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Amazon DOP-C02 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: SDLC Automation22%- Design build and test environments
  • 1. Implement build environments (isolated, reproducible)
  • 2. Design test automation frameworks
  • 3. Integrate security scanning and compliance checks
- Design and implement CI/CD pipelines
  • 1. Implement deployment strategies (blue-green, canary, rolling)
  • 2. Determine appropriate CI/CD pipeline architecture
  • 3. Design failure handling strategies
  • 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. Determine branching strategies
  • 3. Implement repository configurations and hooks
Topic 2: Monitoring and Logging12%- Design and implement monitoring and observability strategies
  • 1. Implement distributed tracing (AWS X-Ray)
  • 2. Implement log aggregation and analysis
  • 3. Design custom metrics and alarms (Amazon CloudWatch)
- Design and implement alerting and incident management
  • 1. Implement automated incident response
  • 2. Create alarm notification strategies
  • 3. Design runbook automation
Topic 3: Configuration Management and Infrastructure as Code22%- Design and implement infrastructure as code
  • 1. Design for scalability and repeatability
  • 2. Develop IaC templates (AWS CloudFormation, Terraform)
  • 3. Implement modular and reusable infrastructure components
- Design and implement configuration management
  • 1. Implement parameter management (AWS Parameter Store, Secrets Manager)
  • 2. Design patch management strategies
  • 3. Implement AWS Systems Manager for configuration 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 data management strategies
  • 1. Design backup and recovery solutions
  • 2. Implement database migration strategies
  • 3. Implement data lifecycle management
Topic 4: Policies and Standards Automation10%- Design and implement governance strategies
  • 1. Design cost optimization through policies
  • 2. Implement tagging policies and resource grouping
  • 3. Implement approval workflows and automation
- Design and implement preventive and detective controls
  • 1. Design and implement security baselines
  • 2. Implement drift detection and remediation
  • 3. Implement AWS Organizations and SCPs
Topic 5: High Availability and Disaster Recovery16%- 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. Design RTO and RPO based DR solutions
  • 3. Implement backup and restore mechanisms
  • 4. Implement pilot light and warm standby architectures
- Implement data backup and restore strategies
  • 1. Implement validation testing for backups
  • 2. Implement cross-region replication
  • 3. Design point-in-time recovery solutions
Topic 6: Incident and Event Response18%- Design and implement event and incident management
  • 1. Implement automated incident detection
  • 2. Design event aggregation and correlation
  • 3. Implement automated response playbooks
- 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

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Amazon AWS Certified DevOps Engineer - Professional Sample Questions (Q218-Q223):

NEW QUESTION # 218
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,C,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
: AWS Lambda event source mappings - AWS Lambda
: Scaling Amazon Kinesis Data Streams with AWS CloudFormation - Amazon Kinesis Data Streams


NEW QUESTION # 219
A DevOps team incorporates automatic load and stress testing capabilities into a CI/CD pipeline by using AWS CodeBuild. The DevOps team uses an Amazon Aurora MySQL DB cluster in a testing environment to perform load testing. The DevOps team set the minimum capacity for the testing DB cluster to 1. The DevOps team uses 10 DB clusters in a production environment. The DevOps team has set all the DB clusters to automatically scale up to a maximum capacity of 15 Aurora Replicas.
When the DevOps team performs load testing, the configuration of the Aurora DB cluster in the testing environment prevents the cluster from scaling rapidly enough to meet the transient demand, which causes load testing to fail.
The DevOps team must configure the DB cluster in the testing environment to meet the load-testing demand.
Which solution will meet this requirement MOST cost-effectively?

Answer: B

Explanation:
The failure occurs because the test Aurora cluster starts with too little minimum replica capacity and cannot scale out fast enough for short-lived load testing. Aurora Auto Scaling uses minimum and maximum capacity values for the DB cluster, and scale-out and scale-in behavior is controlled by cooldown behavior. Raising the minimum capacity before the load test pre-warms the cluster with enough Aurora Replicas to absorb the transient load. Resetting the minimum back to 1 in POST_BUILD keeps the solution cost-effective after testing finishes. Option A does not reset capacity and changes scale-in behavior rather than fixing pre-test scale-out lag. Option C changes capacity after the test, which is too late. RDS Proxy manages connections, not Aurora replica scale-out capacity.


NEW QUESTION # 220
A company requires an RPO of 2 hours and an RTO of 10 minutes for its data and application at all times. An application uses a MySQL database and Amazon EC2 web servers. The development team needs a strategy for failover and disaster recovery.
Which combination of deployment strategies will meet these requirements? (Select TWO.)

Answer: B,C


NEW QUESTION # 221
A company has started using AWS across several teams. Each team has multiple accounts and unique security profiles. The company manages the accounts in an organization in AWS Organizations. Each account has its own configuration and security controls.
The company ' s DevOps team wants to use preventive and detective controls to govern all accounts. The DevOps team needs to ensure the security of accounts now and in the future as the company creates new accounts in the organization.
Which solution will meet these requirements?

Answer: C

Explanation:
AWS Control Tower provides an integrated governance framework that combines both preventive controls, implemented as Service Control Policies at the OU level, and detective controls, implemented as AWS Config rules applied across all enrolled accounts. Control Tower automatically applies these guardrails to all accounts in enrolled OUs. When new accounts are provisioned through Account Factory, they are automatically enrolled in the assigned OU and receive all applicable preventive and detective controls immediately without manual intervention. Option A uses only SCPs, covering only preventive controls without built-in detective capabilities. Option C requires manually updating stack sets when new accounts are created and does not provide preventive controls via SCPs. Option D provides only detective controls through Config rules with no preventive guardrails. Control Tower is the only option that natively handles both control types and automatically governs newly created accounts.


NEW QUESTION # 222
A company uses an organization in AWS Organizations to manage multiple AWS accounts The company needs an automated process across all AWS accounts to isolate any compromised Amazon EC2 instances when the instances receive a specific tag.
Which combination of steps will meet these requirements? (Select TWO.)

Answer: C,E

Explanation:
* Step 1: Deploy the Automation Solution using CloudFormation StackSets To automate the process across multiple AWS accounts within an organization, you can use AWS CloudFormation StackSets. StackSets allow you to deploy CloudFormation templates to multiple accounts within an organization, ensuring consistent infrastructure and automation.
Action: Use AWS CloudFormation StackSets to deploy the necessary resources across all AWS accounts. This includes deploying the Lambda function and security groups that will isolate compromised EC2 instances.
Why: StackSets make it easy to deploy and manage resources across multiple AWS accounts, reducing the operational overhead.
Reference:
This corresponds to Option A: Use AWS CloudFormation StackSets to deploy the CloudFormation stacks in all AWS accounts.
* Step 2: Isolate EC2 Instances using Lambda and Security GroupsWhen an EC2 instance is compromised, it needs to be isolated from the network. This can be done by creating a security group with no inbound or outbound rules and attaching it to the instance. A Lambda function can handle this process and can be triggered automatically by an Amazon EventBridge rule when a specific tag (e.g., "isolation") is applied to the compromised instance.
Action: Create a Lambda function that attaches an isolated security group (with no inbound or outbound rules) to the compromised EC2 instances. Set up an EventBridge rule to trigger the Lambda function when the "isolation" tag is applied to the instance.
Why: This automates the isolation process, ensuring that any compromised instances are immediately cut off from the network, reducing the potential damage from the compromise.
This corresponds to Option E: Create an AWS CloudFormation template that creates an EC2 instance role that has no IAM policies attached. Configure the template to have a security group that has no inbound rules or outbound rules. Use the CloudFormation template to create an AWS Lambda function that attaches the IAM role to instances. Configure the Lambda function to replace any existing security groups with the new security group. Set up an Amazon EventBridge rule to invoke the Lambda function when a specific tag is applied to a compromised EC2 instance.


NEW QUESTION # 223
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