Free Amazon Web Services SAP-C02 Practice Exam with Questions & Answers

This option allows the company to use AWS Client VPN to enable secure and private access to the Amazon ES cluster from any location1. By configuring and setting up an AWS Client VPN endpoint, the company can create a secure tunnel between the developers’ devices and the VPC2. By associating the Client VPN endpoint with a subnet in the VPC, the company can ensure that the trafficfrom the developers’ devices is routed to the Amazon ES cluster within the VPC3. By configuring a Client VPN self-service portal, the company can enable the developers to download and install the client for Client VPN, which is based on OpenVPN4. By instructing the developers to connect by using the client for Client VPN, the company can allow them to access Amazon ES to analyze and visualize logs directly from their local development machines.

What is AWS Client VPN?

Creating a Client VPN endpoint

Associating a target network with a Client VPN endpoint

Configuring a self-service portal

A DAX cluster can be deployed with one or two nodes for development or test workloads. One- and two-node clusters are not fault-tolerant, and we don't recommend using fewer than three nodes for production use. If a one- or two-node cluster encounters software or hardware errors, the cluster can become unavailable or lose cached data.A DAX cluster can be deployed with one or two nodes for development or test workloads. One- and two-node clusters are not fault-tolerant, and we don't recommend using fewer than three nodes for production use. If a one- or two-node cluster encounters software or hardware errors, the cluster can become unavailable or lose cached data.

https://docs.aws.amazon.com/amazondynamodb/latest/developerguide/DAX.concepts.cluster.html

Store Secret in AWS Secrets Manager:

Create a random string in AWS Secrets Manager to be used as a custom HTTP header value.

Set Up Automatic Rotation:

Implement a Lambda function to handle automatic rotation of the secret in AWS Secrets Manager, ensuring the header value remains secure.

Configure CloudFront Custom Header:

In the CloudFront distribution settings, configure an origin custom header with the name and value from AWS Secrets Manager. This header will be included in requests forwarded to the ALB.

Create AWS WAF Web ACL:

Create a Web ACL in AWS WAF with a string match rule to allow requests that include the custom header with the correct value.

Associate the Web ACL with the ALB to filter incoming traffic based on the custom header.

By using this method, you can ensure that only requests coming through CloudFront (which injects the custom header) can reach the ALB, enhancing the origin security

Moving the application frontend to a static website that is hosted on Amazon S3 will save cost as S3 is cheaper than running EC2 instances.

Using Spot instances for the backend EC2 instances will also save cost, as they are significantly cheaper than On-Demand instances. This will be suitable for the application, as it has minimal traffic during the rest of the day, and the availability of spot instances will not negatively affect the application's availability.

Option D offers the lowest latency and highest efficiency:

Amazon DynamoDB global tables replicate data across multiple Regions, ensuring that the database is available and responsive in each Region.

Lambda@Edge allows the backend logic to execute at AWS edge locations, reducing the distance between the user's device and the code execution environment, thereby minimizing latency.

Amazon CloudFront serves as the content delivery network, routing requests to the nearest edge location where the Lambda@Edge function is executed.

Amazon Route 53 maps the DNS name to the CloudFront distribution, ensuring that users are directed to the optimal edge location.

This architecture ensures rapid response times and high availability for a globally distributed user base.

D is correct because AWS Private CA supports resource sharing through AWS RAM, which allows you to share the CA across accounts in your AWS Organization securely. It ensures the CA private key remains secure and is never exported.

A is invalid because you cannot export a CA’s private key, and importing/exporting CAs this way is unsupported.

B is incorrect — IAM policies alone are not sufficient to share Private CAs across accounts.

C is not applicable because resource-based delegation policies do not apply to AWS Private CA.

Creating a user pool in Amazon Cognito and configuring it for the application will meet the requirement of giving only a specific list of users the ability to access the application from the internet. A user pool is a directory of users that can sign in to an application with ausername and password1. The company can populate the user pool with the required users and configure the pool to require MFA for additional security2. Configuring a listenerrule on the ALB to require authentication through the Amazon Cognito hosted UI will meet the requirement of not changing the application and not integrating it with an identity provider. The ALB can use Amazon Cognito as an authentication action to authenticate usersbefore forwarding requests to the Fargate service3. The Amazon Cognito hosted UI is a customizable web page that provides sign-in and sign-up functionality for users4.

Extend the system with an application tier that uses AWS Step Functions and AWS Lambda. Configure this tier to use Amazon Textract and Amazon Comprehend to perform optical character recognition (OCR) on the forms when forms are uploaded. Store the output in Amazon S3. Parse this output by extracting the data that is required within the application tier. Submit the data to the target system's API. This solution meets the requirements of accurate form extraction, minimal time to market, and minimal long-term operational overhead. Amazon Textract and Amazon Comprehend are fully managed and serverless services that can perform OCR and extract relevant data from the forms, which eliminates the need to develop custom libraries or train and host models. Using AWS Step Functions and Lambda allows for easy automation of the process and the ability to scale as needed.

https://aws.amazon.com/rds/aurora/global-database/

Migrating to an Amazon EKS cluster with managed node groups minimizes the effort required because:

EKS is fully managed, offering native Kubernetes support, making it easy to deploy the existing Kubernetes manifests without major changes.

Copying containers to Amazon ECR allows for fully managed, scalable container image storage in AWS, eliminating reliance on the on-premises container repository.

Deploying the existing manifests directly to EKS reuses all the existing configuration, such as service definitions, deployments, and scaling policies, simplifying migration.

Using Amazon Aurora PostgreSQL provides a fully managed, highly available database service that is compatible with PostgreSQL, reducing operational overhead compared to managing a self-hosted database.This approach leverages the power of AWS managed services while preserving the existing microservices and deployment practices, ensuring minimal disruption and fastest migration path.

 The company should create a resource-based IAM policy that includes conditions for specific DynamoDB attributes (fine-grained access control). The company should attach the policy to the DynamoDB table. In the marketing team’s account, the company should create an IAM role that has permissions to access the DynamoDB table in the finance team’s account. This solution will meet the requirements because a resource-based IAM policy is a policy that you attach to an AWS resource (such as a DynamoDB table) to control who can access that resource and what actions they can perform on it. You can use IAM policyconditions to specify fine-grained access control for DynamoDB items and attributes. For example, you can allow or deny access to specific attributes of all items in a table by matching on attribute names1. By creating a resource-based policy that allows access to only specific attributes of the DynamoDB table and attaching it to the table, the company can restrict access to confidential data. By creating an IAM role in the marketing team’s account that has permissions to access the DynamoDB table in the finance team’s account, the company can enable cross-account access.

The other options are not correct because:

Creating an SCP to grant the marketing team’s AWS account access to the specific attributes of the DynamoDB table would not work because SCPs are policies that you can use with AWS Organizations to manage permissions in your organization’s accounts. SCPs do not grant permissions; instead, they specify the maximum permissions that identities in an account can have2. SCPs cannot be used to specify fine-grained access control for DynamoDB items and attributes.

Creating an IAM role in the finance team’s account by using IAM policy conditions for specific DynamoDB attributes and establishing trust with the marketing team’s account would not work because IAM roles are identities that you can create in your account that have specific permissions. You can use an IAM role to delegate access to users, applications, or services that don’t normally have access to your AWS resources3. However, creating an IAM role in the finance team’s account would not restrict access to specific attributes of the DynamoDB table; it would only allow cross-account access. The company would still need a resource-based policy attached to the table to enforce fine-grained access control.

Creating an IAM role in the finance team’s account to access the DynamoDB table and using an IAM permissions boundary to limit the access to the specific attributes would not work because IAM permissions boundaries are policies that you use to delegate permissions management to other users. You can use permissions boundaries to limit the maximum permissions that an identity-based policy can grant to an IAM entity (user or role)4. Permissions boundaries cannot be used to specify fine-grained access control for DynamoDB items and attributes.

This option allows the company to use a single VPC to host multiple test environments that are isolated from each other by using different subnets and security groups1. By including a transit gateway attachment and related routing configurations, the company can enable the test environmentsto communicate with the central server in the on-premises data center through a VPN connection2. By using AWS CloudFormation to deploy all test environments into the VPC, the company can automate the creation and deletion of test environments without any manual intervention3. This option also minimizes the operational overhead by reducing the number of VPCs, accounts, and resources that need to be managed.

Working with VPCs and subnets

Working with transit gateways

Working with AWS CloudFormation stacks

Option C is correct because using Auto Scaling groups for the backend services allows the company to scale up or down the number of EC2 instances based on the demand and traffic. This way, the backend services can handle more requests during peak seasons without compromising performance or availability. Using DynamoDB auto scaling allows the company to adjust the provisioned read and write capacity of the table or index automatically based on the actual traffic patterns. This way, the table or index can handle sudden increases or decreases in workload without throttling or overprovisioning1.

Option A is incorrect because migrating the backend services to AWS Lambda may require significant development effort to rewrite the code and test the functionality. Moreover, increasing the read and write capacity of DynamoDB manually may not be efficient or cost-effective, as it does not account for the variability of the workload. The company may end up paying for unused capacity or experiencing throttling if the workload exceeds the provisioned capacity1.

Option B is incorrect because migrating the backend services to AWS Lambda may require significant development effort to rewrite the code and test the functionality. Moreover, configuring DynamoDB to use global tables may not be necessary or beneficial for the company, as global tables are mainly used for replicating data across multiple AWS Regions for fast local access and disaster recovery. Global tables do not automatically scale the provisioned capacity of each replica table; they still require manual or auto scaling settings2.

Option D is incorrect because using Amazon Simple Queue Service (Amazon SQS) and an AWS Lambda function to write to DynamoDB may introduce additional complexity and latency to the application architecture. Amazon SQS is a message queue service that decouples and coordinates the components of a distributed system. AWS Lambda is a serverless compute service that runs code in response to events. Using these services may require significant development effort to integrate them with the backend services and DynamoDB. Moreover, they may not improve the read performance of DynamoDB, which may also be affected by high traffic3.

Auto Scaling groups

DynamoDB auto scaling

AWS Lambda

DynamoDB global tables

AWS Lambda vs EC2: Comparison of AWS Compute Resources - Simform

Managing throughput capacity automatically with DynamoDB auto scaling - Amazon DynamoDB

AWS Aurora Global Database vs. DynamoDB Global Tables

Amazon Simple Queue Service (SQS)