Amazon Web Services DOP-C02 Exam With Confidence Using Practice Dumps

Exam Code:

DOP-C02

Exam Name:

AWS Certified DevOps Engineer - Professional

Certification:

AWS Certified Professional

Vendor:

Amazon Web Services

Questions:

449

Last Updated:

Sep 17, 2026

Exam Status:

Stable

DOP-C02: AWS Certified Professional Exam 2025 Study Guide Pdf and Test Engine

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AWS Certified DevOps Engineer - Professional Questions and Answers

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Question 1

A DevOps administrator is configuring a repository to store a company ' s container images. The administrator needs to configure a lifecycle rule that automatically deletes container images that have a specific tag and that are older than 15 days. Which solution will meet these requirements with the MOST operational efficiency?

Options:

Create a repository in Amazon Elastic Container Registry (Amazon ECR). Add a lifecycle policy to the repository to expire images that have the matching tag after 15 days.

Create a repository in AWS CodeArtifact. Add a repository policy to the CodeArtifact repository to expire old assets that have the matching tag after 15 days.

Create a bucket in Amazon S3. Add a bucket lifecycle policy to expire old objects that have the matching tag after 15 days.

Create an EC2 Image Builder container recipe. Add a build component to expire the container that has the matching tag after 15 days.

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Question 2

A DevOps team supports an application that runs on a large number of Amazon EC2 instances in an Auto Scaling group. The DevOps team uses AWS CloudFormation to deploy the EC2 instances. The application recently experienced an issue. A single instance returned errors to a large percentage of requests. The EC2 instance responded as healthy to both Amazon EC2 and Elastic Load Balancing health checks. The DevOps team collects application logs in Amazon CloudWatch by using the embedded metric format. The DevOps team needs to receive an alert if any EC2 instance is responsible for more than half of all errors. Which combination of steps will meet these requirements with the LEAST operational overhead? (Select TWO.)

Options:

Create a CloudWatch Contributor Insights rule that groups logs from the CloudWatch application logs based on instance ID and errors.

Create a resource group in AWS Resource Groups. Use the CloudFormation stack to group the resources for the application. Add the application to CloudWatch Application Insights. Use the resource group to identify the application.

Create a metric filter for the application logs to count the occurrence of the term " Error. " Create a CloudWatch alarm that uses the METRIC_COUNT function to determine whether errors have occurred. Configure the CloudWatch alarm to send a notification to an Amazon Simple Notification Service (Amazon SNS) topic to notify the DevOps team.

Create a CloudWatch alarm that uses the INSIGHT_RULE_METRIC function to determine whether a specific instance is responsible for more than half of all errors reported by EC2 instances. Configure the CloudWatch alarm to send a notification to an Amazon Simple Notification Service (Amazon SNS) topic to notify the DevOps team.

Create a CloudWatch subscription filter for the application logs that filters for errors and invokes an AWS Lambda function. Configure the Lambda function to send the instance ID and error in a notification to an Amazon Simple Notification Service (Amazon SNS) topic to notify the DevOps team.

Question 3

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.)

Options:

Create a data stream consumer with enhanced fan-out. Set the Lambda function that processes the logs as the consumer.

Increase the ParallelizationFactor setting in the Lambda event source mapping.

Configure reserved concurrency for the Lambda function that processes the logs.

Increase the batch size in the Kinesis data stream.

Turn off the ReportBatchltemFailures setting in the Lambda event source mapping.

Increase the number of shards in the Kinesis data stream.

Answer:

A, B, C

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.

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

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Amazon Web Services DOP-C02 Exam With Confidence Using Practice Dumps

DOP-C02: AWS Certified Professional Exam 2025 Study Guide Pdf and Test Engine

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AWS Certified DevOps Engineer - Professional Questions and Answers

Options:

Answer:

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Answer:

Explanation:

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