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Amazon DOP-C02 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Monitoring and Logging12%- Design and implement alerting and incident management
  • 1. Design runbook automation
  • 2. Implement automated incident response
  • 3. Create alarm notification strategies
- Design and implement monitoring and observability strategies
  • 1. Implement log aggregation and analysis
  • 2. Design custom metrics and alarms (Amazon CloudWatch)
  • 3. Implement distributed tracing (AWS X-Ray)
Topic 2: Configuration Management and Infrastructure as Code22%- 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. Implement AWS CloudTrail for auditing
  • 2. Use AWS Config for compliance monitoring
  • 3. Design remediation automation
- 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 data management strategies
  • 1. Implement database migration strategies
  • 2. Implement data lifecycle management
  • 3. Design backup and recovery solutions
Topic 3: SDLC Automation22%- Design and implement CI/CD pipelines
  • 1. Design failure handling strategies
  • 2. Implement deployment strategies (blue-green, canary, rolling)
  • 3. Determine appropriate CI/CD pipeline architecture
  • 4. Develop CI/CD pipelines considering testing and security requirements
- Design and implement source code management strategies
  • 1. Design code review and approval processes
  • 2. Implement repository configurations and hooks
  • 3. Determine branching strategies
- Design build and test environments
  • 1. Implement build environments (isolated, reproducible)
  • 2. Integrate security scanning and compliance checks
  • 3. Design test automation frameworks
Topic 4: Incident and Event Response18%- 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. Implement fault injection experiments (AWS Fault Injection Simulator)
  • 2. Analyze system behavior under failure conditions
  • 3. Design resilience testing strategies
Topic 5: Policies and Standards Automation10%- Design and implement governance strategies
  • 1. Implement approval workflows and automation
  • 2. Design cost optimization through policies
  • 3. Implement tagging policies and resource grouping
- Design and implement preventive and detective controls
  • 1. Implement drift detection and remediation
  • 2. Implement AWS Organizations and SCPs
  • 3. Design and implement security baselines
Topic 6: High Availability and Disaster Recovery16%- Design and implement disaster recovery strategies
  • 1. Design RTO and RPO based DR solutions
  • 2. Implement multi-region active-active architectures
  • 3. Implement backup and restore mechanisms
  • 4. Implement pilot light and warm standby architectures
- 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
- Implement data backup and restore strategies
  • 1. Implement cross-region replication
  • 2. Design point-in-time recovery solutions
  • 3. Implement validation testing for backups

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Amazon AWS Certified DevOps Engineer - Professional Sample Questions (Q425-Q430):

NEW QUESTION # 425
A company has an application that runs on AWS Lambda and sends logs to Amazon CloudWatch Logs. An Amazon Kinesis data stream is subscribed to the log groups in CloudWatch Logs. A single consumer Lambda function processes the logs from the data stream and stores the logs in an Amazon S3 bucket.
The company's DevOps team has noticed high latency during the processing and ingestion of some logs.
Which combination of steps will reduce the latency? (Select THREE.)

Answer: A,B,D

Explanation:
The latency in processing and ingesting logs can be caused by several factors, such as the throughput of the Kinesis data stream, the concurrency of the Lambda function, and the configuration of the event source mapping. To reduce the latency, the following steps can be taken:
Create a data stream consumer with enhanced fan-out. Set the Lambda function that processes the logs as the consumer. This will allow the Lambda function to receive records from the data stream with dedicated throughput of up to 2 MB per second per shard, independent of other consumers1. This will reduce the contention and delay in accessing the data stream.
Increase the ParallelizationFactor setting in the Lambda event source mapping. This will allow the Lambda service to invoke more instances of the function concurrently to process the records from the data stream2. This will increase the processing capacity and reduce the backlog of records in the data stream.
Configure reserved concurrency for the Lambda function that processes the logs. This will ensure that the function has enough concurrency available to handle the increased load from the data stream3. This will prevent the function from being throttled by the account-level concurrency limit.
The other options are not effective or may have negative impacts on the latency. Option D is not suitable because increasing the batch size in the Kinesis data stream will increase the amount of data that the Lambda function has to process in each invocation, which may increase the execution time and latency4. Option E is not advisable because turning off the ReportBatchItemFailures setting in the Lambda event source mapping will prevent the Lambda service from retrying the failed records, which may result in data loss. Option F is not necessary because increasing the number of shards in the Kinesis data stream will increase the throughput of the data stream, but it will not affect the processing speed of the Lambda function, which is the bottleneck in this scenario.
Reference:
1: Using AWS Lambda with Amazon Kinesis Data Streams - AWS Lambda
2: AWS Lambda event source mappings - AWS Lambda
3: Managing concurrency for a Lambda function - AWS Lambda
4: AWS Lambda function scaling - AWS Lambda
5: AWS Lambda event source mappings - AWS Lambda
6: Scaling Amazon Kinesis Data Streams with AWS CloudFormation - Amazon Kinesis Data Streams


NEW QUESTION # 426
A company must encrypt all AMIs that the company shares across accounts. A DevOps engineer has access to a source account where an unencrypted custom AMI has been built. The DevOps engineer also has access to a target account where an Amazon EC2 Auto Scaling group will launch EC2 instances from the AMI. The DevOps engineer must share the AMI with the target account.
The company has created an AWS Key Management Service (AWS KMS) key in the source account.
Which additional steps should the DevOps engineer perform to meet the requirements? (Choose three.)

Answer: B,C,F


NEW QUESTION # 427
A company runs several applications in the same AWS account. The applications send logs to Amazon CloudWatch.
A data analytics team needs to collect performance metrics and custom metrics from the applications. The analytics team needs to transform the metrics data before storing the data in an Amazon S3 bucket. The analytics team must automatically collect any new metrics that are added to the CloudWatch namespace.
Which solution will meet these requirements with the LEAST operational overhead?

Answer: C

Explanation:
Amazon CloudWatch metric streams are designed to deliver metrics in near real time to downstream services like Amazon Data Firehose with minimal configuration and management overhead. By configuring a metric stream to include all metrics, you ensure that any newly created performance or custom metrics are automatically included without needing to update filters or code when namespaces or metrics change.
Option B uses a CloudWatch metric stream → Firehose → Lambda → S3 pattern. Firehose natively supports invoking a Lambda function for in-flight transformation of the metric data before final delivery to S3. This satisfies the requirement to transform metrics before storing them and provides a fully managed, serverless pipeline with very little ongoing operational burden.
Option A mentions including metrics from "the application and the CloudWatch namespace," which implies more manual selection and maintenance, potentially missing new metrics if not explicitly added. Options C and D work at the log level, not at the metric level, and would require building additional logic to derive metrics from logs. This is more complex and not aligned with "least operational overhead." Therefore, Option B is the most efficient and scalable solution.


NEW QUESTION # 428
A company has an AWS Control Tower landing zone. The company's DevOps team creates a workload OU. A development OU and a production OU are nested under the workload OU. The company grants users full access to the company's AWS accounts to deploy applications.
The DevOps team needs to allow only a specific management 1AM role to manage the 1AM roles and policies of any AWS accounts In only the production OU.
Which combination of steps will meet these requirements? {Select TWO.)

Answer: C,D

Explanation:
You need to understand how SCP inheritance works in AWS. The way it works for Deny policies is different that allow policies.
Allow polices are passing down to children ONLY if they don't have an allow policy.
Deny policies always pass down to children.
That's why there is always an SCP set to the Root to allow everything by default. If you limit this policy, the whole organization will be limited, not matter what other policies are saying for the other OUs. So it's not A. It's not D because it restricts the wrong OU.


NEW QUESTION # 429
A media company has several thousand Amazon EC2 instances in an AWS account. The company is using Slack and a shared email inbox for team communications and important updates. A DevOps engineer needs to send all AWS-scheduled EC2 maintenance notifications to the Slack channel and the shared inbox. The solution must include the instances' Name and Owner tags.
Which solution will meet these requirements?

Answer: B

Explanation:
https://docs.aws.amazon.com/health/latest/ug/cloudwatch-events-health.html


NEW QUESTION # 430
......

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