DOP-C02 Practice Exam Questions with Answers AWS Certified DevOps Engineer - Professional Certification

https://docs.aws.amazon.com/AmazonCloudWatch/latest/logs/SubscriptionFilters.html#LambdaFunctionExample

https://docs.aws.amazon.com/AmazonCloudWatch/latest/logs/SubscriptionFilters.html

This solution will meet the requirements in the most operationally efficient manner because it will use CloudWatch Logs destination to aggregate the log groups from all the accounts to a single S3 bucket in the logging account. However, unlike option A, this solution will create a CloudWatch Logs destination for each region, instead of a single destination for all regions. This will improve the performance and reliability of the log delivery, as it will avoid cross-region data transfer and latency issues. Moreover, this solution will use an Amazon Kinesis data stream and an Amazon Kinesis Data Firehose delivery stream for each region, instead of a single stream for all regions. This will also improve the scalability and throughput of the log delivery, as it will avoid bottlenecks and throttling issues that may occur with a single stream.

https://docs.aws.amazon.com/codecommit/latest/userguide/how-to-amazon-codeguru-reviewer.html

• To aggregate logs from multiple accounts in an organization, the DevOps engineer needs to create a cross-account subscription1 that allows the monitoring account to receive log events from the sharing accounts.
• To enable cross-account subscription, the DevOps engineer needs to create an IAM role in each sharing account that grants permission to CloudWatch Logs to link the log groups to the destination in the monitoring account2. This can be done using a CloudFormation template and StackSets3 to deploy the role to all accounts in the organization.
• The DevOps engineer also needs to create an IAM role in the monitoring account that allows CloudWatch Logs to create a sink for receiving log events from other accounts4. The role must have a trust policy that specifies the organization ID as a condition.
• Finally, the DevOps engineer needs to attach the CloudWatchLogsReadOnlyAccess policy5 to an IAM role in the monitoring account that can be used to search the logs from the cross-account subscription.

References: 1: Cross-account log data sharing with subscriptions 2: Create an IAM role for CloudWatch Logs in each sharing account 3: AWS CloudFormation StackSets 4: Create an IAM role for CloudWatch Logs in your monitoring account 5: CloudWatchLogsReadOnlyAccess policy

To meet the requirements, the company needs to create a solution that alerts the Senior Manager when the creation of resources approaches the service limits for the account with the least amount of development effort. The company can use AWS Trusted Advisor, which is a service that provides best practice recommendations for cost optimization, performance, security, and service limits. The company can deploy an AWS Lambda function that refreshes Trusted Advisor checks, and configure an Amazon CloudWatch Events rule to run the Lambda function periodically. This will ensure that Trusted Advisor checks are up to date and reflect the current state of the account. The company can then create another CloudWatch Events rule with an event pattern matching Trusted Advisor events and a target Lambda function. The event pattern can filter for events related to service limit checks and their status. The target Lambda function can notify the Senior Manager via a third-party API call if the event indicates that the account is approaching or exceeding a service limit.

https://aws.amazon.com/quickstart/architecture/blue-green-deployment/

AWS CloudWatch Events can be used to monitor events across different AWS resources, and a CloudWatch Event Rule can be created to trigger an AWS Lambda function when a deployment issue is detected in the pipeline. The Lambda function can then evaluate the issue and send a notification to the appropriate stakeholders through an Amazon SNS topic. This approach allows for real-time notifications and faster resolution times.

This solution will meet the requirements because it will use a CloudFormation custom resource to execute custom logic during the stack set operation. A custom resource is a resource that you define in your template and that is associated with an AWS Lambda function. The Lambda function runs whenever the custom resource is created, updated, or deleted, and can perform any actions that are supported by the AWS SDK. In this case, the Lambda function can use the GuardDuty API to check whether GuardDuty is already enabled in each target account, and if not, enable it. This way, the DevOps engineer can avoid deploying the stack set to accounts that already have GuardDuty enabled, and prevent failure during the deployment.

This solution would allow the company to automate the process of updating the SDK and making it available to web clients. By adding a CodePipeline action immediately after the deployment stage of the API, the Lambda function will be invoked automatically each time the API is updated. The Lambda function should be able to download the new SDK from API Gateway, upload it to the S3 bucket and also create a CloudFront invalidation for the SDK path so that the latest version of the SDK is available for the web clients. This is the most straight forward solution and it will meet the requirements.

https://docs.aws.amazon.com/storagegateway/latest/APIReference/API_RefreshCache.html " It only updates the cached inventory to reflect changes in the inventory of the objects in the S3 bucket. This operation is only supported in the S3 File Gateway types."

The correct answer is D. Creating an AWS Config conformance pack that contains the AWS Config rules and remediation actions and deploying it from the delegated administrator account by using AWS Config will meet the requirements. A conformance pack is a collection of AWS Config rules and remediation actions that can be easily deployed as a single entity in an account and a region or across an organization in AWS Organizations1. By using the delegated administrator account, the DevOps engineer can centrally manage the conformance pack and prevent non-administrator users from modifying it in the member accounts. Option A is incorrect because creating a CloudFormation template that contains the AWS Config rules and remediation actions and deploying it from the Organizations management account by using CloudFormation StackSets will not prevent non-administrator users from modifying the AWS Config rules in the member accounts. Option B is incorrect because deploying the conformance pack from the Organizations management account by using CloudFormation StackSets will not use the trusted access feature of AWS Config and will require additional permissions and resources. Option C is incorrect because creating a CloudFormation template that contains the AWS Config rules and remediation actions and deploying it from the delegated administrator account by using AWS Config will not leverage the benefits of conformance packs, such as simplified deployment and management. References:

• Conformance Packs - AWS Config
• Certified DevOps Engineer - Professional (DOP-C02) Study Guide (page 176)

https://aws.amazon.com/premiumsupport/knowledge-center/monitor-security-group-changes-ec2/

The problem is that the DevOps engineer cannot assume the OrganizationAccountAccessRole IAM role in the new member account that joined AnyCompany’s management account through an Organizations invitation. The solution is to create a new IAM role with the same name and trust policy in the new member account.

• Option A is incorrect, as it does not address the root cause of the error. The DevOps engineer’s IAM user already has permission to assume the OrganizationAccountAccessRole IAM role in any member account, as this is the default role name that AWS Organizations creates when a new account joins an organization. The error occurs because the new member account does not have this role, as it was not created by AWS Organizations.
• Option B is incorrect, as it does not address the root cause of the error. An SCP is a policy that defines the maximum permissions for account members of an organization or organizational unit (OU). An SCP does not grant permissions to IAM users or roles, but rather limits the permissions that identity-based policies or resource-based policies grant to them. An SCP also does not affect how IAM roles are assumed by other principals.
• Option C is correct, as it addresses the root cause of the error. By creating a new IAM role with the same name and trust policy as the OrganizationAccountAccessRole IAM role in the new member account, the DevOps engineer can assume this role and access the account. The new role should have the AdministratorAccess AWS managed policy attached, which grants full access to all AWS resources in the account. The trust policy should allow the management account to assume the role, which can be done by specifying the management account ID as a principal in the policy statement.
• Option D is incorrect, as it assumes that the new member account already has the OrganizationAccountAccessRole IAM role, which is not true. The new member account does not have this role, as it was not created by AWS Organizations. Editing the trust policy of a non-existent role will not solve the problem.

The correct answer is D. The scenario requires a solution that can migrate an application from on premises to AWS, run on specific versions of Apache Tomcat, HAProxy, and Varnish Cache, tune the operating system-level parameters, automate the deployment of new application versions, and scale and replace faulty servers automatically. Option D meets all these requirements by using AWS CodeCommit, AWS CodeDeploy, AWS CodePipeline, and Amazon EC2 Auto Scaling. AWS CodeCommit is a fully managed source control service that hosts Git repositories and works with Git-based tools. AWS CodeDeploy is a fully managed deployment service that automates software deployments to a variety of compute services, including Amazon EC2, AWS Fargate, AWS Lambda, and on-premises servers. AWS CodePipeline is a fully managed continuous delivery service that helps automate the release pipelines for fast and reliable application updates. Amazon EC2 Auto Scaling helps maintain application availability and allows scaling of Amazon EC2 capacity up or down automatically according to the defined conditions. By using these services together, the DevOps engineer can migrate the application code to AWS, configure and install the necessary software using the appspec.yml file, automate the deployment process using the pipeline, and scale and replace the servers using the Auto Scaling group.

Option A is incorrect because AWS Fargate is a serverless compute engine for containers that works with Amazon ECS and Amazon EKS. Fargate removes the need to provision and manage servers, but it also limits the ability to tune the operating system-level parameters, which is a requirement in the scenario. Moreover, Fargate does not support HAProxy and Varnish Cache as sidecar containers, which are needed to run the application properly.

Option B is incorrect because AWS Elastic Beanstalk is a fully managed service that automates the deployment and scaling of web applications and services using familiar servers such as Apache, Nginx, Passenger, and IIS. However, Elastic Beanstalk does not support HAProxy and Varnish Cache as part of the Tomcat solution stack, which are needed to run the application properly. Moreover, Elastic Beanstalk web server tier environments are designed to serve HTTP requests, not to process background tasks, which is the purpose of worker tier environments.

Option C is incorrect because AWS Elastic Beanstalk worker tier environments are designed to process background tasks using a daemon process that runs on each Amazon EC2 instance in the environment. Worker tier environments are not suitable for running web applications that serve HTTP requests, which is the case in the scenario. Moreover, Elastic Beanstalk does not support HAProxy and Varnish Cache as part of the Tomcat solution stack, which are needed to run the application properly.

References:

• AWS CodeCommit
• AWS CodeDeploy
• AWS CodePipeline
• Amazon EC2 Auto Scaling
• AWS Fargate
• AWS Elastic Beanstalk

https://docs.aws.amazon.com/codedeploy/latest/ userguide/deployment-steps.html

A bucket policy is a resource-based policy that defines who can access a specific S3 bucket and what actions they can perform on it. By removing unauthenticated access from the bucket policy, you can prevent anyone without valid credentials from accessing the bucket. A service role is an IAM role that allows an AWS service, such as CodeBuild, to perform actions on your behalf. By modifying the service role for the CodeBuild project to include Amazon S3 access, you can grant the project permission to read and write objects in the S3 bucket. The AWS CLI is a command-line tool that allows you to interact with AWS services, such as S3, using commands in your terminal. By using the AWS CLI to download the database population script, you can leverage the service role credentials and encryption to secure the data transfer.

For more information, you can refer to these web pages:

• [Using bucket policies and user policies - Amazon Simple Storage Service]
• [Create a service role for CodeBuild - AWS CodeBuild]
• [AWS Command Line Interface]

This solution meets the requirements in the most operationally efficient manner by automating the application restart process on the instances without restarting them. When the CloudWatch alarm enters the ALARM state, the EventBridge rule is triggered, which in turn invokes the Systems Manager Automation runbook that contains the script to restart the application on the instances.

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.

References:

• 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.

https://docs.aws.amazon.com/codedeploy/latest/userguide/deployment-configurations.html

If instead you want to automatically apply the policy to existing in-scope resources, choose Auto remediate any noncompliant resources. This option creates a web ACL in each applicable account within the AWS organization and associates the web ACL with the resources in the accounts. When you choose Auto remediate any noncompliant resources, you can also choose to remove existing web ACL associations from in-scope resources, for the web ACLs that aren't managed by another active Firewall Manager policy. If you choose this option, Firewall Manager first associates the policy's web ACL with the resources, and then removes the prior associations. If a resource has an association with another web ACL that's managed by a different active Firewall Manager policy, this choice doesn't affect that association.

https://docs.aws.amazon.com/vpc/latest/userguide/managed-prefix-lists.html A managed prefix list is a set of one or more CIDR blocks. You can use prefix lists to make it easier to configure and maintain your security groups and route tables. https://docs.aws.amazon.com/vpc/latest/userguide/sharing-managed-prefix-lists.html With AWS Resource Access Manager (AWS RAM), the owner of a prefix list can share a prefix list with the following: Specific AWS accounts inside or outside of its organization in AWS Organizations An organizational unit inside its organization in AWS Organizations An entire organization in AWS Organizations

https://docs.aws.amazon.com/singlesignon/latest/userguide/configure-abac.html

To implement governance controls that restrict AWS service usage to within the United States and ensure alerts for any activity outside the governance policy, the following actions will meet the requirements:

• A. Create an AWS Organizations SCP that denies access to all non-global services in non-US Regions. Attach the policy to the root of the organization. This action will effectively prevent users and roles in all accounts within the organization from accessing services in non-US Regions12.
• B. Configure AWS CloudTrail to send logs to Amazon CloudWatch Logs and enable it for all Regions. Use a CloudWatch Logs metric filter to send an alert on any service activity in non-US Regions. This action will allow monitoring of all AWS Regions and will trigger alerts if any activity is detected in non-US Regions, ensuring that the governance team is notified as soon as possible3.

References:

• AWS Documentation on Service Control Policies (SCPs) and how they can be used to manage permissions and restrict access based on Regions12.
• AWS Documentation on monitoring CloudTrail log files with Amazon CloudWatch Logs to set up alerts for specific activities3.

These solutions will meet the requirement because they will prevent the loss of notification messages in the future. An Amazon SQS queue is a service that provides a reliable, scalable, and secure message queue for asynchronous communication between distributed components. You can use an SQS queue to buffer messages from an SNS topic and ensure that they are delivered and processed by a Lambda function, even if the function or the database is temporarily unavailable.

Option C will configure an SQS dead-letter queue for the SNS topic. A dead-letter queue is a queue that receives messages that could not be delivered to any subscriber after a specified number of retries. You can use a dead-letter queue to store and analyze failed messages, or to reprocess them later. This way, you can avoid losing messages that could not be delivered to the Lambda function due to network errors, throttling, or other issues.

Option D will subscribe an SQS queue to the SNS topic and configure the Lambda function to process messages from the SQS queue. This will decouple the SNS topic from the Lambda function and provide more flexibility and control over the message delivery and processing. You can use an SQS queue to store messages from the SNS topic until they are ready to be processed by the Lambda function, and also to retry processing in case of failures. This way, you can avoid losing messages that could not be processed by the Lambda function due to database errors, timeouts, or other issues.

API Gateway supports canary deployment on a deployment stage before you direct all traffic to that stage. A parallel environment means we will create a new ALB and a target group that will target a new set of EC2 instances on which the newer version of the app will be deployed. So the canary setting associated to the new version of the API will connect with the new ALB instance which in turn will direct the traffic to the new EC2 instances on which the newer version of the application is deployed.

When AWS CodeDeploy performs an in-place deployment, it updates the instances with the new application revision one at a time, as specified by the deployment configuration codeDeployDefault.oneAtATime. If a lifecycle event hook, such as AfterInstall, fails during the deployment, CodeDeploy will attempt to roll back to the previous version on the affected instances. This is likely what happened with the two instances that still have the previous application revision deployed. The failure of the AfterInstall lifecycle event hook triggered the rollback mechanism, resulting in those instances reverting to the previous application revision.

References:

• AWS CodeDeploy documentation on redeployment and rollback procedures1.
• Stack Overflow discussions on re-deploying older revisions with AWS CodeDeploy2.
• AWS CLI reference guide for deploying a revision2.

To implement failover for the application to the secondary Region so that HTTP GET requests meet the desired RTO, the DevOps engineer should use the following solution:

• Create a new origin on the distribution for the secondary ALB. A CloudFront origin is the source of the content that CloudFront delivers to viewers. By creating a new origin for the secondary ALB, the DevOps engineer can configure CloudFront to route traffic to the secondary Region when the primary Region is unavailable1
• Create a new origin group. Set the original ALB as the primary origin. Configure the origin group to fail over for HTTP 5xx status codes. An origin group is a logical grouping of two origins: a primary origin and a secondary origin. By creating an origin group, the DevOps engineer can specify which origin CloudFront should use as a fallback when the primary origin fails. The DevOps engineer can also define which HTTP status codes should trigger a failover from the primary origin to the secondary origin. By setting the original ALB as the primary origin and configuring the origin group to fail over for HTTP 5xx status codes, the DevOps engineer can ensure that CloudFront will switch to the secondary ALB when the primary ALB returns server errors2
• Update the default behavior to use the origin group. A behavior is a set of rules that CloudFront applies when it receives requests for specific URLs or file types. The default behavior applies to all requests that do not match any other behaviors. By updating the default behavior to use the origin group, the DevOps engineer can enable failover routing for all requests that are sent to the distribution3

This solution will meet the requirements because it will automate the failover of the application to the secondary Region with zero-second RTO. When CloudFront receives an HTTP GET request, it will first try to route it to the primary ALB in the primary Region. If the primary ALB is healthy and returns a successful response, CloudFront will deliver it to the viewer. If the primary ALB is unhealthy or returns an HTTP 5xx status code, CloudFront will automatically route the request to the secondary ALB in the secondary Region and deliver its response to the viewer.

The other options are not correct because they either do not provide zero-second RTO or do not work as expected. Creating a second CloudFront distribution that has the secondary ALB as the default origin and creating Amazon Route 53 alias records that have a failover policy is not a good option because it will introduce additional latency and complexity to the solution. Route 53 health checks and DNS propagation can take several minutes or longer, which means that viewers might experience delays or errors when accessing the application during a failover event. Creating Amazon Route 53 alias records that have a failover policy and Evaluate Target Health set to Yes for both ALBs and setting the TTL of both records to O is not a valid option because it will not work with CloudFront distributions. Route 53 does not support health checks for alias records that point to CloudFront distributions, so it cannot detect if an ALB behind a distribution is healthy or not. Creating a CloudFront function that detects HTTP 5xx status codes and returns a 307 Temporary Redirect error response to the secondary ALB is not a valid option because it will not provide zero-second RTO. A 307 Temporary Redirect error response tells viewers to retry their requests with a different URL, which means that viewers will have to make an additional request and wait for another response from CloudFront before reaching the secondary ALB.

References:

• 1: Adding, Editing, and Deleting Origins - Amazon CloudFront
• 2: Configuring Origin Failover - Amazon CloudFront
• 3: Creating or Updating a Cache Behavior - Amazon CloudFront

https://docs.aws.amazon.com/codedeploy/latest/userguide/reference-appspec-file-structure-hooks.html

https://aws.amazon.com/about-aws/whats-new/2020/02/aws-cloudformation-stacksets-introduces-automat ic-deployments-across-accounts-and-regions-through-aws-organizations/

AWS Health provides real-time events and information related to your AWS infrastructure. It can be integrated with Amazon EventBridge to act upon the health events automatically. If the maintenance notification from AWS Health indicates that an EC2 instance requires a restart, you can set up an EventBridge rule to respond to such events. In this case, the target of this rule would be a Lambda function that would trigger a Systems Manager automation to restart the EC2 instance during a maintenance window. Remember, AWS Health is the source of the events (not EC2 or Systems Manager), and AWS Lambda can be used to execute complex remediation tasks, such as scheduling maintenance tasks via Systems Manager.

The following are the steps involved in configuring the EventBridge rule to meet these requirements:

• Configure an event source of AWS Health, a service of EC2, and an event type that indicates instance maintenance.
• Target a newly created AWS Lambda function that registers an automation task to restart the EC2 instance during a maintenance window.

The AWS Lambda function will be triggered by the event from AWS Health. The function will then register an automation task to restart the EC2 instance during the next maintenance window.

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.

A. The CloudFormation template should be modified to include a parameter that indicates the location of the .zip file containing the Lambda function's code. This allows the CloudFormation deploy action to use the correct artifact depending on the region. This is critical because Lambda functions need to reference their code artifacts from the same region they are being deployed in. B. You would also need to create a new CloudFormation deploy action for the us-east-1 Region within the pipeline. This action should be configured to use the CloudFormation template from the artifact that was specifically created for us-east-1.

These are the possible causes for the AccessDenied error because they affect the permissions to access the S3 object from the EC2 instance. An S3 bucket policy is a resource-based policy that defines who can access the bucket and its objects, and what actions they can perform. An IAM role is an identity that can be assumed by an EC2 instance to grant it permissions to access AWS services and resources. If there is an error in the S3 bucket policy or the IAM role configuration, such as a missing or incorrect statement, condition, or principal, then the EC2 instance may not have the necessary permissions to download the object from the S3 bucket .

https://docs.aws.amazon.com/AmazonS3/latest/userguide/example-bucket-policies.html

https://docs.aws.amazon.com/AWSEC2/latest /UserGuide/iam-roles-for-amazon-ec2.html

 The correct solution is to create a new assertion safety rule in Route 53 ARC and apply it to the two routing controls. An assertion safety rule is a type of safety rule that ensures that a minimum number of routing controls are always enabled. The ATLEAST type of assertion safety rule specifies the minimum number of routing controls that must be enabled for the rule to evaluate as healthy. By setting the threshold to 1, the rule ensures that at least one routing control is always turned on. This prevents the scenario where both routing controls are accidentally turned off and the application becomes unavailable in both Regions.

The other solutions are incorrect because they do not use safety rules to prevent both routing controls from being turned off. A gating safety rule is a type of safety rule that prevents routing control state changes that violate the rule logic. The OR type of gating safety rule specifies that one or more routing controls must be enabled for the rule to evaluate as healthy. However, this rule does not prevent a user from turning off both routing controls manually. A resource set is a collection of resources that are tested for readiness by Route 53 ARC. A readiness check is a test that verifies that all the resources in a resource set are operational. However, these concepts are not related to routing control states or safety rules. Therefore, creating a new resource set and a new readiness check will not ensure that at least one routing control is turned on at all times. References:

• Routing control in Amazon Route 53 Application Recovery Controller
• Viewing and updating routing control states in Route 53 ARC
• Creating a control panel in Route 53 ARC
• Creating safety rules in Route 53 ARC

https://aws.amazon.com/about-aws/whats-new/2016/09/aws-codedeploy-introduces-deployment-monitoring-with-amazon-cloudwatch-alarms-and-automatic-deployment-rollback/

https://docs.aws.amazon.com/AmazonS3/latest/userguide/checking-object-integrity.html

This solution will meet the requirements because it will use Amazon Inspector to scan the EC2 instances for any new vulnerabilities and generate findings that can be viewed in the Inspector console or sent as notifications via Amazon Simple Notification Service (SNS). It will also use the Amazon CloudWatch Agent to collect and send system logs from the EC2 instances to Amazon CloudWatch Logs, where they can be stored, searched, and analyzed. The system logs can provide an audit trail of all login activities on the instances, as well as other useful information such as performance metrics, errors, and events.

https://docs.aws.amazon.com/inspector/latest/user/what-is-inspect or.html

Short Explanation: To meet the requirements, the DevOps engineer should update the SAML assertion to pass the user’s team name, update the IAM role’s trust policy to add an access-team session tag that has the team name, create an IAM permissions boundary in each account, and for each CodeCommit repository, add an access-team tag that has the value set to the name of the associated team.

References:

• Updating the SAML assertion to pass the user’s team name allows the DevOps engineer to use IAM tags to identify which team a user belongs to. This can help enforce fine-grained access control based on the user’s team membership1.
• Updating the IAM role’s trust policy to add an access-team session tag that has the team name allows the DevOps engineer to use IAM condition keys to restrict access based on the session tag value2. For example, the DevOps engineer can use the aws:PrincipalTag condition key to match the access-team tag of the user with the access-team tag of the repository3.
• Creating an IAM permissions boundary in each account allows the DevOps engineer to set the maximum permissions that an identity-based policy can grant to an IAM entity. An entity’s permissions boundary allows it to perform only the actions that are allowed by both its identity-based policies and its permissions boundaries4. For example, the DevOps engineer can use a permissions boundary policy to limit the actions that a user can perform on CodeCommit repositories based on their access-team tag5.
• For each CodeCommit repository, adding an access-team tag that has the value set to the name of the associated team allows the DevOps engineer to use resource tags to identify which team manages a repository. This can help enforce fine-grained access control based on the resource tag value6.
• The other options are incorrect because:

To meet the requirements of ensuring that flow logs remain configured for all existing and new VPCs in the AWS account, the company should use AWS Config and automatic remediation. AWS Config is a service that enables customers to assess, audit, and evaluate the configurations of their AWS resources. AWS Config continuously monitors and records the configuration changes of the AWS resources and evaluates them against desired configurations. Customers can use AWS Config rules to define the desired configuration state of their AWS resources and trigger actions when a resource configuration violates a rule.

One of the AWS Config rules that customers can use is vpc-flow-logs-enabled, which checks whether VPC flow logs are enabled for all VPCs in an AWS account. Customers can also configure automatic remediation for this rule, which means that AWS Config will automatically enable VPC flow logs for any VPCs that do not have them enabled. Customers can specify the destination (CloudWatch Logs or S3) and the traffic type (all, accept, or reject) for the flow logs as remediation parameters. By using AWS Config and automatic remediation, the company can ensure that flow logs remain configured for all existing and new VPCs in its AWS account, regardless of who creates them or how they are created.

The other options are not correct because they do not meet the requirements or follow best practices. Adding the resource to the CloudFormation stack that creates the VPCs is not a sufficient solution because it will only work for VPCs that are created by using the CloudFormation stack. It will not work for VPCs that are created by using other methods, such as the console or the API. Creating an organization in AWS Organizations and creating an SCP to prevent users from modifying VPC flow logs is not a good solution because it will not ensure that flow logs are enabled for all VPCs in the first place. It will only prevent users from disabling or changing flow logs after they are enabled. Creating an IAM policy to deny the use of API calls for VPC flow logs and attaching it to all IAM users is not a valid solution because it will prevent users from enabling or disabling flow logs at all. It will also not work for VPCs that are created by using other methods, such as the console or CloudFormation.

References:

• 1: AWS::EC2::FlowLog - AWS CloudFormation
• 2: Amazon VPC Flow Logs extends CloudFormation Support to custom format subscriptions, 1-minute aggregation intervals and tagging
• 3: Logging IP traffic using VPC Flow Logs - Amazon Virtual Private Cloud
• : About AWS Config - AWS Config
• : vpc-flow-logs-enabled - AWS Config
• : Remediate Noncompliant Resources with AWS Config Rules - AWS Config

Creating an AWS CodeCommit repository for each project, using the main branch for production code, and creating a testing branch for code deployed to testing will meet the requirements. AWS CodeCommit is a managed revision control service that hosts Git repositories and works with all Git-based tools1. By using feature branches to develop new features and pull requests to merge code to testing and main branches, the developers can avoid code conflicts and lost work, and also implement code reviews and approvals. Option B is incorrect because creating another S3 bucket for each project for testing code and using an AWS Lambda function to promote code changes between testing and production buckets will not provide the benefits of revision control, such as tracking changes, branching, merging, and collaborating. Option C is incorrect because using the main branch for production and test code with different deployment pipelines for each environment will not allow the developers to test their code changes before deploying them to production. Option D is incorrect because enabling versioning and branching on each S3 bucket will not work with Git-based tools and will not provide the same level of revision control as AWS CodeCommit. References:

• AWS CodeCommit
• Certified DevOps Engineer - Professional (DOP-C02) Study Guide (page 182)

https://docs.aws.amazon.com/codedeploy/latest/userguide/reference-appspec-file-structure-hooks.html#appspec-hooks-lambda

https://repost.aws/knowledge-center/cloudformation-update-rollback-failed If your stack is stuck in the UPDATE_ROLLBACK_FAILED state after a failed update, then the only actions that you can perform on the stack are the ContinueUpdateRollback or DeleteStack operations.

To meet the requirements of migrating its on-premises Windows and Linux applications to AWS and creating a pilot light DR environment in another AWS Region, the company should use Amazon FSx for NetApp ONTAP for the application storage. Amazon FSx for NetApp ONTAP is a fully managed service that provides highly reliable, scalable, high-performing, and feature-rich file storage built on NetApp’s popular ONTAP file system. FSx for ONTAP supports multiple protocols, including SMB for Windows and NFS for Linux, so the company can access the shared storage from both types of applications. FSx for ONTAP also supports NetApp SnapMirror replication, which enables the company to replicate the storage to the DR Region. NetApp SnapMirror replication is efficient, secure, and incremental, and it preserves the data deduplication and compression benefits of FSx for ONTAP. The company can use automation to launch and configure the EC2 instances in the DR Region and then use NetApp SnapMirror to restore the data from the primary Region.

The other options are not correct because they do not meet the requirements or follow best practices. Using Amazon S3 for the application storage is not a good option because S3 is an object storage service that does not support SMB or NFS protocols natively. The company would need to use additional services or software to mount S3 buckets as file systems, which would add complexity and cost. Using Amazon EBS for the application storage is also not a good option because EBS is a block storage service that does not support SMB or NFS protocols natively. The company would need to set up and manage file servers on EC2 instances to provide shared access to the EBS volumes, which would add overhead and maintenance. Using a Volume Gateway in AWS Storage Gateway for the application storage is not a valid option because Volume Gateway does not support SMB protocol. Volume Gateway only supports iSCSI protocol, which means that only Linux applications can access the shared storage.

References:

• 1: What is Amazon FSx for NetApp ONTAP? - FSx for ONTAP
• 2: Amazon FSx for NetApp ONTAP
• 3: Amazon FSx for NetApp ONTAP | NetApp
• 4: AWS Announces General Availability of Amazon FSx for NetApp ONTAP
• : Replicating Data with NetApp SnapMirror - FSx for ONTAP
• : What Is Amazon S3? - Amazon Simple Storage Service
• : What Is Amazon Elastic Block Store (Amazon EBS)? - Amazon Elastic Compute Cloud
• : What Is AWS Storage Gateway? - AWS Storage Gateway

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.

To meet the requirements, the DevOps engineer should create an Amazon EventBridge event rule that has the default event bus as the source. The rule's event pattern should match EC2 security group creation and modification events, and it should be configured to invoke the Lambda function. This solution will allow for near real-time detection of security group rule changes and will trigger the Lambda function to remove any unrestricted rules and send email notifications to the security team.

https://repost.aws/knowledge-center/monitor-security-group-changes-ec2

https://docs.aws.amazon.com/systems-manager/latest/userguide/patch-manager-how-it-works-alt-source-repository.html

Update the buildspec.yml file to log in to the ECR repository by using the aws ecr get-login-password AWS CLI command to obtain an authentica-tion token. Update the docker login command to use the authentication token to access the ECR repository.

This is the correct solution. The aws ecr get-login-password AWS CLI command retrieves and displays an authentication token that can be used to log in to an ECR repository. The docker login command can use this token as a password to authenticate with the ECR repository. This way, the CodeBuild project can push and pull images from the ECR repository without any errors. For more information, see Using Amazon ECR with the AWS CLI and get-login-password.

To implement a control that requires the use of IMDSv2 on all EC2 instances in the account, the DevOps engineer can use a permissions boundary. A permissions boundary is a policy that defines the maximum permissions that an IAM entity can have. The DevOps engineer can create a permissions boundary that prevents the ec2:RunInstance action if the ec2:MetadataHttpTokens condition key is not set to a value of required. This condition key enforces the use of IMDSv2 on EC2 instances. The DevOps engineer can attach the permissions boundary to the IAM role that was used to launch the instance. This way, any attempt to launch an EC2 instance without using IMDSv2 will be denied by the permissions boundary.

A comprehensive and detailed explanation is:

• Option A is correct because using batch writes to write multiple log events in a single write operation is a recommended practice for optimizing the performance and cost of data ingestion in Timestream. Batch writes can reduce the number of network round trips and API calls, and can also take advantage of parallel processing by Timestream. Batch writes can also improve the compression ratio of data in the memory store and the magnetic store, which can reduce the storage costs and improve the query performance1.
• Option B is incorrect because writing each log event as a single write operation is not a recommended practice for optimizing the performance and cost of data ingestion in Timestream. Writing each log event as a single write operation would increase the number of network round trips and API calls, and would also reduce the compression ratio of data in the memory store and the magnetic store. This would increase the storage costs and degrade the query performance1.
• Option C is incorrect because treating each log as a single-measure record is not a recommended practice for optimizing the query performance in Timestream. Treating each log as a single-measure record would result in creating multiple records for each timestamp, which would increase the storage size and the query latency. Moreover, treating each log as a single-measure record would require using joins to query multiple measures for the same timestamp, which would add complexity and overhead to the query processing2.
• Option D is correct because treating each log as a multi-measure record is a recommended practice for optimizing the query performance in Timestream. Treating each log as a multi-measure record would result in creating a single record for each timestamp, which would reduce the storage size and the query latency. Moreover, treating each log as a multi-measure record would allow querying multiple measures for the same timestamp without using joins, which would simplify and speed up the query processing2.
• Option E is incorrect because configuring the memory store retention period to be longer than the magnetic store retention period is not a valid option in Timestream. The memory store retention period must always be shorter than or equal to the magnetic store retention period. This ensures that data is moved from the memory store to the magnetic store before it expires out of the memory store3.
• Option F is correct because configuring the memory store retention period to be shorter than the magnetic store retention period is a valid option in Timestream. The memory store retention period determines how long data is kept in the memory store, which is optimized for fast point-in-time queries. The magnetic store retention period determines how long data is kept in the magnetic store, which is optimized for fast analytical queries. By configuring these retention periods appropriately, you can balance your storage costs and query performance according to your application needs3.

References:

• 1: Batch writes
• 2: Multi-measure records vs. single-measure records
• 3: Storage

The following are the steps that the DevOps engineer should take to reduce the latency of the Lambda function at all times of the day:

• 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.

The provisioned concurrency setting ensures that there is always a minimum number of Lambda function instances available to handle requests. The Application Auto Scaling setting will automatically scale the number of Lambda function instances up or down based on the demand for the application.

This solution will ensure that the Lambda function is able to handle the increased load during the middle of the day, while also keeping the cold-start latency low.

The following are the reasons why the other options are not correct:

• Option A is incorrect because it will not reduce the cold-start latency of the Lambda function.
• Option B is incorrect because it will not scale the number of Lambda function instances up or down based on demand.
• Option D is incorrect because it will only configure reserved concurrency on the API Gateway API, which will not affect the Lambda function.