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Amazon DOP-C02 Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: Configuration Management and Infrastructure as Code	22%	- 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 configuration management 1. Design patch management strategies 2. Implement AWS Systems Manager for configuration management 3. Implement parameter management (AWS Parameter Store, Secrets Manager) - Design and implement infrastructure as code 1. Develop IaC templates (AWS CloudFormation, Terraform) 2. Design for scalability and repeatability 3. Implement modular and reusable infrastructure components - Implement compliance and configuration monitoring 1. Design remediation automation 2. Use AWS Config for compliance monitoring 3. Implement AWS CloudTrail for auditing
Topic 2: High Availability and Disaster Recovery	16%	- Implement data backup and restore strategies 1. Design point-in-time recovery solutions 2. Implement validation testing for backups 3. Implement cross-region replication - Design and implement disaster recovery strategies 1. Implement pilot light and warm standby architectures 2. Implement multi-region active-active architectures 3. Design RTO and RPO based DR solutions 4. Implement backup and restore mechanisms - 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
Topic 3: Policies and Standards Automation	10%	- Design and implement preventive and detective controls 1. Implement drift detection and remediation 2. Design and implement security baselines 3. Implement AWS Organizations and SCPs - Design and implement governance strategies 1. Implement approval workflows and automation 2. Design cost optimization through policies 3. Implement tagging policies and resource grouping
Topic 4: Incident and Event Response	18%	- Design and implement chaos engineering practices 1. Analyze system behavior under failure conditions 2. Design resilience testing strategies 3. Implement fault injection experiments (AWS Fault Injection Simulator) - Design and implement event and incident management 1. Implement automated incident detection 2. Design event aggregation and correlation 3. Implement automated response playbooks
Topic 5: Monitoring and Logging	12%	- Design and implement monitoring and observability strategies 1. Implement log aggregation and analysis 2. Implement distributed tracing (AWS X-Ray) 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
Topic 6: SDLC Automation	22%	- Design build and test environments 1. Design test automation frameworks 2. Integrate security scanning and compliance checks 3. Implement build environments (isolated, reproducible) - Design and implement CI/CD pipelines 1. Develop CI/CD pipelines considering testing and security requirements 2. Determine appropriate CI/CD pipeline architecture 3. Design failure handling strategies 4. Implement deployment strategies (blue-green, canary, rolling) - Design and implement source code management strategies 1. Implement repository configurations and hooks 2. Design code review and approval processes 3. Determine branching strategies

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Amazon AWS Certified DevOps Engineer - Professional Sample Questions (Q290-Q295):

NEW QUESTION # 290
A company is launching an application that stores raw data in an Amazon S3 bucket. Three applications need to access the data to generate reports. The data must be redacted differently for each application before the applications can access the data.
Which solution will meet these requirements?

A. For each application, create an S3 access point that uses the raw data's S3 bucket as the destination.
Create an AWS Lambda function that is invoked by object creation events in the raw data's S3 bucket.
Program the Lambda function to redact data for each application. Store the data in each application's S3 access point. Configure each application to consume data from its own S3 access point.
B. Create an S3 access point that uses the raw data's S3 bucket as the destination. For each application, create an S3 Object Lambda access point that uses the S3 access point. Configure the AWS Lambda function for each S3 Object Lambda access point to redact data when objects are retrieved. Configure each application to consume data from its own S3 Object Lambda access point.
C. Create an Amazon Kinesis data stream. Create an AWS Lambda function that is invoked by object creation events in the raw data's S3 bucket. Program the Lambda function to redact data for each application. Publish the data on the Kinesis data stream. Configure each application to consume data from the Kinesis data stream.
D. Create an S3 bucket for each application. Configure S3 Same-Region Replication (SRR) from the raw data's S3 bucket to each application's S3 bucket. Configure each application to consume data from its own S3 bucket.

Answer: B

Explanation:
* The best solution is to use S3 Object Lambda1, which allows you to add your own code to S3 GET, LIST, and HEAD requests to modify and process data as it is returned to an application2. This way, you can redact the data differently for each application without creating and storing multiple copies of the data or running proxies.
* The other solutions are less efficient or scalable because they require replicating the data to multiple buckets, streaming the data through Kinesis, or storing the data in S3 access points.
References: 1: Amazon S3 Features | Object Lambda | AWS 2: Transforming objects with S3 Object Lambda
- Amazon Simple Storage Service

NEW QUESTION # 291
A company ' s web application uses an Application Load Balancer (ALB) to direct traffic to Amazon EC2 instances across three Availability Zones.
The company has deployed a newer version of the application to one Availability Zone for testing. If a problem is detected with the application, the company wants to direct traffic away from the affected Availability Zone until the deployment has been rolled back. The application must remain available and maintain static stability during the rollback.
Which solution will meet these requirements with the MOST operational efficiency?

A. Configure cross-zone load balancing on the ALB's target group to inherit settings from the ALB.
Initiate a zonal shift on the ALB to direct traffic away from the affected Availability Zone.
B. Disable cross-zone load balancing on the ALB's target group. Initiate a zonal shift on the ALB to direct traffic away from the affected Availability Zone.
C. Disable cross-zone load balancing on the ALB's target group. Manually remove instances in the target group that belong to the affected Availability Zone.
D. Configure cross-zone load balancing on the ALB's target group to inherit settings from the ALB.
Remove the subnet that is associated with the affected Availability Zone.

Answer: B

Explanation:
A zonal shift in Amazon Application Recovery Controller is the correct mechanism for quickly moving traffic away from an impaired Availability Zone while keeping the application active in healthy zones. AWS states that zonal shift causes the load balancer to stop sending new traffic to the affected Availability Zone. For ALB targets, the shifted-away targets receive an AdministrativeOverride state, and the ALB stops routing new traffic to them while existing connections close normally. Disabling cross-zone load balancing at the target group level supports the static-stability goal because traffic and capacity remain zonally scoped. Option B is manual and slower. Option C leaves cross-zone inheritance in place, which weakens zonal isolation. Option D changes subnet configuration and is operationally riskier than ARC zonal shift.

NEW QUESTION # 292
A company is launching an application. The application must use only approved AWS services. The account that runs the application was created less than 1 year ago and is assigned to an AWS Organizations OU.
The company needs to create a new Organizations account structure. The account structure must have an appropriate SCP that supports the use of only services that are currently active in the AWS account.
The company will use AWS Identity and Access Management (IAM) Access Analyzer in the solution.
Which solution will meet these requirements?

A. Create an SCP that allows the services that IAM Access Analyzer identifies. Attach the new SCP to the organization's root.
B. Create an SCP that allows the services that IAM Access Analyzer identifies. Create an OU for the account. Move the account into the new OU. Attach the new SCP to the new OU. Detach the default FullAWSAccess SCP from the new OU.
C. Create an SCP that denies the services that IAM Access Analyzer identifies. Create an OU for the account. Move the account into the new OIJ. Attach the new SCP to the new OU.
D. Create an SCP that allows the services that IAM Access Analyzer identifies. Create an OU for the account. Move the account into the new OU. Attach the new SCP to the management account. Detach the default FullAWSAccess SCP from the new OU.

Answer: B

Explanation:
To meet the requirements of creating a new Organizations account structure with an appropriate SCP that supports the use of only services that are currently active in the AWS account, the company should use the following solution:
Create an SCP that allows the services that IAM Access Analyzer identifies. IAM Access Analyzer is a service that helps identify potential resource-access risks by analyzing resource-based policies in the AWS environment. IAM Access Analyzer can also generate IAM policies based on access activity in the AWS CloudTrail logs. By using IAM Access Analyzer, the company can create an SCP that grants only the permissions that are required for the application to run, and denies all other services. This way, the company can enforce the use of only approved AWS services and reduce the risk of unauthorized access12 Create an OU for the account. Move the account into the new OU. An OU is a container for accounts within an organization that enables you to group accounts that have similar business or security requirements. By creating an OU for the account, the company can apply policies and manage settings for the account as a group. The company should move the account into the new OU to make it subject to the policies attached to the OU3 Attach the new SCP to the new OU. Detach the default FullAWSAccess SCP from the new OU. An SCP is a type of policy that specifies the maximum permissions for an organization or organizational unit (OU). By attaching the new SCP to the new OU, the company can restrict the services that are available to all accounts in that OU, including the account that runs the application. The company should also detach the default FullAWSAccess SCP from the new OU, because this policy allows all actions on all AWS services and might override or conflict with the new SCP45 The other options are not correct because they do not meet the requirements or follow best practices. Creating an SCP that denies the services that IAM Access Analyzer identifies is not a good option because it might not cover all possible services that are not approved or required for the application. A deny policy is also more difficult to maintain and update than an allow policy. Creating an SCP that allows the services that IAM Access Analyzer identifies and attaching it to the organization's root is not a good option because it might affect other accounts and OUs in the organization that have different service requirements or approvals. Creating an SCP that allows the services that IAM Access Analyzer identifies and attaching it to the management account is not a valid option because SCPs cannot be attached directly to accounts, only to OUs or roots.
References:
1: Using AWS Identity and Access Management Access Analyzer - AWS Identity and Access Management
2: Generate a policy based on access activity - AWS Identity and Access Management
3: Organizing your accounts into OUs - AWS Organizations
4: Service control policies - AWS Organizations
5: How SCPs work - AWS Organizations

NEW QUESTION # 293
A company runs an application in an Amazon Elastic Container Service (Amazon ECS) service that is associated with an Elastic Load Balancing (ELB) target group. A DevOps engineer updates the service to include a new task definition version. The DevOps engineer notices that the deployment does not finish running. New tasks enter a stopped state soon after the tasks launch. The task definition references an Amazon CloudWatch Logs log group.
Which issues are most likely the cause of the failing deployment? (Select TWO.)

A. The IAM role that the DevOps engineer used to update the ECS service does not have the Amazon ECS RunTask permission.
B. An essential container in the ECS task is exiting.
C. The CloudWatch Logs log group that is referenced in the task definition does not exist.
D. The target group health check is failing, which causes Amazon ECS to stop the tasks.
E. The task role does not have the required permissions to launch the task.

Answer: B,D

Explanation:
Comprehensive and Detailed Explanation From Exact Extract of DevOps Engineer documents only:
During an Amazon ECS service deployment, if tasks fail the Elastic Load Balancing target group health checks, Amazon ECS considers those tasks unhealthy and stops and replaces them. This behavior can cause the deployment to remain incomplete because healthy replacement tasks never become available.
Also, if an essential container in the task exits, the entire task stops. Since the question states that the new tasks enter a stopped state soon after launch, an essential container failure is a direct and highly likely cause.
Why the other options are incorrect:
B). The IAM role used by the DevOps engineer to update the ECS service does not need RunTask permission for the tasks to remain running after launch. A permission issue here would more likely affect the update action itself rather than cause launched tasks to stop shortly afterward.
C). Although CloudWatch Logs configuration problems can affect logging, the missing log group is not the most likely direct reason for ECS tasks to repeatedly stop in this deployment scenario.
D). The task role provides permissions to the application code running inside the container. It is not the role primarily responsible for launching the task. Task startup is typically related to the task execution role, ECS service behavior, container health, and load balancer checks.

NEW QUESTION # 294
A company has a single developer writing code for an automated deployment pipeline. The developer is storing source code in an Amazon S3 bucket for each project. The company wants to add more developers to the team but is concerned about code conflicts and lost work The company also wants to build a test environment to deploy newer versions of code for testing and allow developers to automatically deploy to both environments when code is changed in the repository.
What is the MOST efficient way to meet these requirements?

A. Enable versioning and branching on each S3 bucket, use the main branch for production code, and create a testing branch for code deployed to testing. Have developers use each branch for developing in each environment.
B. Create an AWS CodeCommit repository for each project, and use the main branch for production and test code with different deployment pipelines for each environment Use feature branches to develop new features.
C. Create an AWS CodeCommit repository tor each project, use the mam branch for production code: and create a testing branch for code deployed to testing Use feature branches to develop new features and pull requests to merge code to testing and main branches.
D. Create another S3 bucket for each project for testing code, and use an AWS Lambda function to promote code changes between testing and production buckets Enable versioning on all buckets to prevent code conflicts.

Answer: C

Explanation:
Creating an AWS CodeCommit repository for each project, using the main branch for production code, and creating a testing branch for code deployed to testing will meet the requirements. AWS CodeCommit is a managed revision control service that hosts Git repositories and works with all Git-based tools1. By using feature branches to develop new features and pull requests to merge code to testing and main branches, the developers can avoid code conflicts and lost work, and also implement code reviews and approvals. Option B is incorrect because creating another S3 bucket for each project for testing code and using an AWS Lambda function to promote code changes between testing and production buckets will not provide the benefits of revision control, such as tracking changes, branching, merging, and collaborating. Option C is incorrect because using the main branch for production and test code with different deployment pipelines for each environment will not allow the developers to test their code changes before deploying them to production. Option D is incorrect because enabling versioning and branching on each S3 bucket will not work with Git-based tools and will not provide the same level of revision control as AWS CodeCommit. Reference:
AWS CodeCommit
Certified DevOps Engineer - Professional (DOP-C02) Study Guide (page 182)

NEW QUESTION # 295
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