Amazon DOP-C02 Practice Test - Questions Answers, Page 21

To meet the requirements, the DevOps engineer needs to configure the CloudWatch alarm to stop the EC2 instances when the average of the NetworkPacketsIn metric is less than 5 for at least 3 hours in a 12-hour time window. This means that the alarm should trigger when 3 out of 12 datapoints are below the threshold of 5. The alarm should also treat missing data as not breaching the threshold, so that the EC2 instances continue to run if there is no data for the metric during the evaluation period. The DevOps engineer can add an EC2 action to stop the instance when the alarm enters the ALARM state, which is a built-in action type for CloudWatch alarms.

To meet the requirements, the DevOps team needs to configure a monitoring solution for the VPC flow logs that can detect anomalies in network traffic over time and initiate a response to the anomaly. The DevOps team can use Amazon Kinesis Data Streams to ingest and process streaming data from CloudWatch Logs. The DevOps team can subscribe the log group to a Kinesis data stream, which will deliver log events from CloudWatch Logs to Kinesis Data Streams in near real-time. The DevOps team can then create an AWS Lambda function to detect log anomalies using machine learning or statistical methods. The Lambda function can be set as a processor for the data stream, which means that it will process each record from the stream before sending it to downstream applications or destinations. The Lambda function can also write to the default Amazon EventBridge event bus if it detects an anomaly, which will allow other AWS services or custom applications to respond to the anomaly event.

The correct answer is C, Allowing users to deploy CloudFormation stacks using AWS Service Catalog only and enforcing the use of a launch constraint is the best way to ensure that the internal business teams launch resources through pre-approved CloudFormation templates only. AWS Service Catalog is a service that enables organizations to create and manage catalogs of IT services that are approved for use on AWS. A launch constraint is a rule that specifies the role that AWS Service Catalog assumes when launching a product. By using a launch constraint, the DevOps engineer can control the permissions that the users have when launching a product. Using AWS Config rules to detect when resources have drifted from their expected state is the best way to automate the monitoring of the resources. AWS Config is a service that enables you to assess, audit, and evaluate the configurations of your AWS resources. AWS Config rules are custom or managed rules that AWS Config uses to evaluate whether your AWS resources comply with your desired configurations. By using AWS Config rules, the DevOps engineer can track the changes in the resources and identify any non-compliant resources.

Option A is incorrect because allowing users to deploy CloudFormation stacks using a CloudFormation service role only is not the best way to ensure that the internal business teams launch resources through pre-approved CloudFormation templates only. A CloudFormation service role is an IAM role that CloudFormation assumes to create, update, or delete the stack resources. By using a CloudFormation service role, the DevOps engineer can control the permissions that CloudFormation has when acting on the resources, but not the permissions that the users have when launching a stack. Therefore, option A does not prevent the users from launching resources that are not approved by the company. Using CloudFormation drift detection to detect when resources have drifted from their expected state is a valid way to monitor the resources, but it is not as automated and scalable as using AWS Config rules. CloudFormation drift detection is a feature that enables you to detect whether a stack's actual configuration differs, or has drifted, from its expected configuration. To use this feature, the DevOps engineer would need to manually initiate a drift detection operation on the stack or the stack resources, and then view the drift status and details in the CloudFormation console or API.

Option B is incorrect because allowing users to deploy CloudFormation stacks using a CloudFormation service role only is not the best way to ensure that the internal business teams launch resources through pre-approved CloudFormation templates only, as explained in option A. Using AWS Config rules to detect when resources have drifted from their expected state is a valid way to monitor the resources, as explained in option C,

Option D is incorrect because enforcing the use of a template constraint is not the best way to ensure that the internal business teams launch resources through pre-approved CloudFormation templates only. A template constraint is a rule that defines the values or properties that users can specify when launching a product. By using a template constraint, the DevOps engineer can control the parameters that the users can provide when launching a product, but not the permissions that the users have when launching a product. Therefore, option D does not prevent the users from launching resources that are not approved by the company. Using Amazon EventBridge notifications to detect when resources have drifted from their expected state is a less reliable and consistent solution than using AWS Config rules. Amazon EventBridge is a service that enables you to connect your applications with data from a variety of sources. Amazon EventBridge can deliver a stream of real-time data from event sources, such as AWS services, and route that data to targets, such as AWS Lambda functions. However, to use this solution, the DevOps engineer would need to configure the event source, the event bus, the event rule, and the event target for each resource type that needs to be monitored, which is more complex and error-prone than using AWS Config rules.

The UserData property of the AWS: AutoScaling: LaunchConfiguration resource can be used to specify a script that runs when the EC2 instances are launched. This script can include the ECS cluster name as an environment variable for the ECS agent running on the EC2 instances. This way, the EC2 instances will register with the correct ECS cluster. Option A is incorrect because the AWS: ECS: Cluster resource does not have a property to reference the EC2 instances. Option C is incorrect because the EC2 instances are launched by the Auto Scaling group, not by the AWS: EC2: Instance resource. Option D is incorrect because using a custom resource and a Lambda function is unnecessary and overly complex for this scenario.Reference:AWS::AutoScaling::LaunchConfiguration,Amazon ECS Container Agent Configuration

For deploying a Ruby-based application with requirements for interaction with an Amazon RDS for MySQL database, automatic scaling, high availability, and data persistence, the following steps will meet the requirements:

B) Deploy the application on AWS Elastic Beanstalk. Deploy a separate Amazon RDS for MySQL DB instance outside of Elastic Beanstalk.This approach ensures that the database persists independently of the Elastic Beanstalk environment, which can be torn down and recreated without affecting the database123.

E) Use the immutable deployment method to deploy new application versions.Immutable deployments provide a zero-downtime deployment method that ensures that if any part of the deployment process fails, the environment is rolled back to the original state automatically4.

D) Configure an Amazon EventBridge rule to monitor AWS Health events. Use an Amazon Simple Notification Service (Amazon SNS) topic as a target to alert the application team.This setup allows for automated monitoring and alerting of the application team in case of deployment failures or other health events56.

AWS Elastic Beanstalk documentation on deploying Ruby applications1.

AWS documentation on application auto-scaling7.

AWS documentation on automated deployment strategies with automatic rollbacks and alerts456.

To meet the new guideline for application deployment, the company can use a combination of AWS CodePipeline and AWS CloudTrail. A manual approval action in CodePipeline allows the security team to review and approve changes before they are deployed. This action can be configured to pause the pipeline until approval is granted, ensuring that no changes move to production without the necessary sign-off. Additionally, by creating an AWS CloudTrail trail, all actions taken within CodePipeline, including approvals, are recorded and delivered to an Amazon S3 bucket. This provides an audit trail that can be retained for compliance and review purposes.

AWS CodePipeline's manual approval action provides a way to ensure that a member of the security team can review and approve changes before they are deployed1.

AWS CloudTrail integration with CodePipeline allows for the recording and retention of all pipeline actions, including approvals, which can be stored in Amazon S3 for record-keeping2.

The most cost-effective solution to meet the RTO and RPO requirements is option B. This option involves copying the CloudFormation templates to an Amazon S3 bucket in the DR Region, configuring Aurora automated backup Cross-Region Replication, and configuring ECR Cross-Region Replication. In the event of a disaster, the CloudFormation template with the most recent Aurora snapshot and the Docker image from the local ECR repository can be used to launch a new CloudFormation stack in the DR Region. This approach avoids the need to build Docker images from the Dockerfile, which can sometimes take more than 2 hours, thus meeting the RTO requirement. Additionally, the use of automated backups and replication ensures that the RPO of 8 hours is met.

AWS Documentation on Disaster Recovery:Plan for Disaster Recovery (DR) - Reliability Pillar

AWS Blog on Establishing RPO and RTO Targets:Establishing RPO and RTO Targets for Cloud Applications

AWS Documentation on ECR Cross-Region Replication: Amazon ECR Cross-Region Replication

AWS Documentation on Aurora Cross-Region Replication: Replicating Amazon Aurora DB Clusters Across AWS Regions

To analyze and find the number of logins for a specific user from the past 7 days, a CloudWatch Logs Insights query is the most suitable solution. CloudWatch Logs Insights enables you to interactively search and analyze your log data in Amazon CloudWatch Logs. You can use the query language to perform queries that contain multiple commands, including aggregation functions, which can count the occurrences of logins for a specific username over a specified time period. This approach is more direct and efficient than creating a metric filter or subscription, which would require additional steps to publish and sum a metric.Reference:AWS Certified DevOps Engineer - Professional,CloudWatch Logs Insights query syntax,Tutorial: Run a query with an aggregation function,Add or remove a number widget from a CloudWatch dashboard.

* Create an Amazon Elastic File System (Amazon EFS) File System with Targets in Multiple Availability Zones:

Amazon EFS provides a scalable and highly available network file system that supports the NFS protocol. EFS is ideal for Linux instances as it allows multiple instances to read and write data concurrently.

Setting up EFS with targets in multiple Availability Zones ensures high availability and durability.

* Create an Amazon FSx for NetApp ONTAP Multi-AZ File System:

Amazon FSx for NetApp ONTAP offers a fully managed file storage solution that supports both SMB for Windows and NFS for Linux.

The Multi-AZ deployment ensures high availability and durability, providing sub-millisecond latencies suitable for the application's performance requirements.

* Update the User Data for Each Application's Launch Template to Mount the File System:

Updating the user data in the launch template ensures that every new instance launched by the Auto Scaling group will automatically mount the appropriate file system.

This step is necessary to ensure that all instances can access the shared storage without manual intervention.

Example user data for mounting EFS (Linux)

#!/bin/bash

sudo yum install -y amazon-efs-utils

sudo mount -t efs fs-12345678:/ /mnt/efs

Example user data for mounting FSx (Windows):

By implementing these steps, the company can provide a durable storage solution with sub-millisecond latencies that supports both SMB and NFS protocols, meeting the requirements for both Windows and Linux instances.

Mounting EFS File Systems

Mounting Amazon FSx File Systems