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Achieving certification in the Amazon DOP-C02 Exam demonstrates that a DevOps engineer has a deep understanding of the AWS platform and is able to design, implement, and manage complex, multi-tier applications in a scalable, fault-tolerant manner. AWS Certified DevOps Engineer - Professional certification is highly valued by employers and can lead to higher salaries and more challenging job opportunities in the DevOps field.
Achieving the AWS Certified DevOps Engineer - Professional certification can open up many career opportunities for IT professionals. AWS Certified DevOps Engineer - Professional certification validates a candidate's expertise in designing, deploying, and operating scalable and highly available systems on AWS, which is a highly sought-after skillset in today's technology landscape. Additionally, this certification demonstrates a candidate's commitment to their professional development and their ability to adapt to new technologies and practices in the rapidly-evolving field of DevOps.
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Amazon DOP-C02 Certification Exam is designed to test an individual's ability to implement and manage a DevOps environment on the AWS platform. This includes designing and implementing continuous delivery systems, continuous integration, and continuous deployment systems. It also measures an individual's knowledge of monitoring, logging, and metrics systems on the AWS platform, as well as their ability to implement and manage security and compliance policies.
Amazon AWS Certified DevOps Engineer - Professional Sample Questions (Q13-Q18):
NEW QUESTION # 13
A company uses an AWS CodeCommit repository to store its source code and corresponding unit tests. The company has configured an AWS CodePipeline pipeline that includes an AWS CodeBuild project that runs when code is merged to the main branch of the repository.
The company wants the CodeBuild project to run the unit tests. If the unit tests pass, the CodeBuild project must tag the most recent commit.
How should the company configure the CodeBuild project to meet these requirements?
- A. Configure the CodeBuild project to use AWS CLI commands to copy the code from the CodeCommit repository. Configure the project to run the unit tests. Configure the project to use AWS CLI commands to create a new repository tag in the repository if the code passes the unit tests.
- B. Configure the CodeBuild project to use native Git to clone the CodeCommit repository. Configure the project to run the unit tests. Configure the project to use native Git to create a tag and to push the Git tag to the repository if the code passes the unit tests.
- C. Configure the CodeBuild project to use native Git to clone the CodeCommit repository. Configure the project to run the unit tests. Configure the project to use AWS CLI commands to create a new repository tag in the repository if the code passes the unit tests.
- D. Configure the CodeBuild project to use AWS CLI commands to copy the code from the CodeCommit repository. Configure the project lo run the unit tests. Configure the project to use AWS CLI commands to create a new Git tag in the repository if the code passes the unit tests.
Answer: B
Explanation:
Step 1: Using Native Git in CodeBuildTo meet the requirement of running unit tests and tagging the most recent commit if the tests pass, the CodeBuild project should be configured to use native Git to clone the CodeCommit repository. Native Git support allows full functionality for managing the repository, including the ability to create and push tags.
Action: Configure the CodeBuild project to use native Git to clone the repository and run the tests.
Why: Using native Git provides flexibility for managing tags and other repository operations after the tests are successfully executed.
Step 2: Tagging the Most Recent CommitOnce the unit tests pass, the CodeBuild project can use native Git to create a tag for the most recent commit and push that tag to the repository. This ensures that the tagged commit is linked to the test results.
Action: Configure the project to use native Git to create and push a tag to the repository if the tests pass.
Why: This ensures the correct commit is tagged automatically, streamlining the workflow.
Reference: AWS documentation on AWS CodeBuild and Git integration.
This corresponds to Option A: Configure the CodeBuild project to use native Git to clone the CodeCommit repository. Configure the project to run the unit tests. Configure the project to use native Git to create a tag and to push the Git tag to the repository if the code passes the unit tests.
NEW QUESTION # 14
A company uses Amazon EC2 as its primary compute platform. A DevOps team wants to audit the company's EC2 instances to check whether any prohibited applications have been installed on the EC2 instances.
Which solution will meet these requirements with the MOST operational efficiency?
- A. Designate Amazon CloudWatch Logs as the log destination for all application instances Run an automated script across all instances to create an inventory of installed applications Configure the script to forward the results to CloudWatch Logs Create a CloudWatch alarm that uses filter patterns to search log data to identify prohibited applications.
- B. Configure AWS Systems Manager on each instance Use Systems Manager Inventory Create AWS Config rules that monitor changes from Systems Manager Inventory to identify prohibited applications.
- C. Configure AWS Systems Manager on each instance. Use Systems Manager Inventory. Filter a trail in AWS CloudTrail for Systems Manager Inventory events to identify prohibited applications.
- D. Configure AWS Systems Manager on each instance Use AWS Systems Manager Inventory Use Systems Manager resource data sync to synchronize and store findings in an Amazon S3 bucket Create an AWS Lambda function that runs when new objects are added to the S3 bucket. Configure the Lambda function to identify prohibited applications.
Answer: D
Explanation:
Configure AWS Systems Manager on Each Instance:
AWS Systems Manager provides a unified interface for managing AWS resources. Install the Systems Manager agent on each EC2 instance to enable inventory management and other features.
Use AWS Systems Manager Inventory:
Systems Manager Inventory collects metadata about your instances and the software installed on them. This data includes information about applications, network configurations, and more.
Enable Systems Manager Inventory on all EC2 instances to gather detailed information about installed applications.
Use Systems Manager Resource Data Sync to Synchronize and Store Findings in an Amazon S3 Bucket:
Resource Data Sync aggregates inventory data from multiple accounts and regions into a single S3 bucket, making it easier to query and analyze the data.
Configure Resource Data Sync to automatically transfer inventory data to an S3 bucket for centralized storage.
Create an AWS Lambda Function that Runs When New Objects are Added to the S3 Bucket:
Use an S3 event to trigger a Lambda function whenever new inventory data is added to the S3 bucket.
The Lambda function can parse the inventory data and check for the presence of prohibited applications.
Configure the Lambda Function to Identify Prohibited Applications:
The Lambda function should be programmed to scan the inventory data for any known prohibited applications and generate alerts or take appropriate actions if such applications are found.
Example Lambda function in Python
import json
import boto3
def lambda_handler(event, context):
s3 = boto3.client('s3')
bucket = event['Records'][0]['s3']['bucket']['name']
key = event['Records'][0]['s3']['object']['key']
response = s3.get_object(Bucket=bucket, Key=key)
inventory_data = json.loads(response['Body'].read().decode('utf-8'))
prohibited_apps = ['app1', 'app2']
for instance in inventory_data['Instances']:
for app in instance['Applications']:
if app['Name'] in prohibited_apps:
# Send notification or take action
print(f"Prohibited application found: {app['Name']} on instance {instance['InstanceId']}") return {'statusCode': 200, 'body': json.dumps('Check completed')} By leveraging AWS Systems Manager Inventory, Resource Data Sync, and Lambda, this solution provides an efficient and automated way to audit EC2 instances for prohibited applications.
References:
AWS Systems Manager Inventory
AWS Systems Manager Resource Data Sync
S3 Event Notifications
AWS Lambda
NEW QUESTION # 15
A company is implementing AWS CodePipeline to automate its testing process The company wants to be notified when the execution state fails and used the following custom event pattern in Amazon EventBridge:
Which type of events will match this event pattern?
- A. All the events across all pipelines
- B. Approval actions across all the pipelines
- C. All rejected or failed approval actions across all the pipelines
- D. Failed deploy and build actions across all the pipelines
Answer: C
Explanation:
Action-level states in events
Action state Description
STARTED The action is currently running.
SUCCEEDED The action was completed successfully.
FAILED For Approval actions, the FAILED state means the action was either rejected by the reviewer or failed due to an incorrect action configuration.
CANCELED The action was canceled because the pipeline structure was updated.
NEW QUESTION # 16
A company has multiple AWS accounts. The company uses AWS IAM Identity Center (AWS Single Sign-On) that is integrated with AWS Toolkit for Microsoft Azure DevOps. The attributes for access control feature is enabled in IAM Identity Center.
The attribute mapping list contains two entries. The department key is mapped to
${path:enterprise.department}. The costCenter key is mapped to ${path:enterprise.costCenter}.
All existing Amazon EC2 instances have a department tag that corresponds to three company departments (d1, d2, d3). A DevOps engineer must create policies based on the matching attributes. The policies must minimize administrative effort and must grant each Azure AD user access to only the EC2 instances that are tagged with the user's respective department name.
Which condition key should the DevOps engineer include in the custom permissions policies to meet these requirements?
- A.

- B.

- C.

- D. <e ip="img_142.jpg"></e>b
Answer: D
Explanation:
Explanation
https://docs.aws.amazon.com/singlesignon/latest/userguide/configure-abac.html
NEW QUESTION # 17
A company runs several applications in the same AWS account. The applications send logs to Amazon CloudWatch.
A data analytics team needs to collect performance metrics and custom metrics from the applications. The analytics team needs to transform the metrics data before storing the data in an Amazon S3 bucket. The analytics team must automatically collect any new metrics that are added to the CloudWatch namespace.
Which solution will meet these requirements with the LEAST operational overhead?
- A. Configure a CloudWatch metrics stream to include all the metrics and to deliver the metrics to an Amazon Data Firehose delivery stream. Configure the Firehose delivery stream to invoke an AWS Lambda function to transform the data. Configure the delivery stream to send the transformed data to the S3 bucket.
- B. Configure a CloudWatch metric stream to include metrics from the application and the CloudWatch namespace. Configure the metric stream to deliver the metrics to an Amazon Data Firehose delivery stream. Configure the Firehose delivery stream to invoke an AWS Lambda function to transform the data. Configure the delivery stream to send the transformed data to the S3 bucket.
- C. Configure subscription filters on the application log groups to target an Amazon Data Firehose delivery stream. Configure the Firehose delivery stream to invoke an AWS Lambda function to transform the data. Configure the delivery stream to send the transformed data to the S3 bucket.
- D. Configure metric filters for the CloudWatch logs to create custom metrics. Configure a CloudWatch metric stream to deliver the application metrics to the S3 bucket.
Answer: A
Explanation:
Amazon CloudWatch metric streams are designed to deliver metrics in near real time to downstream services like Amazon Data Firehose with minimal configuration and management overhead. By configuring a metric stream to include all metrics, you ensure that any newly created performance or custom metrics are automatically included without needing to update filters or code when namespaces or metrics change.
Option B uses a CloudWatch metric stream → Firehose → Lambda → S3 pattern. Firehose natively supports invoking a Lambda function for in-flight transformation of the metric data before final delivery to S3. This satisfies the requirement to transform metrics before storing them and provides a fully managed, serverless pipeline with very little ongoing operational burden.
Option A mentions including metrics from "the application and the CloudWatch namespace," which implies more manual selection and maintenance, potentially missing new metrics if not explicitly added. Options C and D work at the log level, not at the metric level, and would require building additional logic to derive metrics from logs. This is more complex and not aligned with "least operational overhead." Therefore, Option B is the most efficient and scalable solution.
NEW QUESTION # 18
......
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