Amazon Web Services DOP-C02 Study & Exam Dumps 2025

AWS Certified DevOps Engineer - Professional Questions and Answers

Question 1

A company is building a new pipeline by using AWS CodePipeline and AWS CodeBuild in a build account. The pipeline consists of two stages. The first stage is a CodeBuild job to build and package an AWS Lambda function. The second stage consists of deployment actions that operate on two different AWS accounts a development environment account and a production environment account. The deployment stages use the AWS Cloud Format ion action that CodePipeline invokes to deploy the infrastructure that the Lambda function requires.

A DevOps engineer creates the CodePipeline pipeline and configures the pipeline to encrypt build artifacts by using the AWS Key Management Service (AWS KMS) AWS managed key for Amazon S3 (the aws/s3 key). The artifacts are stored in an S3 bucket When the pipeline runs, the Cloud Formation actions fail with an access denied error.

Which combination of actions must the DevOps engineer perform to resolve this error? (Select TWO.)

Options:

Create an S3 bucket in each AWS account for the artifacts Allow the pipeline to write to the S3 buckets. Create a CodePipeline S3 action to copy the artifacts to the S3 bucket in each AWS account Update the CloudFormation actions to reference the artifacts S3 bucket in the production account.

Create a customer managed KMS key Configure the KMS key policy to allow the IAM roles used by the CloudFormation action to perform decrypt operations Modify the pipeline to use the customer managed KMS key to encrypt artifacts.

Create an AWS managed KMS key Configure the KMS key policy to allow the development account and the production account to perform decrypt operations. Modify the pipeline to use the KMS key to encrypt artifacts.

In the development account and in the production account create an IAM role for CodePipeline. Configure the roles with permissions to perform CloudFormation operations and with permissions to retrieve and decrypt objects from the artifacts S3 bucket. In the CodePipeline account configure the CodePipeline CloudFormation action to use the roles.

In the development account and in the production account create an IAM role for CodePipeline Configure the roles with permissions to perform CloudFormationoperations and with permissions to retrieve and decrypt objects from the artifacts S3 bucket. In the CodePipelme account modify the artifacts S3 bucket policy to allow the roles access Configure the CodePipeline CloudFormation action to use the roles.

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Question 2

A company's application runs on Amazon EC2 instances. The application writes to a log file that records the username, date, time: and source IP address of the login. The log is published to a log group in Amazon CloudWatch Logs

The company is performing a root cause analysis for an event that occurred on the previous day The company needs to know the number of logins for a specific user from the past 7 days

Which solution will provide this information'?

Options:

Create a CloudWatch Logs metric filter on the log group Use a filter pattern that matches the username. Publish a CloudWatch metric that sums the number of logins over the past 7 days.

Create a CloudWatch Logs subscription on the log group Use a filter pattern that matches the username Publish a CloudWatch metric that sums the number of logins over the past 7 days

Create a CloudWatch Logs Insights query that uses an aggregation function to count the number of logins for the username over the past 7 days. Run the query against the log group

Create a CloudWatch dashboard. Add a number widget that has a filter pattern that counts the number of logins for the username over the past 7 days directly from the log group

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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