DOP-C02 : BUNDLE PACK LEARNING TOOLS INCLUDED

DOP-C02 AWS Certified DevOps Engineer - Professional Exam

The AWS Certified DevOps Engineer - Professional showcases individuals’ technical expertise in provisioning, operating, and managing distributed application systems on the AWS platform, giving them increased confidence and credibility with peers, stakeholders, and customers. Organizations with these qualified professionals can ensure speedy delivery of secure, compliant, systems that are highly available and scalable.

Did you know? Job listings requiring this certification have increased by 52% between Oct 2021 and Sept 2022 (source: Lightcast™ September 2022).

Exam overview
Level: Professional
Length: 180 minutes to complete the exam
Format: 75 questions, either multiple choice or multiple response.

Recommended AWS knowledge
The target candidate has the following:
• Experience in building highly automated infrastructure
• Experience in administering operating systems
• Experience with modern development and operations processes and methodologies
• Experience in securing AWS infrastructure


Exam Topics
Domain 1: SDLC Automation 22%
Domain 2: Configuration Management and IaC 17%
Domain 3: Resilient Cloud Solutions 15%
Domain 4: Monitoring and Logging 15%
Domain 5: Incident and Event Response 14%
Domain 6: Security and Compliance 17%
TOTAL 100%

Who should take this exam?
AWS Certified DevOps Engineer - Professional is intended for individuals with two or more years of experience provisioning, operating, and managing AWS environments. Before you take this exam, we recommend you have:

Experience developing code in at least one high-level programming language; building highly automated infrastructures; and administering operating systems
Understanding of modern development and operations processes and methodologies
Ability to implement and manage continuous delivery systems and methodologies on AWS
Ability to implement and automate security controls, governance processes, and compliance validation
Ability to define and deploy monitoring, metrics, and logging systems on AWS

What does it take to earn this certification?
To earn this certification, you’ll need to take and pass the AWS Certified DevOps Engineer - Professional exam (DOP-C02). The exam features a combination of two question formats: multiple choice and multiple response. Additional information, such as the exam content outline and passing score, is in the exam guide.

Review sample questions that demonstrate the format of the questions used on this exam and include rationales for the correct answers.

Prepare for your exam
You’ve set your goal. Now it’s time to build knowledge and skills to propel your career. Check out these resources from AWS Training and Certification that are relevant to AWS Certified DevOps Engineer - Professional. We don’t require that you take any specific training before you take an exam. These recommended resources are opportunities to learn from the experts at AWS.

Additional resources – including AWS Builder Labs and game-based learning to complement your prep – are available with a subscription on AWS Skill Builder.

Select a resource type from the section below to learn more.

 

QUESTION 1
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?

A. 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.

B. 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.

C. 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.

D. 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 XRay
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.

Answer: B

QUESTION 2
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?

A. Configure provisioned concurrency on the Lambda function with a concurrency value of 1. Delete the DAX cluster for the DynamoDB table.
B. Configure reserved concurrency on the Lambda function with a concurrency value of 0.
C. 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.
D. 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.

Answer: C

QUESTION 3
A company is adopting AWS CodeDeploy to automate its application deployments for a Java-Apache
Tomcat application with an Apache Webserver. The development team started with a proof of
concept, created a deployment group for a developer environment, and performed functional tests
within the application. After completion, the team will create additional deployment groups for
staging and production.
The current log level is configured within the Apache settings, but the team wants to change this
configuration dynamically when the deployment occurs, so that they can set different log level
configurations depending on the deployment group without having a different application revision
for each group.
How can these requirements be met with the LEAST management overhead and without requiring
different script versions for each deployment group?

A. Tag the Amazon EC2 instances depending on the deployment group. Then place a script into the
application revision that calls the metadata service and the EC2 API to identify which deployment
group the instance is part of. Use this information to configure the log level settings. Reference the
script as part of the AfterInstall lifecycle hook in the appspec.yml file.

B. Create a script that uses the CodeDeploy environment variable DEPLOYMENT_GROUP_ NAME to
identify which deployment group the instance is part of. Use this information to configure the log
level settings. Reference this script as part of the BeforeInstall lifecycle hook in the appspec.yml file.

C. Create a CodeDeploy custom environment variable for each environment. Then place a script into
the application revision that checks this environment variable to identify which deployment group
the instance is part of. Use this information to configure the log level settings. Reference this script as
part of the ValidateService lifecycle hook in the appspec.yml file.

D. Create a script that uses the CodeDeploy environment variable DEPLOYMENT_GROUP_ID to
identify which deployment group the instance is part of to configure the log level settings. Reference
this script as part of the Install lifecycle hook in the appspec.yml file.

Answer: B

QUESTION 4
A company requires its developers to tag all Amazon Elastic Block Store (Amazon EBS) volumes in an
account to indicate a desired backup frequency. This requirement Includes EBS volumes that do not
require backups. The company uses custom tags named Backup_Frequency that have values of none,
dally, or weekly that correspond to the desired backup frequency. An audit finds that developers are
occasionally not tagging the EBS volumes.
A DevOps engineer needs to ensure that all EBS volumes always have the Backup_Frequency tag so
that the company can perform backups at least weekly unless a different value is specified.
Which solution will meet these requirements?

A. Set up AWS Config in the account. Create a custom rule that returns a compliance failure for all
Amazon EC2 resources that do not have a Backup Frequency tag applied. Configure a remediation
action that uses a custom AWS Systems Manager Automation runbook to apply the
Backup_Frequency tag with a value of weekly.

B. Set up AWS Config in the account. Use a managed rule that returns a compliance failure for
EC2::Volume resources that do not have a Backup Frequency tag applied. Configure a remediation
action that uses a custom AWS Systems Manager Automation runbook to apply the
Backup_Frequency tag with a value of weekly.

C. Turn on AWS CloudTrail in the account. Create an Amazon EventBridge rule that reacts to EBS
CreateVolume events. Configure a custom AWS Systems Manager Automation runbook to apply the
Backup_Frequency tag with a value of weekly. Specify the runbook as the target of the rule.

D. Turn on AWS CloudTrail in the account. Create an Amazon EventBridge rule that reacts to EBS
CreateVolume events or EBS ModifyVolume events. Configure a custom AWS Systems Manager
Automation runbook to apply the Backup_Frequency tag with a value of weekly. Specify the runbook
as the target of the rule.

Answer: B

QUESTION 5
A company is using an Amazon Aurora cluster as the data store for its application. The Aurora cluster
is configured with a single DB instance. The application performs read and write operations on the
database by using the cluster's instance endpoint.
The company has scheduled an update to be applied to the cluster during an upcoming maintenance
window. The cluster must remain available with the least possible interruption during the
maintenance window.
What should a DevOps engineer do to meet these requirements?

A. Add a reader instance to the Aurora cluster. Update the application to use the Aurora cluster
endpoint for write operations. Update the Aurora cluster's reader endpoint for reads.

B. Add a reader instance to the Aurora cluster. Create a custom ANY endpoint for the cluster. Update
the application to use the Aurora cluster's custom ANY endpoint for read and write operations.

C. Turn on the Multi-AZ option on the Aurora cluster. Update the application to use the Aurora cluster
endpoint for write operations. Update the Aurora cluster’s reader endpoint for reads.

D. Turn on the Multi-AZ option on the Aurora cluster. Create a custom ANY endpoint for the cluster.
Update the application to use the Aurora cluster's custom ANY endpoint for read and write
operations.

Answer: B