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Amazon DOP-C02 Exam Syllabus Topics:

Section	Weight	Objectives
Incident and Event Response	14%	- Manage incidents and outages 1. Coordinate response and recovery 2. Troubleshoot complex issues 3. Document and learn from events - Automate event management 1. Classify and prioritize events 2. Integrate with ticketing and workflow systems 3. Automate common operational tasks - Improve operational processes 1. Update runbooks and playbooks 2. Optimize response time and efficiency 3. Implement feedback loops
Configuration Management and Infrastructure as Code	17%	- Implement infrastructure as code 1. Enforce configuration standards 2. Manage templates and stacks 3. Use AWS CloudFormation, Terraform, or AWS CDK - Automate configuration management 1. Detect and remediate configuration drift 2. Maintain consistent configurations 3. Use AWS Systems Manager, Ansible, or Puppet - Manage infrastructure deployments 1. Implement version control for configurations 2. Provision and update resources automatically 3. Manage multi-account and multi-region environments
Resilient Cloud Solutions	15%	- Implement disaster recovery 1. Pilot light, warm standby, and active-active 2. Test and validate recovery plans 3. Backup and restore strategies - Design high availability architectures 1. Use Route 53 for routing and failover 2. Implement auto scaling and load balancing 3. Multi-AZ and multi-region deployments - Ensure reliability and scalability 1. Manage capacity and elasticity 2. Design for fault tolerance 3. Optimize performance and cost
Monitoring and Logging	15%	- Implement monitoring solutions 1. Create dashboards and insights 2. Monitor infrastructure, applications, and costs 3. Use Amazon CloudWatch for metrics and alarms - Automate incident response 1. Automate remediation and scaling 2. Set up event-driven actions with Amazon EventBridge 3. Implement alerting and notification workflows - Implement logging and analysis 1. Analyze logs for troubleshooting and security 2. Use AWS X-Ray for tracing 3. Centralize logs with CloudWatch Logs
Security, Governance, and Compliance	17%	- Automate security and compliance 1. Use AWS Security Hub and AWS Shield 2. Integrate security into CI/CD pipelines 3. Detect and remediate violations automatically - Implement security controls 1. Encrypt data at rest and in transit 2. Secure secrets and credentials 3. Manage IAM for pipelines and environments - Enforce governance and compliance 1. Use AWS Config and AWS Organizations 2. Implement compliance rules and audits 3. Manage access and permissions at scale
SDLC Automation	22%	- Automate software release processes 1. Automate rollback procedures 2. Manage artifacts and dependencies 3. Implement deployment strategies - Implement CI/CD pipelines 1. Use AWS CodePipeline, CodeBuild, CodeDeploy 2. Automate build, test, and deployment stages 3. Integrate version control systems - Automate testing and validation 1. Automate quality gates 2. Security and compliance testing 3. Unit, integration, and performance testing

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Amazon AWS Certified DevOps Engineer - Professional Sample Questions (Q144-Q149):

NEW QUESTION # 144
A company has a file-reading application that saves files to a database running on Amazon EC2 instances. Regulations require daily file deletions from EC2 instances and deletion of database records older than 60 days. Database record deletion must occur after file deletion. The company needs email notifications for any deletion script failures.
Which solution will meet these requirements with the LEAST development effort?

A. Create an EventBridge rule to invoke a Lambda function at the specified time. Configure the Lambda function to run deletion scripts sequentially and send failure notifications via SES.
B. Use AWS Systems Manager State Manager to automatically invoke an Automation document at the specified time daily. Configure the Automation document to run deletion scripts sequentially via run command. Create an EventBridge rule to send failure notifications to Amazon SNS.
C. Create an EventBridge rule to invoke a Lambda function at the specified time. Configure the Lambda function to run deletion scripts sequentially and send failure notifications via SNS.
D. Use AWS Systems Manager State Manager to automatically invoke an Automation document at the specified time daily. Configure the Automation document to run deletion scripts sequentially. Add a conditional check for errors as the last step and send failure notifications via Amazon SES.

Answer: B

Explanation:
Systems Manager State Manager with Automation documents allows running scripts sequentially and reliably with built-in retry and status tracking.
Using EventBridge with SNS for notifications leverages managed services with minimal custom development.
Using SES (Options B, D) requires more setup and custom logic for email formatting and sending.
Lambda (Options C, D) can run scripts but might have limitations on execution time and complexity compared to Systems Manager Automation.
References:
AWS Systems Manager Automation
Monitoring Automation Execution and Notifications

NEW QUESTION # 145
A company uses the AWS Cloud Development Kit (AWS CDK) to define its application. The company uses a pipeline that consists of AWS CodePipeline and AWS CodeBuild to deploy the CDK application. The company wants to introduce unit tests to the pipeline to test various infrastructure components. The company wants to ensure that a deployment proceeds if no unit tests result in a failure.
Which combination of steps will enforce the testing requirement in the pipeline? (Select TWO.)

A. Create a test that uses the AWS CDK assertions module. Use the template.hasResourceProperties assertion to test that resources have the expected properties.
B. Create a test that uses the cdk diff command. Configure the test to fail if any resources have changed.
C. Update the CodeBuild build phase commands to run the tests then to deploy the application. Add the -- rollback true flag to the cdk deploy command.
D. Update the CodeBuild build phase commands to run the tests then to deploy the application. Set the OnFailure phase property to ABORT.
E. Update the CodeBuild build phase commands to run the tests then to deploy the application. Add the -- require-approval any-change flag to the cdk deploy command.

Answer: A,D

Explanation:
Comprehensive and Detailed Explanation From Exact Extract of DevOps Engineer Documents Only:
To validate AWS CDK-defined infrastructure, use CDK Assertions (assertions module) to test synthesized CloudFormation templates (e.g., template.hasResourceProperties). Integrate testing into CodeBuild buildspec before deployment, setting OnFailure: ABORT so the pipeline halts if tests fail. This ensures safe continuous delivery following AWS CDK testing best practices.

NEW QUESTION # 146
A DevOps engineer maintains a web application that is deployed on an Amazon Elastic Container Service (Amazon ECS) service behind an Application Load Balancer (ALB).
Recent updates to the service caused downtime for the application because of issues with the application code. The DevOps engineer needs to design a solution to test updates on a small amount of traffic first before deploying to the rest of the service.
Which solution will meet these requirements?

A. Create a new AWS CodeBuild project. Connect the project to an AWS CodeConnections compatible Git repository. Create a buildspec.yml file in the Git repository that contains commands to call the Amazon ECS UpdateService API. Set a slow start duration of 2 minutes on the ALB target group.
B. Create a new pipeline in AWS CodePipeline. Connect the pipeline to an AWS CodeConnections compatible Git repository. Configure the pipeline with an ECRBuildAndPublish action and an Amazon ECS standard deployment action. Configure the ECS service to use the rolling update deployment type.
C. Create a new AWS CodeBuild project that uses AWS Lambda compute and that includes an IAM role that has permissions to update the ECS task definition. Update the project buildspec file to call the Amazon ECS RegisterTaskDefinition API for deployments. Configure the ECS service to use the rolling update deployment type.
D. Update the ECS service to use AWS CodeDeploy as the deployment controller. Create a second target group for the ALB. Create a CodeDeploy application and deployment group for the application. Use CodeDeploy to deploy updates by using the CodeDeployDefault.ECSCanary10Percent15Minutes deployment configuration.

Answer: D

Explanation:
The key requirement is to shift a small percentage of traffic to a new version first to validate changes before rolling out to the entire ECS service, thereby reducing downtime and deployment risk. For ECS services behind an Application Load Balancer, the AWS-recommended and most reliable approach is to use AWS CodeDeploy with blue/green or canary deployments.
Option B directly addresses this requirement. By configuring the ECS service to use CodeDeploy as the deployment controller, CodeDeploy can manage traffic shifting between two ALB target groups: one for the current (stable) version and one for the new version. The CodeDeployDefault.ECSCanary10Percent15Minutes deployment configuration initially routes 10% of production traffic to the new task set, monitors the deployment for issues, and then shifts the remaining traffic after the defined interval. This enables early detection of application errors while limiting user impact.
Option A and C rely on rolling updates, which replace tasks incrementally but do not provide precise traffic control or automated rollback based on health checks. Option D's slow start setting only affects how quickly targets receive traffic after registration and does not implement true canary testing.
Therefore, using AWS CodeDeploy with ECS canary deployments is the most robust, AWS-supported solution to test changes safely before full rollout.

NEW QUESTION # 147
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. 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.
B. 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.
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: A

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.
1: Amazon S3 Features | Object Lambda | AWS 2: Transforming objects with S3 Object Lambda - Amazon Simple Storage Service

NEW QUESTION # 148
A company runs a data processing pipeline on AWS every day. The pipeline downloads data from an Amazon S3 bucket to Amazon EC2 instances. The company runs a batch analysis process on the downloaded data by manually running a custom Python script. The batch process usually takes 10 to 30 minutes to complete the analysis.
A DevOps engineer wants to modernize the data processing pipeline. The DevOps engineer needs to set up a new event-driven pipeline that sends notifications to company management when the batch process is finished.
Which solution will meet these requirements with the LEAST operational overhead?

A. Run the custom Python script on an EC2 instance when a new file is uploaded to the S3 bucket. Use Amazon EventBridge and Amazon Simple Notification Service (Amazon SNS) to build an automated workflow that sends notifications to company management when the Python script finishes running.
B. Invoke a Python shell job in AWS Glue to run the custom Python script in response to an Amazon EventBridge rule when a new file is uploaded to the S3 bucket. Use EventBridge and Amazon Simple Notification Service (Amazon SNS) to build an automated workflow that sends notifications to company management when the AWS Glue job finishes running.
C. Invoke an AWS Lambda function by using AWS Step Functions with a retry mechanism that is based on an S3 event notification when a new file is uploaded to the S3 bucket. Use Amazon EventBridge and Amazon Simple Notification Service (Amazon SNS) to build an automated workflow that sends notifications to company management when the Lambda function finishes running.
D. Run the custom Python script on an EC2 instance by creating a new custom API that points to the Python script. Use Amazon EventBridge and Amazon Simple Notification Service (Amazon SNS) to build an automated workflow that sends notifications to company management when the Python script finishes running.

Answer: B

Explanation:
AWS Glue Python shell jobs are made to run Python scripts without managing EC2 instances, which directly fits the existing custom Python batch script. AWS documents that Python shell jobs run Python scripts in AWS Glue, and Glue integrates with EventBridge for automation and job state changes. This creates an event- driven serverless workflow: an S3 object event starts the Glue job, Glue emits a completion event, and EventBridge routes the event to SNS for management notification. Option C is unsafe because the batch process can take up to 30 minutes, while a standard Lambda invocation has a 15-minute maximum timeout.
Options B and D keep EC2 in the design, which adds patching, scaling, instance availability, and operational overhead.

NEW QUESTION # 149
......

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