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Amazon DOP-C02 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Configuration Management and Infrastructure as Code17%- Infrastructure provisioning and automation
  • 1. AWS CloudFormation and CDK usage
    • 2. Configuration tools and automation strategies
      Topic 2: Resilient Cloud Solutions15%- High availability and fault tolerance design
      • 1. Disaster recovery strategies
        • 2. Multi-AZ and multi-region architectures
          Topic 3: Security and Compliance Automation13%- Security automation in CI/CD and infrastructure
          • 1. Compliance monitoring and auditing
            • 2. IAM policy automation and governance
              Topic 4: Incident and Event Management18%- Operational response and recovery
              • 1. Incident detection and remediation
                • 2. Automated event-driven responses
                  Topic 5: SDLC Automation22%- CI/CD pipeline design and implementation
                  • 1. Build and deployment automation
                    • 2. Pipeline optimization and scaling
                      Topic 6: Monitoring and Logging15%- Observability and metrics
                      • 1. Log aggregation and analysis
                        • 2. CloudWatch monitoring and alarms

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                          Amazon AWS Certified DevOps Engineer - Professional Sample Questions (Q258-Q263):

                          NEW QUESTION # 258
                          A DevOps engineer has developed an AWS Lambda function The Lambda function starts an AWS CloudFormation drift detection operation on all supported resources for a specific CloudFormation stack The Lambda function then exits Its invocation The DevOps engineer has created an Amazon EventBrdge scheduled rule that Invokes the Lambda function every hour. An Amazon Simple Notification Service (Amazon SNS) topic already exists In the AWS account. The DevOps engineer has subscribed to the SNS topic to receive notifications The DevOps engineer needs to receive a notification as soon as possible when drift is detected in this specific stack configuration.
                          Which solution Will meet these requirements?

                          Answer: B

                          Explanation:
                          Explanation
                          A comprehensive and detailed explanation is:
                          Option A is incorrect because EventBridge rules cannot filter events based on the message body or attributes of the target service. Therefore, configuring an SNS subscription filter policy to match the CloudFormation stack will not work. The SNS topic will receive all events from the EventBridge rule, regardless of the stack name or drift status.
                          Option B is incorrect because it introduces unnecessary complexity and cost. Creating a second Lambda function to query the CloudFormation API for the drift detection results is redundant, since CloudFormation already publishes drift detection events to EventBridge. Moreover, invoking two Lambda functions every hour will incur more charges than invoking one.
                          Option C is incorrect because GuardDuty does not provide drift detection for CloudFormation stacks.
                          GuardDuty is a threat detection service that monitors for malicious activity and unauthorized behavior in AWS accounts and workloads. It does not monitor or report on configuration changes or drifts in CloudFormation stacks.
                          Option D is correct because it leverages AWS Config and its managed rule for drift detection. AWS Config is a service that enables you to assess, audit, and evaluate the configurations of your AWS resources. It can detect configuration changes and drifts in CloudFormation stacks using the cloudformation-stack-drift-detection-check managed rule. This rule triggers an AWS Config event when a stack drifts from its expected template configuration. By creating a second EventBridge rule that reacts to this event for the specific stack, the DevOps engineer can configure the SNS topic as a target and receive a notification as soon as possible when drift is detected.
                          References:
                          AWS Config
                          Amazon SNS subscription filter policies
                          Amazon EventBridge rules


                          NEW QUESTION # 259
                          A company has an application that runs on Amazon EC2 instances in an Auto Scaling group. The application processes a high volume of messages from an Amazon Simple Queue Service (Amazon SQS) queue.
                          A DevOps engineer noticed that the application took several hours to process a group of messages from the SQS queue. The average CPU utilization of the Auto Scaling group did not cross the threshold of a target tracking scaling policy when processing the messages. The application that processes the SQS queue publishes logs to Amazon CloudWatch Logs.
                          The DevOps engineer needs to ensure that the queue is processed quickly.
                          Which solution meets these requirements with the LEAST operational overhead?

                          Answer: C

                          Explanation:
                          Comprehensive and Detailed Explanation From Exact Extract:
                          The default CPU utilization metric does not reflect the processing backlog in the SQS queue, so the Auto Scaling group is not scaling properly to handle the workload.
                          To scale the Auto Scaling group based on queue length, you can create a target tracking scaling policy that uses acustom metricthat combines the SQS queue'sApproximateNumberOfMessagesVisibleand the number of instances (GroupIn-ServiceInstances) metric usingCloudWatch metric math. This allows the scaling policy to calculate the average number of messages per instance and scale accordingly.
                          This approach requires no additional Lambda functions or log processing, thus minimizing operational overhead.
                          Option A and B require Lambda functions to publish custom metrics, which increases operational complexity.
                          Option D also adds complexity with logging and metric filters.
                          Reference:
                          Scaling based on SQS queue length using metric math:"You can create CloudWatch metric math expressions combining SQS and Auto Scaling group metrics to enable target tracking scaling policies that respond to queue backlog."(AWS Auto Scaling with SQS) Target Tracking Scaling Policies:"Target tracking policies can use metric math expressions as a source to make scaling decisions."(AWS Auto Scaling Target Tracking)


                          NEW QUESTION # 260
                          A company is implementing a well-architected design for its globally accessible API stack. The design needs to ensure both high reliability and fast response times for users located in North America and Europe.
                          The API stack contains the following three tiers:
                          Amazon API Gateway
                          AWS Lambda
                          Amazon DynamoDB
                          Which solution will meet the requirements?

                          Answer: B


                          NEW QUESTION # 261
                          A DevOps engineer is building an application that uses an AWS Lambda function to query an Amazon Aurora MySQL DB cluster. The Lambda function performs only read queries. Amazon EventBridge events invoke the Lambda function.
                          As more events invoke the Lambda function each second, the database's latency increases and the database's throughput decreases. The DevOps engineer needs to improve the performance of the application.
                          Which combination of steps will meet these requirements? (Select THREE.)

                          Answer: A,C,F

                          Explanation:
                          Explanation
                          Short Explanation: To improve the performance of the application, the DevOps engineer should use Amazon RDS Proxy, implement the database connection opening outside the Lambda event handler code, and connect to the proxy endpoint from the Lambda function.
                          References:
                          Amazon RDS Proxy is a fully managed, highly available database proxy for Amazon Relational Database Service (RDS) that makes applications more scalable, more resilient to database failures, and more secure1. By using Amazon RDS Proxy, the DevOps engineer can reduce the overhead of opening and closing connections to the database, which can improve latency and throughput2.
                          The DevOps engineer should connect the proxy to the Aurora cluster reader endpoint, which allows read-only connections to one of the Aurora Replicas in the DB cluster3. This can help balance the load across multiple read replicas and improve performance for read-intensive workloads4.
                          The DevOps engineer should implement the database connection opening outside the Lambda event handler code, which means using a global variable to store the database connection object5. This can enable connection reuse across multiple invocations of the Lambda function, which can reduce latency and improve performance.
                          The DevOps engineer should connect to the proxy endpoint from the Lambda function, which is a unique URL that represents the proxy. This can allow the Lambda function to access the database through the proxy, which can provide benefits such as connection pooling, load balancing, failover handling, and enhanced security.
                          The other options are incorrect because:
                          Implementing database connection pooling inside the Lambda code is unnecessary and redundant when using Amazon RDS Proxy, which already provides connection pooling as a service.
                          Implementing the database connection opening and closing inside the Lambda event handler code is inefficient and costly, as it can increase latency and consume more resources for each invocation of the Lambda function.
                          Connecting to the Aurora cluster endpoint from the Lambda function is not optimal for read-only queries, as it can direct traffic to either the primary instance or one of the Aurora Replicas in the DB cluster. This can result in inconsistent performance and potential conflicts with write operations on the primary instance.


                          NEW QUESTION # 262
                          A company wants governance where only specific Regions and services can be used, with centralized AD authentication and job-function-based roles.
                          Which solution meets these requirements?

                          Answer: D

                          Explanation:
                          Apply SCPs for Region and service restriction. Use CloudFormation StackSets to consistently deploy IAM roles with trust policies for SSO/AD integration. This model enforces governance uniformly across all accounts per AWS multi-account best practices.


                          NEW QUESTION # 263
                          ......

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