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| Section | Weight | Objectives |
|---|
| Topic 1: Policies and Standards Automation | 10% | - Design and implement governance strategies
- 1. Implement tagging policies and resource grouping
- 2. Design cost optimization through policies
- 3. Implement approval workflows and automation
- Design and implement preventive and detective controls
- 1. Implement AWS Organizations and SCPs
- 2. Design and implement security baselines
- 3. Implement drift detection and remediation
|
| Topic 2: 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. Implement automated incident response
- 2. Design runbook automation
- 3. Create alarm notification strategies
|
| Topic 3: High Availability and Disaster Recovery | 16% | - Design and implement high availability and scalability
- 1. Implement load balancing and traffic management
- 2. Implement auto scaling strategies
- 3. Design multi-AZ and multi-region architectures
- Design and implement disaster recovery strategies
- 1. Implement multi-region active-active architectures
- 2. Implement backup and restore mechanisms
- 3. Implement pilot light and warm standby architectures
- 4. Design RTO and RPO based DR solutions
- Implement data backup and restore strategies
- 1. Implement cross-region replication
- 2. Design point-in-time recovery solutions
- 3. Implement validation testing for backups
|
| Topic 4: SDLC Automation | 22% | - Design and implement CI/CD pipelines
- 1. Determine appropriate CI/CD pipeline architecture
- 2. Design failure handling strategies
- 3. Develop CI/CD pipelines considering testing and security requirements
- 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
- Design build and test environments
- 1. Implement build environments (isolated, reproducible)
- 2. Design test automation frameworks
- 3. Integrate security scanning and compliance checks
|
| Topic 5: Incident and Event Response | 18% | - 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
- Design and implement event and incident management
- 1. Implement automated incident detection
- 2. Implement automated response playbooks
- 3. Design event aggregation and correlation
|
| Topic 6: Configuration Management and Infrastructure as Code | 22% | - 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. Implement database migration strategies
- 2. Design backup and recovery solutions
- 3. Implement data lifecycle management
- 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 infrastructure as code
- 1. Design for scalability and repeatability
- 2. Implement modular and reusable infrastructure components
- 3. Develop IaC templates (AWS CloudFormation, Terraform)
|
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Amazon AWS Certified DevOps Engineer - Professional Sample Questions (Q169-Q174):
NEW QUESTION # 169
A company has a stateless web application that is deployed on Amazon EC2 instances. The EC2 instances are in a target group behind an Application Load Balancer (ALB). Amazon Route 53 manages the application domain.
The company updates the application UI and develops a beta version of the application. The company wants to test the beta version on 10% of its traffic.
Which solution will meet these requirements with the LEAST number of configuration changes?
- A. Containerize and deploy the application on Amazon Elastic Container Service (Amazon ECS). Use AWS CodeDeploy to deploy the beta version by using the CodeDeployDefault.ECSCanary10Percent15Minutes deployment configuration.
- B. Refactor the application to implement a feature flag for the beta version by using AWS AppConfig. Use the feature flag to enable the beta version for 10% of the EC2 instances.
- C. Deploy the beta version to new EC2 instances in a new target group. Associate the new target group with the same ALB listener rule. Assign a weight of 90 to the existing target group. Assign a weight of
10 to the new target group. - D. Deploy the beta version to new EC2 instances in a new target group. Associate the new target group with a new ALB. Update the existing Route 53 record to use a weighted routing policy. Add a new Route 53 record that points to the new ALB with the same routing policy. Assign a weight of 90 to the existing record. Assign a weight of 10 to the new record.
Answer: C
Explanation:
Comprehensive and Detailed Explanation From Exact Extract of DevOps Engineer Documents Only:
ALB supports weighted target groups for traffic splitting between versions without DNS-level changes. By attaching multiple target groups (old & beta) to the same ALB listener rule with weights (90/10), partial traffic testing can occur seamlessly. This is the recommended least-change method per Application Load Balancer advanced request routing documentation.
NEW QUESTION # 170
A developer is using the AWS Serverless Application Model (AWS SAM) to create a prototype for an AWS Lambda function. The AWS SAM template contains an AWS::Serverless::Function resource that has the CodeUri property pointing to an Amazon S3 location. The developer wants to identify the correct commands for deployment before creating a CI/CD pipeline.
The developer creates an archive of the Lambda function code named package.zip, uploads the .zip file archive to the S3 location specified in the CodeUri property, and runs the sam deploy command to deploy the Lambda function. The developer updates the Lambda function code and uses the same steps to deploy the new version. The sam deploy command fails and returns an error of " no changes to deploy. " Which solutions will deploy the new version? (Select TWO.)
- A. Update the CodeUri property to reference the local application code folder. Use the aws cloudformation package command and the aws cloudformation deploy command.
- B. Use the aws cloudformation update-stack-instances command instead of the sam deploy command.
- C. Update the CodeUri property to reference the local application code folder. Use the aws cloudformation create-change-set command and the aws cloudformation execute-change-set command.
- D. Update the CodeUri property to reference the local application code folder. Use the sam deploy command.
- E. Use the aws cloudformation update-stack command instead of the sam deploy command.
Answer: A,D
Explanation:
When the CodeUri property points directly to a static S3 object path, AWS CloudFormation detects no template changes between deployments because the S3 URI remains identical even after you upload updated code to the same key. The solution is to reference local source code so that SAM or CloudFormation can compute a content hash, upload the artifact with a unique S3 key, and update the template, creating a detectable change. Option C works because sam deploy with a local CodeUri path automatically packages the function, uploads it to S3 with a hash-derived key, and deploys the updated stack. Option E works for the same reason: aws cloudformation package computes the hash, uploads the artifact, and produces a packaged template that aws cloudformation deploy can then apply. Options A and B do not resolve the root cause and are not designed for SAM Lambda packaging.
NEW QUESTION # 171
A DevOps team deploys an ECS app behind an ALB using CodeDeploy with all-at-once strategy. Recent deployment increased response times, requiring rollback. The team wants a deployment strategy to monitor new versions before full traffic shift and rollback quickly if issues occur.
Which steps meet these requirements? (Select TWO.)
- A. Create a CloudWatch alarm on ALB UnHealthyHostCount and associate it with the deployment group for rollback.
- B. Use CodeDeployDefault.ECSLinear10PercentEvery3Minutes deployment configuration.
- C. Use CodeDeployDefault.ECSCanary10Percent5Minutes deployment configuration.
- D. Create a CloudWatch alarm on ALB TargetResponseTime and associate it with the deployment group for rollback.
- E. Create a CloudWatch alarm on ALB TargetConnectionErrorCount and associate it with the deployment group for rollback.
Answer: C,D
Explanation:
* Canary deploymentsgradually shift traffic (10% at first), enabling monitoring before full rollout.
* MonitoringTargetResponseTimealigns with detecting increased latency, a key issue reported.
* Alarms tied to the deployment group trigger automatic rollback on threshold breach.
* UnHealthyHostCount and TargetConnectionErrorCount are less specific to response time issues.
* Linear deployment is valid but canary is preferred for quick detection.
References:
CodeDeploy Deployment Configurations
Automatic Rollback with CloudWatch Alarms
NEW QUESTION # 172
A company is adopting AWS CodeDeploy to automate its application deployments for a Java-Apache Tomcat application with an Apache Webserver. The development team started with a proof of concept, created a deployment group for a developer environment, and performed functional tests within the application. After completion, the team will create additional deployment groups for staging and production.
The current log level is configured within the Apache settings, but the team wants to change this configuration dynamically when the deployment occurs, so that they can set different log level configurations depending on the deployment group without having a different application revision for each group.
How can these requirements be met with the LEAST management overhead and without requiring different script versions for each deployment group?
- A. Create a CodeDeploy custom environment variable for each environment. Then place a script into the application revision that checks this environment variable to identify which deployment group the instance is part of. Use this information to configure the log level settings. Reference this script as part of the ValidateService lifecycle hook in the appspec.yml file.
- B. Create a script that uses the CodeDeploy environment variable DEPLOYMENT_GROUP_ID to identify which deployment group the instance is part of to configure the log level settings. Reference this script as part of the Install lifecycle hook in the appspec.yml file.
- C. Create a script that uses the CodeDeploy environment variable DEPLOYMENT_GROUP_ NAME to identify which deployment group the instance is part of. Use this information to configure the log level settings. Reference this script as part of the BeforeInstall lifecycle hook in the appspec.yml file.
- D. Tag the Amazon EC2 instances depending on the deployment group. Then place a script into the application revision that calls the metadata service and the EC2 API to identify which deployment group the instance is part of. Use this information to configure the log level settings. Reference the script as part of the AfterInstall lifecycle hook in the appspec.yml file.
Answer: C
Explanation:
Explanation
The following are the steps that the company can take to change the log level dynamically when the deployment occurs:
Create a script that uses the CodeDeploy environment variable DEPLOYMENT_GROUP_NAME to identify which deployment group the instance is part of.
Use this information to configure the log level settings.
Reference this script as part of the BeforeInstall lifecycle hook in the appspec.yml file.
The DEPLOYMENT_GROUP_NAME environment variable is automatically set by CodeDeploy when the deployment is triggered. This means that the script does not need to call the metadata service or the EC2 API to identify the deployment group.
This solution is the least complex and requires the least management overhead. It also does not require different script versions for each deployment group.
The following are the reasons why the other options are not correct:
Option A is incorrect because it would require tagging the Amazon EC2 instances, which would be a manual and time-consuming process.
Option C is incorrect because it would require creating a custom environment variable for each environment. This would be a complex and error-prone process.
Option D is incorrect because it would use the DEPLOYMENT_GROUP_ID environment variable.
However, this variable is not automatically set by CodeDeploy, so the script would need to call the metadata service or the EC2 API to get the deployment group ID. This would add complexity and overhead to the solution.
NEW QUESTION # 173
A DevOps engineer needs to install antivirus software on all Amazon EC2 instances in an AWS account. The EC2 instances run the most recent Amazon Linux version. The solution must detect all instances and use an AWS Systems Manager document to install the software if missing.
Which solution will meet these requirements?
- A. Create an association in Systems Manager State Manager targeting all managed nodes. Include the software and Systems Manager document.
- B. Use Amazon Inspector to detect missing software and associate with Systems Manager automation.
- C. Use EventBridge to detect EC2 RunInstances events and trigger SSM automation.
- D. Use AWS Config with a custom rule to check for antivirus installation. Configure automatic remediation using the Systems Manager document.
Answer: D
Explanation:
AWS Config can monitor compliance by checking EC2 software inventory. Custom Config rules can automatically trigger Systems Manager Automation documents as remediation actions when noncompliant (software missing). This meets policy enforcement goals with automation.
NEW QUESTION # 174
......
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