SAP-C02 Exam Dumps - Amazon Web Services AWS Certified Professional Questions and Answers

This option allows the solutions architect to use a private hosted zone to host DNS records that are only accessible within the VPC1. By associating the private hosted zone with the VPC, the solutions architect can ensure that DNS queries from the VPC are routed to the private hosted zone2. By activating the enableDnsSupport attribute and the enableDnsHostnames attribute for the VPC, the solutions architect can enable DNS resolution and hostname assignment for instances in the VPC3. By creating a new VPC DHCP options set, and configuring domain-name-servers=AmazonProvidedDNS, the solutions architect can use Amazon-provided DNS servers to resolve DNS queries from instances in the VPC4. By associating the new DHCP options set with the VPC, the solutions architect can apply the DNS settings to all instances in the VPC5.

What is Amazon Route 53 Resolver?

Associating a private hosted zone with your VPC

Using DNS with your VPC

DHCP options sets

Modifying your DHCP options

Developing infrastructure services using AWS CloudFormation templates and uploading them as AWS Service Catalog products to portfolios created in a central AWS account will enable thecompany to centrally manage the creation of infrastructure services and control who can use them1. AWS Service Catalog allows you to create and manage catalogs of IT services that are approved for use on AWS2. You can organize products into portfolios, which are collections of products along with configuration information3. You can share portfolios with other accounts in your organization using AWS Organizations4.

Allowing user IAM roles to have ServiceCatalogEndUserAccess permissions only and using an automation script to import the central portfolios to local AWS accounts, copy the TagOption, assign users access, and apply launch constraints will enable the company to provide least privilege access to users when launching AWS infrastructure services. ServiceCatalogEndUserAccess is a managed IAM policy that grants users permission to list and view products and launch product instances. An automation script can help import the shared portfolios from the central account to the local accounts, copy the TagOption from the central account, assign users access to the portfolios, and apply launch constraints that specify which IAM role or user can provision a product.

Using the AWS Service Catalog TagOption Library to maintain a list of tags required by the company and applying the TagOption to AWS Service Catalog products or portfolios will enable the company to enforce tags on any infrastructure that is started by users. TagOptions are key-value pairs that you can use to classify your AWS Service Catalog resources. You can create a TagOption Library that contains all the tags that you want to use across your organization. You can apply TagOptions to products or portfolios, and they will be automatically applied to any provisioned product instances.

Creating a product from an existing CloudFormation template

What is AWS Service Catalog?

Working with portfolios

Sharing a portfolio with AWS Organizations

[Providing least privilege access for users]

[AWS managed policies for job functions]

[Importing shared portfolios]

[Enforcing tag policies]

[Working with TagOptions]

[Creating a TagOption Library]

[Applying TagOptions]

This option uses different types of savings plans and reserved nodes to minimize the company’s overall monthly costs for running its application on EC2 instances, Lambda functions, and MemoryDB cache nodes. Savings plans are flexible pricing models that offer significant savings on AWS usage (up to 72%) in exchange for a commitment of a consistent amount of usage (measured in $/hour) for a one-year or three-year term. There are two types of savings plans: Compute Savings Plans and EC2 Instance Savings Plans. Compute Savings Plans apply to any compute usage across EC2 instances, Fargate containers, Lambda functions, SageMaker notebooks, and ECS tasks. EC2 Instance Savings Plans apply to a specific instance family within a region and provide more savings than Compute Savings Plans (up to 66% versus up to 54%). Reserved nodes are similar to savings plans but apply only to MemoryDB cache nodes. They offer up to 55% savings compared to on-demand pricing.

AWS Cost Anomaly Detection is a feature of the AWS Cost Management suite that leverages machine learning to enable continuous monitoring of your AWS costs and usage, allowing you to identify unexpected and abnormal spending1. You can create cost monitors that evaluate specific AWS services, member accounts, cost allocation tags, orcost categories based on your AWS account structure2. You can also configure alert subscriptions that notify you when a cost monitor detects an anomaly that meets your threshold2. In this case, you can create a cost monitor with a monitor type of AWS Service and apply a filter of Amazon EC2 to track the EC2 usage as a metric. You can then configure an alert subscription to notify the architecture team if the usage is 10% more than the average usage for the last 30 days, which is the anomaly detection period used by AWS Cost Anomaly Detection3.

This option allows the company to use private subnets and VPC endpoints to connect the Lambda functions to the Neptune DB cluster and DynamoDB tables securely and efficiently1. By creating three private subnets in the Neptune VPC, the company can isolate the Lambda functions from the public internet and reduce the attack surface2. By routing internet traffic through a NAT gateway,the company can enable the Lambda functions to access AWS services that are outside the VPC, suchas Amazon S3 or Amazon CloudWatch3. By hosting the Lambda functions in the three new private subnets, the company can ensure that the Lambda functions can access the Neptune DB cluster within the same VPC4. By creating a VPC endpoint for DynamoDB, the company can enable the Lambda functions to access DynamoDB tables without going through the internet or a NAT gateway5. By routing DynamoDB traffic to the VPC endpoint, the company can improve the performance and availability of the DynamoDB access5.

Configuring a Lambda function to access resources in a VPC

Working with VPCs and subnets

NAT gateways

Accessing Amazon Neptune from AWS Lambda

VPC endpoints for DynamoDB

A Direct Connect gateway allows you to connect multiple VPCs across different Regions to a Direct Connect connection1. A public VIF allows you to access AWS public services such as EC21. A Site-to-Site VPN connection over the public VIF provides encryption and redundancy for the traffic between the on-premises data center and the VPCs2. This solution is cheaper than setting up additional Direct Connect connections or using a private VIF with VPC peering.

Resource-based policies are policies that you attach to a resource, such as an IAM role, to specify who can access the resource and what actions they can perform on it1. Identity-based policies are policies that you attach to an IAM user, group, or role to specify what actions they can perform on which resources2. Trust policies are special types of resource-based policies that define which principals (such as IAM users or roles) can assume a role3.

To allow an IAM user in Account A to assume a role in Account B, the solutions architect needs to do the following:

Configure the resource-based policy on the target role in Account B to allow the action sts:AssumeRole for the IAM user in Account A. This policy grants permission to the IAM user to assume the role4.

Configure the identity-based policy on the user in Account A to allow the action sts:AssumeRole for the target role in Account B. This policy grants permission to the user to perform the action of assuming the role5.

Configure the trust policy on the target role in Account B to allow the principal of the IAM user in Account A. This policy defines who can assume the role.

Resource-based policies

Identity-based policies

Trust policies

Granting a user permissions to switch roles

Switching roles

[Modifying a role trust policy]

 This solution will provide the highest availability for the database, as the read replicas will allow the database to be available in multiple Regions, thus reducing the chances of disruption. Additionally, the promotion of the cross-Region read replica to become a standalone DB instance will ensure that the database is still available even if one of the Regions experiences disruptions.

•Use Amazon S3 for web hosting with AWS AppSync for database API services. Use Amazon Simple Queue Service (Amazon SQS) for order queuing. Use AWS Lambda for business logic with an Amazon SQS dead-letter queue for retaining failed orders.

This solution will allow you to:

•Host a static website on Amazon S3 without provisioning or managing servers1.

•Use AWS AppSync to create a scalable GraphQL API that connects to your database and other data sources1.

•Use Amazon SQS to decouple and scale your order processing microservices1.

•Use AWS Lambda to run code for your business logic without provisioning or managing servers1.

•Use an Amazon SQS dead-letter queue to retain messages that can’t be processed by your Lambda function1.

GitHub Webhooks to Trigger CodePipeline:

Configure GitHub webhooks to trigger the AWS CodePipeline pipeline. This ensures that every code push to the repository automatically triggers the pipeline, initiating the build and deployment process.

Unit Testing with Jenkins and AWS CodeBuild:

Use Jenkins integrated with the AWS CodeBuild plugin to perform unit testing. Jenkins will manage the build process, and the results will be handled by CodeBuild.

Notifications for Bad Builds:

Configure Amazon SNS (Simple Notification Service) to send alerts for any failed builds. This keeps the engineering team informed of build issues immediately, allowing for quick resolutions.

Blue/Green Deployment with AWS CodeDeploy:

Utilize AWS CodeDeploy with a blue/green deployment strategy. This method reduces downtime and risk by running two identical production environments (blue and green). CodeDeploy shifts traffic between these environments, allowing you to test in the new environment (green) while the old environment (blue) remains live. If issues arise, you can quickly roll back to the previous environment.

This solution provides seamless, zero-downtime deployments, and the ability to quickly roll back changes if necessary, fulfilling the requirements of the startup company.

References

AWS DevOps Blog on Integrating Jenkins with AWS CodeBuild and CodeDeploy【32】.

Plain English Guide to AWS CodePipeline with GitHub【33】.

Jenkins Plugin for AWS CodePipeline【34】.

The correct answer is D.

D. This solution meets the requirements because it uses a scheduled scaling policy for the EC2 instances, which can adjust the capacity according to the known sale events. It also uses Amazon Aurora PostgreSQL Multi-AZ DB cluster, which provides high availability and durability for the database. It uses Amazon EventBridge rules and AWS Lambda functions to create a larger Aurora Replica before a sale event and fail over to it, which can improve the performance and handle the increased traffic.It also uses anotherEventBridge rule and Lambda function to scale down the Aurora Replica after the sale event, which can save costs123

A. This solution is incorrect because it uses predictive scaling policy for the EC2 instances, which is not suitable for one-time events that are scheduled. Predictive scaling is based on historical data and machine learning, which may not accurately forecast the demand for sale events. It also uses Amazon Aurora PostgreSQL Serverless v2 Multi-AZ DB instance, which does not support read replicas.The use of AWS Step Functions state machine and Lambda functions to pre-warm the database is unnecessary and adds complexity45

B. This solution is incorrect because it uses Amazon RDS for PostgreSQL Multi-AZ DB instance with automatically scaling read replicas, which may not provide enough performance improvement for the sale events. The use of EventBridge rules and Lambda functions to create a larger read replica and fail over to it is risky and may cause downtime ordata loss.The use of another EventBridge rule and Lambda function to scale down the read replica is also risky and may cause inconsistency or data loss67

C. This solution is incorrect because it uses predictive scaling policy for the EC2 instances, which is not suitable for one-time events that are scheduled. Predictive scaling is based on historical data and machine learning, which may not accurately forecast the demand for sale events.The use of AWS Step Functions state machine and Lambda functions to pre-warm the database is unnecessary and adds complexity45

Comprehensive and Detailed Explanation From Exact Extract:

When an IAM user appears to have the correct permissions but still receives Access Denied errors, especially in an AWS Organizations environment, the effective permissions must be evaluated across all permission layers. In AWS, permissions are the intersection of all applicable controls, and an explicit deny at any layer overrides any allow.

First, because the company uses AWS Organizations, service control policies (SCPs) must be evaluated. SCPs define the maximum permissions that accounts or organizational units can have. Even if an IAM user or IAM policy allows an action, an SCP attached to the account or OU can explicitly or implicitly deny that action. If an SCP does not allow s3:ListAllMyBuckets or related S3 read actions, the IAM user will not be able to list buckets in the S3 console and will see no buckets at all. Therefore, checking the SCPs applied to the OU or account is a required troubleshooting step.

Second, IAM permissions boundaries can further restrict the effective permissions of an IAM user. A permissions boundary defines the maximum permissions that an IAM user can exercise, regardless of what their attached policies allow. If the permissions boundary does not include the required Amazon S3 read-only permissions (such as s3:ListAllMyBuckets or s3:GetBucketLocation), the user will receive access denied errors even though the user’s IAM policy appears to allow read-only access. Reviewing whether a permissions boundary is attached, and whether it allows the necessary S3 actions, is essential.

Option A (checking bucket policies) can be relevant for access to specific buckets or objects, but a user seeing no buckets at all in the S3 console is more commonly caused by missing or denied account-level list permissions rather than individual bucket policies. Bucket policies generally do not control the ability to list all buckets in an account unless they contain explicit denies, which is less common as a first troubleshooting step in an Organizations setup.

Option B (checking ACLs) is less relevant because ACLs primarily control object-level and bucket-level access and are not typically used to manage console-level visibility of all buckets in an account. ACLs also do not commonly block the ListAllMyBuckets action.

Option E is incorrect because IAM users do not require IAM roles to access AWS services. Roles are assumed by users or services, but the presence or absence of a role attached to an IAM user does not affect the user’s direct permissions.

Therefore, the most appropriate troubleshooting steps are to check the SCPs applied through AWS Organizations and to verify whether an IAM permissions boundary is restricting the user’s effective permissions.