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Amazon DOP-C02 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Configuration Management and Infrastructure as Code17%- Manage infrastructure deployments
  • 1. Implement version control for configurations
  • 2. Provision and update resources automatically
  • 3. Manage multi-account and multi-region environments
- Implement infrastructure as code
  • 1. Manage templates and stacks
  • 2. Enforce configuration standards
  • 3. Use AWS CloudFormation, Terraform, or AWS CDK
- Automate configuration management
  • 1. Maintain consistent configurations
  • 2. Detect and remediate configuration drift
  • 3. Use AWS Systems Manager, Ansible, or Puppet
Topic 2: 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. Design for fault tolerance
  • 3. Manage capacity and elasticity
- Implement disaster recovery
  • 1. Test and validate recovery plans
  • 2. Backup and restore strategies
  • 3. Pilot light, warm standby, and active-active
Topic 3: SDLC Automation22%- Automate software release processes
  • 1. Manage artifacts and dependencies
  • 2. Implement deployment strategies
  • 3. Automate rollback procedures
- Implement CI/CD pipelines
  • 1. Integrate version control systems
  • 2. Automate build, test, and deployment stages
  • 3. Use AWS CodePipeline, CodeBuild, CodeDeploy
- Automate testing and validation
  • 1. Unit, integration, and performance testing
  • 2. Automate quality gates
  • 3. Security and compliance testing
Topic 4: Incident and Event Response14%- Automate event management
  • 1. Classify and prioritize events
  • 2. Integrate with ticketing and workflow systems
  • 3. Automate common operational tasks
- Manage incidents and outages
  • 1. Coordinate response and recovery
  • 2. Document and learn from events
  • 3. Troubleshoot complex issues
- Improve operational processes
  • 1. Optimize response time and efficiency
  • 2. Update runbooks and playbooks
  • 3. Implement feedback loops
Topic 5: Monitoring and Logging15%- Implement monitoring solutions
  • 1. Use Amazon CloudWatch for metrics and alarms
  • 2. Create dashboards and insights
  • 3. Monitor infrastructure, applications, and costs
- Automate incident response
  • 1. Implement alerting and notification workflows
  • 2. Set up event-driven actions with Amazon EventBridge
  • 3. Automate remediation and scaling
- Implement logging and analysis
  • 1. Analyze logs for troubleshooting and security
  • 2. Centralize logs with CloudWatch Logs
  • 3. Use AWS X-Ray for tracing
Topic 6: Security, Governance, and Compliance17%- Automate security and compliance
  • 1. Integrate security into CI/CD pipelines
  • 2. Detect and remediate violations automatically
  • 3. Use AWS Security Hub and AWS Shield
- Implement security controls
  • 1. Secure secrets and credentials
  • 2. Manage IAM for pipelines and environments
  • 3. Encrypt data at rest and in transit
- Enforce governance and compliance
  • 1. Manage access and permissions at scale
  • 2. Implement compliance rules and audits
  • 3. Use AWS Config and AWS Organizations

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Amazon AWS Certified DevOps Engineer - Professional Sample Questions (Q172-Q177):

NEW QUESTION # 172
A company has configured Amazon RDS storage autoscaling for its RDS DB instances. A DevOps team needs to visualize the autoscaling events on an Amazon CloudWatch dashboard. Which solution will meet this requirement?

Answer: C

Explanation:
Step 1: Reacting to RDS Storage Autoscaling Events Using Amazon EventBridgeAmazon RDS emits events when storage autoscaling occurs. To visualize these events in a CloudWatch dashboard, you can create an EventBridge rule that listens for these specific autoscaling events.
Action: Create an EventBridge rule that reacts to RDS storage autoscaling events from the RDS event stream.
Why: EventBridge allows you to listen to RDS events and route them to specific AWS services for processing.
Step 2: Creating a Custom CloudWatch Metric via LambdaOnce the EventBridge rule detects a storage autoscaling event, you can use a Lambda function to publish a custom metric to CloudWatch. This metric can then be visualized in a CloudWatch dashboard.
Action: Use a Lambda function to publish custom metrics to CloudWatch based on the RDS storage autoscaling events.
Why: Custom metrics allow you to track specific events like autoscaling and visualize them easily on a CloudWatch dashboard.
Reference: AWS documentation on Publishing Custom Metrics to CloudWatch.
This corresponds to Option A: Create an Amazon EventBridge rule that reacts to RDS storage autoscaling events from RDS events. Create an AWS Lambda function that publishes a CloudWatch custom metric.
Configure the EventBridge rule to invoke the Lambda function. Visualize the custom metric by using the CloudWatch dashboard.


NEW QUESTION # 173
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?

Answer: D

Explanation:
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."


NEW QUESTION # 174
A company has an AWS CodePipeline pipeline that is configured with an Amazon S3 bucket in the eu-west-1 Region. The pipeline deploys an AWS Lambda application to the same Region. The pipeline consists of an AWS CodeBuild project build action and an AWS CloudFormation deploy action.
The CodeBuild project uses the aws cloudformation package AWS CLI command to build an artifact that contains the Lambda function code's .zip file and the CloudFormation template. The CloudFormation deploy action references the CloudFormation template from the output artifact of the CodeBuild project's build action.
The company wants to also deploy the Lambda application to the us-east-1 Region by using the pipeline in eu-west-1. A DevOps engineer has already updated the CodeBuild project to use the aws cloudformation package command to produce an additional output artifact for us-east-1.
Which combination of additional steps should the DevOps engineer take to meet these requirements? (Choose two.)

Answer: C,D

Explanation:
A) The CloudFormation template should be modified to include a parameter that indicates the location of the .zip file containing the Lambda function's code. This allows the CloudFormation deploy action to use the correct artifact depending on the region. This is critical because Lambda functions need to reference their code artifacts from the same region they are being deployed in.
B) You would also need to create a new CloudFormation deploy action for the us-east-1 Region within the pipeline. This action should be configured to use the CloudFormation template from the artifact that was specifically created for us-east-1.


NEW QUESTION # 175
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,C

Explanation:
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.
References:
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 # 176
A DevOps engineer at a company is supporting an AWS environment in which all users use AWS IAM Identity Center (AWS Single Sign-On). The company wants to immediately disable credentials of any new IAM user and wants the security team to receive a notification.
Which combination of steps should the DevOps engineer take to meet these requirements? (Choose three.)

Answer: A,B,D


NEW QUESTION # 177
......

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