AWS DevOps Practise Test – (DOP-C02) Practise Test – 4

September 6, 2024

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AWS DevOps Practise Test - (DOP-C02)

Practise Test-4

1 / 19

A developer has uploaded an object of size 100 MB to an Amazon S3 bucket as a single-part direct upload using the REST API that has checksum enabled. The checksum of the object uploaded via the REST API was the checksum of the entire object. Later that day, the developer used the AWS Management Console to rename the object, copy it and edit its metadata. Later, when the developer checked for the checksum of the object updated via the AWS Management Console, the checksum was not the checksum of the entire object. Confused by the behavior, the developer has reached out to you for a possible solution.

As an AWS Certified DevOps Engineer - Professional, which of the following options would you identify as the reason for this behavior?

When you change metadata of an object in S3, the checksum algorithm of the objects changes by default. This is an expected behavior

A new checksum value for the object, that is calculated based on the checksum values of the individual parts, has been created. This behavior is expected

If an object is greater than 50 MB in size, checksum will be a calculation based on the checksum values of each individual parts. The developer's initial calculation for the REST API based checksum was incorrect. This resulted in the mismatch of the two checksum values

If an object is greater than 16 MB in size, checksum will be a calculation based on the checksum values of each individual parts. The developer's initial calculation for the REST API based checksum was incorrect. This resulted in the mismatch of the two checksum values

2 / 19

An AWS managed cloudformation-stack-drift-detection-check rule is defined in AWS Config for drift detection in AWS CloudFormation resources. The DevOps team is facing two issues:

a) How to detect drifts of Cloudformation custom resources b) Drift status of the stack shows as IN_SYNC in the CloudFormation console, the following is the drift detection error - 'While AWS CloudFormation failed to detect drift, defaulting to NON_COMPLIANT. Re-evaluate the rule and try again. If the problem persists contact AWS CloudFormation support'

As a DevOps Engineer, which steps will you combine to fix the aforementioned issues? (Select two)

You receive the error when the AWS Identity and Access Management (IAM) role for the required cloudformationRoleArn parameter doesn't have sufficient service permissions

AWS CloudFormation only determines drift for property values that are explicitly set. Explicitly set the property values for your custom resource to be included in drift

This error is a false positive and can be ignored for this scenario

AWS Config rule depends on the availability of DetectStackDrift action of CloudFormation API. AWS Config defaults the rule to NON_COMPLIANT when throttling occurs

AWS CloudFormation does not support drift detection of custom resources

3 / 19

For deployments across AWS accounts, an e-commerce company has decided to use AWS CodePipeline to deploy an AWS CloudFormation stack in an AWS account (account A) to a different AWS account (account B).

What combination of steps will you take to configure this requirement? (Select three)

In account A, create a customer-managed AWS KMS key that grants usage permissions to account A's CodePipeline service role and account B. Also, create an Amazon Simple Storage Service (Amazon S3) bucket with a bucket policy that grants account B access to the bucket

In account B, create a service role for the CloudFormation stack that includes the required permissions for the services deployed by the stack. In account A, update the CodePipeline configuration to include the resources associated with account B

In account A, create a service role for the CloudFormation stack that includes the required permissions for the services deployed by the stack. In account B, update the CodePipeline configuration to include the resources associated with account A

In account B, create a cross-account IAM role. In account A, add the AssumeRole permission to account A's CodePipeline service role to allow it to assume the cross-account role in account B

In account A, create a customer-managed AWS KMS key that grants usage permissions to account A's CodePipeline service role and account B. In account B, create an Amazon Simple Storage Service (Amazon S3) bucket with a bucket policy that grants account A access to the bucket

In account B, add the AssumeRole permission to account A's CodePipeline service role to allow it to assume the cross-account role in account A

4 / 19

An e-commerce company is deploying its flagship application on Amazon EC2 instances. The DevOps team at the company needs a solution to query both the application logs as well as the AWS account API activity.

As an AWS Certified DevOps Engineer - Professional, what solution will you recommend to meet these requirements?

Set up AWS CloudTrail to deliver the API logs to CloudWatch Logs. Leverage the Amazon CloudWatch Agent to deliver logs from the EC2 instances to Amazon CloudWatch Logs. Utilize the CloudWatch Logs Insights to query both sets of logs

Set up AWS CloudTrail to deliver the API logs to Kinesis Data Streams. Leverage the Amazon CloudWatch Agent to deliver logs from the EC2 instances to Kinesis Data Streams. Direct both the Kinesis Data Streams to direct the stream output to Kinesis Data Analytics for running near-real-time queries on both sets of logs

Set up AWS CloudTrail to deliver the API logs to Amazon S3. Leverage the Amazon CloudWatch Agent to deliver logs from the EC2 instances to Amazon CloudWatch Logs. Utilize Amazon Athena to query both sets of logs

Set up AWS CloudTrail to deliver the API logs to Amazon S3. Leverage the Amazon CloudWatch Agent to deliver logs from the EC2 instances to Amazon S3. Utilize Amazon Athena to query both sets of logs

5 / 19

A media application runs on a host of Amazon EC2 instances fronted with an Application Load Balancer (ALB) and Amazon S3 buckets as storage service. For enhanced security, an AWS Web Application Firewall (AWS WAF) has been set up to monitor the requests coming to the ALB. The DevOps team needs to submit a quarterly report on the web requests received by AWS WAF, having detailed information about each web request as well as the details about rules that the request matched. The team has reached out to you for implementing the changes needed for collecting the security data for the coming months.

As DevOps Engineer, how will you implement this requirement?

Enable logging on AWS WAF and configure Amazon Kinesis Data Firehose with a configured storage destination as WAF logging destination. Configure Firehose to use a Kinesis stream as its source. Data firehose name should start with the prefix aws-waf-logs-

To send logs to Amazon CloudWatch Logs, create a CloudWatch Logs log group. When you enable logging in AWS WAF, provide the log group ARN as the WAF logging destination. Log group names must start with aws-waf-logs- and end with any suffix. Define CloudWatch Metrics for the logs collected and trigger CloudWatch alarm(s) based on the logs generated

Create an Amazon S3 bucket. Enable logging and provide an Amazon S3 bucket ARN as a WAF logging destination. Bucket names for AWS WAF logging must start with aws-waf-logs- and can end with any suffix you want. For added security, you can add log encryption configuration by providing AWS Key Management Service keys that are managed by AWS

6 / 19

A data analytics company wants to move all its clients belonging to the regulated and security-sensitive industries such as financial services and healthcare to the AWS Cloud as it wants to leverage the out-of-box security-specific capabilities offered by AWS. The DevOps team at the company is developing a framework to validate the adoption of AWS best practices and industry-recognized compliance standards. The AWS Management Console is the preferred method for the in-house teams wanting to provision resources.

Which of the following strategies would you adopt to address these business requirements for continuously assessing, auditing and monitoring the configurations of AWS resources? (Select two)

Leverage AWS Config rules to audit changes to AWS resources and monitor the compliance of the configuration by running the evaluations for the rule at a frequency that you choose. Develop AWS Config custom rules to establish a test-driven development approach by triggering the evaluation when any resource that matches the rule's scope changes in configuration

Enable trails and set up CloudTrail events to review and monitor management activities of all AWS accounts by logging these activities into CloudWatch Logs using a KMS key. Ensure that CloudTrail is enabled for all accounts as well as all available AWS services

Leverage CloudTrail integration with SNS to automatically notify unauthorized API activities. Ensure that CloudTrail is enabled for all accounts as well as all available AWS services. Use Lambda functions to automatically revert non-authorized changes in AWS resources

Leverage EventBridge events near-real-time capabilities to monitor system events patterns to trigger Lambda functions to automatically revert non-authorized changes in AWS resources. Send notifications via SNS topics to improve the incidence response time

Leverage CloudWatch Logs agent to collect all the AWS SDK logs. Search the log data using a pre-defined set of filter patterns that match mutating API calls. Use CloudWatch alarms to send notifications via SNS when unintended changes are performed. Archive log data by using a batch export to Amazon S3 and analyze via Athena

7 / 19

A company having hundreds of AWS accounts manages its operations and security through a single organization created in AWS Organizations. As per the company's policy, AWS Config and AWS CloudTrail are enabled for all accounts. The security policy mandates configuring AWS Web Application Firewall (AWS WAF) web ACLs for all internet-facing Application Load Balancers (ALBs) and Amazon API Gateway APIs. However, monthly audit reports consistently report unsecured ALBs and API Gateway APIs.

As a DevOps engineer, the security team has requested you to automate these configurations for all accounts to avoid oversight. What steps will you recommend?

Designate one of the AWS accounts in your organization as the administrator for Firewall Manager in AWS Organizations. Create an AWS Firewall Manager policy to attach AWS WAF web ACLs to any newly created ALBs and API Gateway APIs

Create an Amazon GuardDuty policy to attach AWS WAF web ACLs to any newly created ALBs and API Gateway APIs

Create an Amazon Systems Manager policy to attach AWS WAF web ACLs to any newly created ALBs and API Gateway APIs

Configure a managed rule in AWS Config to attach AWS WAF web ACLs to any newly created ALBs and API Gateway APIs

8 / 19

The security policy of a company mandates encrypting all AMIs that the company shares across its AWS accounts. An AWS account (Account A) has a custom AMI that is not encrypted. This AMI needs to be shared with another AWS Account B. Account B has Amazon EC2 instances configured with an Auto Scaling group that will use the AMI. Account A already has an AWS Key Management Service (AWS KMS) key.

As a DevOps Engineer, which combination of steps will you take to share the AMI with Account B while adhering to the company's security policy? (Select two)

In Account A, create an encrypted AMI from the unencrypted version and specify the KMS key in the copy action. Modify the key policy to give permissions to Account B for creating a grant. Share the encrypted AMI with Account B

In Account B, create a KMS grant that delegates permissions to the service-linked role attached to the Auto Scaling group

In Account A, create an encrypted AMI from the unencrypted version with AWS managed key. Modify the key policy to give permissions to Account B for creating a grant. Share the encrypted AMI with Account B

In Account A, create an encrypted AMI from the unencrypted version and encrypt the associated EBS snapshots with it. Specify the KMS key in the copy action. Share the encrypted AMI with Account B

In Account A, create an encrypted AMI from the unencrypted version and specify the KMS key in the copy action. Modify permissions on the AMI to be accessible from Account B

9 / 19

A company has configured AWS Organizations to manage its multiple AWS accounts. The company uses Amazon Elastic File System (Amazon EFS) as a shared storage service, configured in AWS Account A of the company. To implement a serverless architecture, the company has decided to move its applications to AWS Lambda. The Lambda functions will be managed through another AWS account (Account B). All the Lambda functions will be deployed in a VPC. A DevOps team needs help to continue using Amazon EFS in Account A with the Lambda function in Account B.

How will you reconfigure the existing EFS file system for use with AWS Lambda function? (Select two)

Create a VPC peering connection to connect Account A to Account B. Create Service control policies (SCPs) to set permission guardrails for access to Amazon EFS from AWS Lambda function execution role

Update the Lambda execution roles with permission to access the VPC and the EFS file system

Configure the Lambda functions in Account B to assume an existing IAM role in Account A for the cross-region, or cross-AZ connectivity between EFS and Lambda

Lambda charges for data transfer between VPCs. To manage costs, create a new EFS file system in Account B. Configure AWS DataSync to transfer data from EFS in Account B to EFS in Account B

Create a VPC peering connection to connect Account A to Account B. Update the EFS file system policy to provide Account B with access to mount and write to the EFS file system in Account A

10 / 19

A company uses serverless application architecture to process thousands of requests using AWS Lambda with Amazon DynamoDB as the database. The Amazon API Gateway REST API is used to invoke an AWS Lambda function that loads a large amount of data from the Amazon DynamoDB database. This results in cold start latencies of 7-10 seconds. The DynamoDB tables have already been configured with DynamoDB Accelerator (DAX) to reduce latency. Yet, customers report of application latency, especially during peak access hours. The application receives maximum traffic between 2 PM -5 PM every day and gradually reduces thereafter, reporting a minimum traffic post 8 PM.

How should a DevOps engineer configure the AWS Lambda function to reduce its latency at all times?

Configure the AWS Lambda function to use provisioned concurrency. Configure the application Auto Scaling on the Lambda function with provisioned concurrency values of 1 (minimum) and 100 (maximum) respectively

Configure the Lambda function execution environment to use up to 10,240 MB of ephemeral storage. This transient cache for data between invocations can be accessed from the Lambda function code via /tmp space

Use the Lambda function layers for parallel processing of Lambda runtime requests. Deploy the Lambda function as a .zip file archive to utilize Lambda layer functionality

Configure the AWS Lambda function to use Reserved concurrency. Configure the application Auto Scaling on the Lambda function with reserved concurrency as half of the Lambda function instances invoked during peak traffic hours

11 / 19

A developer configured an AWS CloudFormation template to create custom resource necessary for the project. The AWS Lambda function for the custom resource executed successfully as seen by the successful creation of the custom resource. But, the CloudFormation stack is not transitioning from in-progress status (CREATE_IN_PROGRESS) to completion status (CREATE_COMPLETE).

Which step did the developer possibly miss for the successful completion of the CloudFormation stack?

Configure the AWS Lambda function to send the response(SUCCESS or FAILED) of the custom resource creation to a pre-signed Amazon Simple Storage Service URL

After executing the send method in the cfn-response module, the Lambda function terminates, so anything written after this method is ignored

If the template developer and custom resource provider are configured to the same person or entity then CloudFormation stack completion fails

The AWS CloudFormation resource AWS::CloudFormation::CustomResource should be used to specify a custom resource in the template

12 / 19

In a multinational company, various AWS accounts are efficiently managed using AWS Control Tower. The company operates both internal and public applications across its infrastructure. To streamline operations, each application team is assigned a dedicated AWS account responsible for hosting their respective applications. These accounts are consolidated under an organization in AWS Organizations. Additionally, a specific AWS Control Tower member account acts as a centralized DevOps hub, offering Continuous Integration/Continuous Deployment (CI/CD) pipelines that application teams utilize to deploy applications to their designated AWS accounts. A specialized IAM role for deployment is available within this central DevOps account.

Currently, a particular application team is facing challenges while attempting to deploy its application to an Amazon Elastic Kubernetes Service (Amazon EKS) cluster situated in their application-specific AWS account. They have an existing IAM role for deployment within the application AWS account. The deployment process relies on an AWS CodeBuild project, configured within the centralized DevOps account, and utilizes an IAM service role for CodeBuild. However, the deployment process is encountering an Unauthorized error when trying to establish connections to the cross-account EKS cluster from the CodeBuild environment.

To resolve this error and facilitate a successful deployment, what solution would you recommend?

Establish a trust relationship in the centralized DevOps account for the application account's deployment IAM role, allowing the sts:AssumeRole action. Also, grant the application account's deployment IAM role the necessary access to the EKS cluster. Additionally, configure the EKS cluster aws-auth ConfigMap to map the role to the appropriate system permissions

Establish a trust relationship in the application account's deployment IAM role for the centralized DevOps account, allowing the sts:AssumeRole action. Also, grant the application account's deployment IAM role the necessary access to the EKS cluster. Additionally, configure the EKS cluster aws-auth ConfigMap to map the role to the appropriate system permissions

Establish a trust relationship in the application account's deployment IAM role for the centralized DevOps account, allowing the sts:AssumeRoleWithSAML action. Also, grant the centralized DevOps account's deployment IAM role the required access to CodeBuild and the EKS cluster

Establish a trust relationship in the centralized DevOps account's deployment IAM role for the application account, allowing the sts:AssumeRoleWithSAML action. Also, grant the centralized DevOps account's deployment IAM role the required access to CodeBuild

13 / 19

A company has hired you as an AWS Certified DevOps Engineer - Professional to provide recommendations for a failed security audit of its flagship project. You have been tasked to review the company's buildspec.yaml file for its AWS CodeBuild project. Upon investigation, you have noticed that the file has hard-coded values for the environment variables that reference the AWS Access Key ID, Secret Access Key, and the database password. In addition, to perform one-time configuration changes during the build phase, the file has commands to ssh and scp into an EC2 instance using an SSH private key stored on Amazon S3.

What changes would you recommend to comply with AWS security best practices? (Select three)

Store the database password as a SecureString value in AWS Systems Manager Parameter Store which is then referenced in the buildspec environment. Also, delete the environment variable referencing the hard-coded value of the database password from the buildspec.yaml file

Leverage the AWS Systems Manager automation document to manage the EC2 instance, rather than using commands to ssh and scp into the EC2 instance via the SSH private key stored on Amazon S3

Leverage the AWS Systems Manager run command to manage the EC2 instance, rather than using commands to ssh and scp into the EC2 instance via the SSH private key stored on Amazon S3

Store the environment variables that reference the AWS Access Key ID, Secret Access Key, and the database password in an encrypted format on Amazon S3. Leverage a Python script to dynamically import the values from S3 during the pre-build phase

Store the database password as a SecureString value in AWS Secrets Manager which is then referenced in the buildspec environment. Also, delete the environment variable referencing the hard-coded value of the database password from the buildspec.yaml file

Configure the CodeBuild project role with the necessary permissions policy and then delete the environment variables referencing the AWS credentials from the buildspec.yaml file

14 / 19

An application runs on a fleet of Amazon EC2 instances that are configured with an Auto Scaling group (ASG). Both Spot and On-Demand instances are utilized as per the ASG configuration. For the most part, the ASG seems to be working fine as expected. There are a few issues that the DevOps team has flagged:

a) During a scale-in activity, ASG has terminated instance in the Availability Zone (AZ) that already had fewer instances than the other b) For some duration, ASG exceeded the specified maximum capacity of the group

What reasons can you identify for this behavior? (Select two)

With Default termination policy, instances that are closest to the next billing hour are terminated first. This can temporarily cause instance distribution imbalance among the AZs

You can only specify one Lambda function in the termination policies for an Auto Scaling group. If more than one Lambda functions are configured, the ASG behavior is ambiguous

The instance that was launched from the oldest launch template or launch configuration is terminated first. This can temporarily lead to an unbalanced group

Amazon EC2 Auto Scaling can temporarily exceed the specified maximum capacity of a group by a 10 percent margin (or by a margin of one instance, whichever is greater) during a rebalancing activity

When an Auto Scaling group with a mixed instances policy scales in, Amazon EC2 Auto Scaling will first identify which of the two types (Spot or On-Demand) should be terminated. This can temporarily cause a misbalance between the AZs

15 / 19

A web application is hosted on Amazon EC2 instances behind an Application Load Balancer (ALB). While using CodeDeploy Blue/Green deployment to deploy a new version, the deployment failed during the AllowTraffic lifecycle event. The DevOps team has found no errors in the deployment logs.

Which of the following would you identify as the root cause behind the failure of the deployment?

The cause of the failure could be a script from the last successful deployment that never runs successfully. Create a new deployment and specify that the ApplicationStop, BeforeBlockTraffic, and AfterBlockTraffic failures should be ignored

If an instance is terminated between lifecycle events or before the first lifecycle event step starts, then AllowTraffic lifecycle event fails without generating logs

A scale-in event or any other termination event, during an in-progress deployment, causes the instance to detach from the Amazon EC2 Auto Scaling group and the instance fails the AllowTraffic lifecycle event

Incorrectly configured health checks on Application Load Balancer (ALB) are responsible for this issue

16 / 19

During an AWS CloudFormation stack update process, an error occurred in the updated template, causing AWS CloudFormation to initiate an automatic stack rollback. After the rollback attempt, a DevOps engineer noticed that the application remained unavailable, and the stack is now in the UPDATE_ROLLBACK_FAILED state.

To ensure the successful completion of the stack rollback, which actions should the DevOps engineer take? (Select two)

Automatically fix the issue by using AWS CloudFormation stack sets

Automatically fix the issue by using AWS CloudFormation drift detection

Execute a ContinueUpdateRollback command from the AWS CloudFormation

Manually fix the resources to match the correct state of the stack

Update the existing AWS CloudFormation stack by using the original template

17 / 19

A company uses an AWS CodePipeline pipeline to deploy updates to the API several times a month. As part of this process, the DevOps team exports the JavaScript SDK for the API from the API Gateway console and uploads it to an Amazon S3 bucket, which is being used as an origin for an Amazon CloudFront distribution. Web clients access the SDK through the CloudFront distribution's endpoint. The goal is to have an automated solution that ensures the latest SDK is always available to clients whenever there's a new API deployment.

As an AWS Certified DevOps Engineer - Professional, what solution will you suggest?

Set up a CodePipeline action that runs immediately after the API deployment stage. Configure this action to leverage the CodePipeline integration with API Gateway to export the SDK to Amazon S3. Trigger another action that calls the S3 API to invalidate the cache for the SDK path

Set up an Amazon EventBridge rule that reacts to CreateDeployment events from aws.apigateway. Configure this rule to leverage the CodePipeline integration with API Gateway to export the SDK to Amazon S3. Trigger another action that calls the S3 API to invalidate the cache for the SDK path

Set up a CodePipeline action that runs immediately after the API deployment stage. Configure this action to invoke an AWS Lambda function. The Lambda function will then download the SDK from API Gateway, upload it to the S3 bucket, and create a CloudFront invalidation for the SDK path

Set up an Amazon EventBridge rule on a schedule that is invoked every 5 minutes. Configure this rule to invoke an AWS Lambda function. The Lambda function will then download the SDK from API Gateway, upload it to the S3 bucket, and create a CloudFront invalidation for the SDK path

18 / 19

A company provides an application to customers. The application has an Amazon API Gateway REST API that invokes an AWS Lambda function. On initialization, the Lambda function loads a large amount of data from an Amazon DynamoDB table. The data load process results in long cold-start times of 8-10 seconds. The DynamoDB table has DynamoDB Accelerator (DAX) configured. Customers report that the application intermittently takes a long time to respond to requests. The application receives thousands of requests throughout the day. In the middle of the day, the application experiences 10 times more requests than at any other time of the day. Near the end of the day, the application's request volume decreases to 10% of its normal total. A DevOps engineer needs to reduce the latency of the Lambda function at all times of the day. Which solution will meet these requirements?

Configure provisioned concurrency on the Lambda function with a concurrency value of 1. Delete the DAX cluster for the DynamoDB table.

Configure reserved concurrency on the Lambda function with a concurrency value of 0.

Configure provisioned concurrency on the Lambda function. Configure AWS Application Auto Scaling on the Lambda function with provisioned concurrency values set to a minimum of 1 and a maximum of 100.

Configure reserved concurrency on the Lambda function. Configure AWS Application Auto Scaling on the API Gateway API with a reserved concurrency maximum value of 100.

19 / 19

A company has a mobile application that makes HTTP API calls to an Application Load Balancer (ALB). The ALB routes requests to an AWS Lambda function. Many different versions of the application are in use at any given time, including versions that are in testing by a subset of users. The version of the application is defined in the user-agent header that is sent with all requests to the API. After a series of recent changes to the API, the company has observed issues with the application. The company needs to gather a metric for each API operation by response code for each version of the application that is in use. A DevOps engineer has modified the Lambda function to extract the API operation name, version information from the user-agent header and response code. Which additional set of actions should the DevOps engineer take to gather the required metrics?

Modify the Lambda function to write the API operation name, response code, and version number as a log line to an Amazon CloudWatch Logs log group. Configure a CloudWatch Logs metric filter that increments a metric for each API operation name. Specify response code and application version as dimensions for the metric.

Modify the Lambda function to write the API operation name, response code, and version number as a log line to an Amazon CloudWatch Logs log group. Configure a CloudWatch Logs Insights query to populate CloudWatch metrics from the log lines. Specify response code and application version as dimensions for the metric.

Configure the ALB access logs to write to an Amazon CloudWatch Logs log group. Modify the Lambda function to respond to the ALB with the API operation name, response code, and version number as response metadata. Configure a CloudWatch Logs metric filter that increments a metric for each API operation name. Specify response code and application version as dimensions for the metric.

Configure AWS X-Ray integration on the Lambda function. Modify the Lambda function to create an X-Ray subsegment with the API operation name, response code, and version number. Configure X-Ray insights to extract an aggregated metric for each API operation name and to publish the metric to Amazon CloudWatch. Specify response code and application version as dimensions for the metric.

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