should look something like this:
{
"Effect": "Deny",
"Action": [
"codecommit:GitPush",
"codecommit:PutFile"
],
"Resource": "arn:aws:codecommit:<region>:<account-id>:<repository-name>",
"Condition": {
"StringEqualsIfExists": {
"codecommit:Reference": [
"refs/heads/main"
]
}
}

NEW QUESTION # 277
A company wants to improve its security practices by enforcing least privilege across all projects. Developers must be able to access Amazon EC2 resources but not Amazon RDS resources. Database administrators must have access only to Amazon RDS resources.
Every employee has a unique IAM user. There are already pre-existing IAM policies for developer and database administrator job functions. All AWS resources are already tagged with appropriate project tags. All the IAM users are tagged with the appropriate project and job function.
The company must ensure that each employee can access only the project that the employee is working on.
Which solution will meet these requirements? (Select THREE.)

A. Create an IAM policy that allows users to assume a role only when the ResourceTag values match the PrincipalTag values for project tags and job function tags. Attach the new policy to the IAM roles for each job function.
B. Tag the pre-existing IAM policies with the appropriate projects and job functions. Attach the modified policies to IAM roles for each job function.
C. For each project, create one IAM group for developers and one IAM group for database administrators. Add the appropriate users to each group so the users can assume their respective IAM roles.
D. Create an IAM policy that allows users to assume a role only when the ResourceTag values match the PrincipalTag values for project tags and job function tags. Attach the new policy to all IAM users.
E. Modify the pre-existing IAM policies to include a StringEquals condition that compares the ResourceTag for projects with the PrincipalTag value. Attach the modified policies to the IAM roles for each job function.
F. For each project, create one IAM role for developers and one IAM role for database administrators. Tag the IAM roles with the corresponding projects and job functions.

Answer: D,E,F

Explanation:
The requirements describe a classic attribute-based access control (ABAC) model using AWS IAM. The company already has consistent tagging across users and resources, which is ideal for ABAC and least-privilege enforcement at scale.
First, Option A is required because IAM roles should represent job functions (developer vs. database administrator) and be scoped per project. Creating separate roles per project and job function allows permissions to be isolated cleanly and prevents cross-project access.
Second, Option B enforces project-level isolation at the policy level. By modifying the existing job-function policies to include a StringEquals condition that compares aws:ResourceTag/Project with aws:PrincipalTag/Project, access is automatically limited to only those resources that belong to the same project as the user. This is an AWS-recommended ABAC pattern and avoids policy sprawl.
Third, Option C is required so users can assume roles only when their tags match the role's tags. An IAM policy attached to users that allows sts:AssumeRole only if both project and job function tags match ensures users cannot assume roles outside their assigned scope.
Options D, E, and F either misapply policies to the wrong entities, misuse tagging on policies (which IAM does not evaluate for authorization), or introduce unnecessary group-based management that conflicts with the ABAC design.
Therefore, A, B, and C together provide least privilege, project isolation, and scalable access control with minimal ongoing administration.

NEW QUESTION # 278
A DevOps engineer must implement a solution that immediately terminates Amazon EC2 instances in Auto Scaling groups when cryptocurrency mining activity is detected.
Which solution will meet these requirements with the LEAST development effort?

A. Configure Amazon Route 53 to send query logs directly to Amazon CloudWatch Logs. Create an AWS Lambda function that runs every 5 minutes and checks the query logs for domains related to cryptocurrency activity. If the domains are found, terminate the identified EC2 instances.
B. Enable Amazon GuardDuty. Monitor EC2 findings. Create an Amazon EventBridge rule with GuardDuty as the event source. Create an AWS Lambda function that is triggered by the EventBridge rule. Configure the Lambda function to parse the event and terminate the identified EC2 instances.
C. Configure VPC Flow Logs to send flow logs to an Amazon S3 bucket. Create an AWS Lambda function that runs every 5 minutes and invokes an Amazon Athena query to find IP addresses associated with cryptocurrency activity. If the IP addresses are found, terminate the identified EC2 instances.
D. Enable AWS Security Hub. Monitor EC2 findings. Create an Amazon EventBridge rule with Security Hub as the event source. Create an AWS Lambda function that is triggered by the EventBridge rule. Configure the Lambda function to parse the event and terminate the identified EC2 instances.

Answer: B

NEW QUESTION # 279
A company hosts applications in its AWS account Each application logs to an individual Amazon CloudWatch log group. The company's CloudWatch costs for ingestion are increasing A DevOps engineer needs to Identify which applications are the source of the increased logging costs.
Which solution Will meet these requirements?

A. Use AWS Cost Explorer to generate a cost report that details the cost for CloudWatch usage
B. Use CloudWatch metrics to create a custom expression that Identifies the CloudWatch log groups that have the most data being written to them.
C. Use AWS CloudTrail to filter for CreateLogStream events for each application
D. Use CloudWatch Logs Insights to create a set of queries for the application log groups to Identify the number of logs written for a period of time

Answer: A

Explanation:
Explanation
The correct answer is C.
A comprehensive and detailed explanation is:
Option A is incorrect because using CloudWatch metrics to create a custom expression that identifies the CloudWatch log groups that have the most data being written to them is not a valid solution.
CloudWatch metrics do not provide information about the size or volume of data being ingested by CloudWatch logs. CloudWatch metrics only provide information about the number of events, bytes, and errors that occur within a log group or stream. Moreover, creating a custom expression with CloudWatch metrics would require using the search_web tool, which is not necessary for this use case.
Option B is incorrect because using CloudWatch Logs Insights to create a set of queries for the application log groups to identify the number of logs written for a period of time is not a valid solution.
CloudWatch Logs Insights can help analyze and filter log events based on patterns and expressions, but it does not provide information about the cost or billing of CloudWatch logs. CloudWatch Logs Insights also charges based on the amount of data scanned by each query, which could increase the logging costs further.
Option C is correct because using AWS Cost Explorer to generate a cost report that details the cost for CloudWatch usage is a valid solution. AWS Cost Explorer is a tool that helps visualize, understand, and manage AWS costs and usage over time. AWS Cost Explorer can generate custom reports that show the breakdown of costs by service, region, account, tag, or any other dimension. AWS Cost Explorer can also filter and group costs by usage type, which can help identify the specific CloudWatch log groups that are the source of the increased logging costs.
Option D is incorrect because using AWS CloudTrail to filter for CreateLogStream events for each application is not a valid solution. AWS CloudTrail is a service that records API calls and account activity for AWS services, including CloudWatch logs. However, AWS CloudTrail does not provide information about the cost or billing of CloudWatch logs. Filtering for CreateLogStream events would only show when a new log stream was created within a log group, but not how much data was ingested or stored by that log stream.
References:
CloudWatch Metrics
CloudWatch Logs Insights
AWS Cost Explorer
AWS CloudTrail

NEW QUESTION # 280
......

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