DOP-C02受験方法 & DOP-C02資格練習

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Amazon DOP-C02 Exam Syllabus Topics:

SectionWeightObjectives
Configuration Management and Infrastructure as Code17%- Implement infrastructure as code
  • 1. Manage templates and stacks
  • 2. Enforce configuration standards
  • 3. Use AWS CloudFormation, Terraform, or AWS CDK
- Manage infrastructure deployments
  • 1. Manage multi-account and multi-region environments
  • 2. Implement version control for configurations
  • 3. Provision and update resources automatically
- Automate configuration management
  • 1. Use AWS Systems Manager, Ansible, or Puppet
  • 2. Detect and remediate configuration drift
  • 3. Maintain consistent configurations
SDLC Automation22%- Automate software release processes
  • 1. Automate rollback procedures
  • 2. Manage artifacts and dependencies
  • 3. Implement deployment strategies
- Implement CI/CD pipelines
  • 1. Integrate version control systems
  • 2. Use AWS CodePipeline, CodeBuild, CodeDeploy
  • 3. Automate build, test, and deployment stages
- Automate testing and validation
  • 1. Automate quality gates
  • 2. Unit, integration, and performance testing
  • 3. Security and compliance testing
Monitoring and Logging15%- Implement monitoring solutions
  • 1. Use Amazon CloudWatch for metrics and alarms
  • 2. Monitor infrastructure, applications, and costs
  • 3. Create dashboards and insights
- Implement logging and analysis
  • 1. Analyze logs for troubleshooting and security
  • 2. Use AWS X-Ray for tracing
  • 3. Centralize logs with CloudWatch Logs
- Automate incident response
  • 1. Implement alerting and notification workflows
  • 2. Set up event-driven actions with Amazon EventBridge
  • 3. Automate remediation and scaling
Incident and Event Response14%- Manage incidents and outages
  • 1. Troubleshoot complex issues
  • 2. Document and learn from events
  • 3. Coordinate response and recovery
- Automate event management
  • 1. Automate common operational tasks
  • 2. Integrate with ticketing and workflow systems
  • 3. Classify and prioritize events
- Improve operational processes
  • 1. Update runbooks and playbooks
  • 2. Implement feedback loops
  • 3. Optimize response time and efficiency
Security, Governance, and Compliance17%- Automate security and compliance
  • 1. Use AWS Security Hub and AWS Shield
  • 2. Detect and remediate violations automatically
  • 3. Integrate security into CI/CD pipelines
- Enforce governance and compliance
  • 1. Manage access and permissions at scale
  • 2. Use AWS Config and AWS Organizations
  • 3. Implement compliance rules and audits
- Implement security controls
  • 1. Secure secrets and credentials
  • 2. Manage IAM for pipelines and environments
  • 3. Encrypt data at rest and in transit
Resilient Cloud Solutions15%- Design high availability architectures
  • 1. Multi-AZ and multi-region deployments
  • 2. Use Route 53 for routing and failover
  • 3. Implement auto scaling and load balancing
- Ensure reliability and scalability
  • 1. Optimize performance and cost
  • 2. Manage capacity and elasticity
  • 3. Design for fault tolerance
- Implement disaster recovery
  • 1. Test and validate recovery plans
  • 2. Backup and restore strategies
  • 3. Pilot light, warm standby, and active-active

>> DOP-C02受験方法 <<

Amazon DOP-C02資格練習 & DOP-C02前提条件

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Amazon AWS Certified DevOps Engineer - Professional 認定 DOP-C02 試験問題 (Q450-Q455):

質問 # 450
An application runs on Amazon EC2 instances behind an Application Load Balancer (ALB). A DevOps engineer is using AWS CodeDeploy to release a new version. The deployment fails during the AlIowTraffic lifecycle event, but a cause for the failure is not indicated in the deployment logs.
What would cause this?

正解：B

解説：
Explanation
This failure is typically due to incorrectly configured health checks in Elastic Load Balancing for the Classic Load Balancer, Application Load Balancer, or Network Load Balancer used to manage traffic for the deployment group. To resolve the issue, review and correct any errors in the health check configuration for the load balancer.
https://docs.aws.amazon.com/codedeploy/latest/userguide/troubleshooting-deployments.html#troubleshooting-de


質問 # 451
A company is using AWS CodeDeploy to deploy applications to a fleet of Amazon EC2 instances. During a recent deployment, several EC2 instances failed to update successfully. A DevOps engineer must investigate the root cause of the failures and must determine which specific deployment lifecycle events encountered errors.
What is the MOST operationally efficient way to access and analyze the detailed deployment logs for troubleshooting?

正解：C

解説：
AWS recommends centralizing CodeDeploy agent logs in Amazon CloudWatch Logs for efficient analysis.
By configuring the CloudWatch agent or using the CodeDeploy console integration, you can stream logs in near-real time and query them with CloudWatch Logs Insights. This enables filtering by deployment lifecycle events, saving time versus manually connecting to instances. Refer to AWS documentation section
"Monitoring and troubleshooting deployments with CodeDeploy and CloudWatch."


質問 # 452
A DevOps engineer needs to configure a blue green deployment for an existing three-tier application. The application runs on Amazon EC2 instances and uses an Amazon RDS database The EC2 instances run behind an Application Load Balancer (ALB) and are in an Auto Scaling group.
The DevOps engineer has created a launch template and an Auto Scaling group for the blue environment. The DevOps engineer also has created a launch template and an Auto Scaling group for the green environment. Each Auto Scaling group deploys to a matching blue or green target group. The target group also specifies which software blue or green gets loaded on the EC2 instances. The ALB can be configured to send traffic to the blue environments target group or the green environments target group. An Amazon Route 53 record for www example com points to the ALB.
The deployment must move traffic all at once between the software on the blue environment's EC2 instances to the newly deployed software on the green environments EC2 instances What should the DevOps engineer do to meet these requirements?

正解：A

解説：
This solution will meet the requirements because it will use a rolling restart to gradually replace the EC2 instances in the green environment with new instances that have the new software version installed. A rolling restart is a process that terminates and launches instances in batches, ensuring that there is always a minimum number of healthy instances in service. This way, the green environment can be updated without affecting the availability or performance of the application. When the rolling restart is complete, the DevOps engineer can use an AWS CLI command to modify the listener rules of the ALB and change the default action to forward traffic to the green environment's target group. This will switch the traffic from the blue environment to the green environment all at once, as required by the question.


質問 # 453
A company used a lift-and-shift strategy to migrate a workload to AWS. The company has an Auto Scaling group of Amazon EC2 instances. Each EC2 instance runs a web application, a database, and a Redis cache.
Users are experiencing large variations in the web application's response times. Requests to the web application go to a single EC2 instance that is under significant load. The company wants to separate the application components to improve availability and performance.
Which solution will meet these requirements?

正解：D

解説：
The current design colocates the web tier, database, and cache on the same EC2 instances. This causes resource contention and makes it difficult to scale each layer independently. The correct solution is to separate these concerns into independently scalable managed services.
Option D uses an Application Load Balancer (ALB) in front of an Auto Scaling group for the web application. ALB is designed for HTTP/HTTPS traffic, supports path-based and host-based routing, and can spread load evenly across multiple instances and Availability Zones, eliminating the issue where one instance is overloaded.
The database is migrated to Amazon Aurora with Multi-AZ, which provides high availability, automated failover, and managed backups. Aurora offloads database management and ensures consistent performance.
For caching, Option D introduces Amazon ElastiCache for Redis, a managed in-memory cache that is purpose-built for low-latency reads, independent scaling, and high availability through replication and clustering.
Option A and C misuse NLB for HTTP traffic or for Redis exposure and introduce unnecessary complexity. Option B keeps Redis on EC2 (via NLB + ASG in a single AZ), which reduces availability and does not leverage managed caching.
Thus, Option D best separates tiers and improves performance and availability.


質問 # 454
A company's DevOps engineer is creating an AWS Lambda function to process notifications from an Amazon Simple Notification Service (Amazon SNS) topic. The Lambda function will process the notification messages and will write the contents of the notification messages to an Amazon RDS Multi-AZ DB instance.
During testing a database administrator accidentally shut down the DB instance. While the database was down the company lost several of the SNS notification messages that were delivered during that time.
The DevOps engineer needs to prevent the loss of notification messages in the future Which solutions will meet this requirement? (Select TWO.)

正解：C、D

解説：
These solutions will meet the requirement because they will prevent the loss of notification messages in the future. An Amazon SQS queue is a service that provides a reliable, scalable, and secure message queue for asynchronous communication between distributed components. You can use an SQS queue to buffer messages from an SNS topic and ensure that they are delivered and processed by a Lambda function, even if the function or the database is temporarily unavailable.
Option C will configure an SQS dead-letter queue for the SNS topic. A dead-letter queue is a queue that receives messages that could not be delivered to any subscriber after a specified number of retries. You can use a dead-letter queue to store and analyze failed messages, or to reprocess them later. This way, you can avoid losing messages that could not be delivered to the Lambda function due to network errors, throttling, or other issues.
Option D will subscribe an SQS queue to the SNS topic and configure the Lambda function to process messages from the SQS queue. This will decouple the SNS topic from the Lambda function and provide more flexibility and control over the message delivery and processing. You can use an SQS queue to store messages from the SNS topic until they are ready to be processed by the Lambda function, and also to retry processing in case of failures. This way, you can avoid losing messages that could not be processed by the Lambda function due to database errors, timeouts, or other issues.


質問 # 455
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