Free Amazon Web Services SAA-C03 Practice Exam with Questions & Answers | Set: 9

Detailed Explanation:

A. ECS + API Gateway:Overly complex and costly for an on-demand, intermittent workload.

B. EventBridge + SNS:EventBridge schedules are unnecessary for on-demand generation.

C. EKS + API Gateway:Overkill for this use case, with high operational overhead.

D. Lambda + SES:Most cost-effective and efficient solution for generating and emailing reports on demand.

Amazon RDSMulti-AZ DB cluster deploymentensures high availability by automatically replicating data across multiple Availability Zones (AZs), and it supports failover in case of a failure in one AZ. This setup also provides increased capacity for read workloads by allowing read scaling with reader instances in different AZs. This solution offers the most operational efficiency with minimal manual intervention.

Option A (DynamoDB): DynamoDB is not suitable for a relational database workload, which requires a PostgreSQL engine.

Option B (RDS with Multi-AZ): While this provides high availability, it doesn't offer read scaling capabilities.

Option D (Cross-Region Read Replicas): This adds complexity and is not necessary if the requirement is high availability within a single region.

AWS References:

Amazon RDS Multi-AZ DB Cluster

S3 One Zone-IA:

Suitable for infrequently accessed data that doesn't require multiple Availability Zone resilience.

Cost-effective for storing user-uploaded images that are only used for AI model training twice a year.

S3 Standard:

Ideal for frequently accessed data with high durability and availability.

Store premium user-generated AI images here to ensure they are readily available for download at any time.

S3 Standard-IA:

Cost-effective storage for data that is accessed less frequently but still requires rapid retrieval.

Store non-premium user-generated AI images here, as these images are only downloaded once every 6 hours, making it a good balance between cost and accessibility.

Cost-Effectiveness: This solution optimizes storage costs by categorizing data based on access patterns and durability requirements, ensuring that each type of data is stored in the most cost-effective manner.

Why Option B is Correct:

AWS WAF: Provides a simple way to create geographic match rules to block or allow traffic based on country IP ranges.

Least Operational Overhead: Attaching the WAF rule to the ALB ensures centralized control without modifying ACLs or instance firewalls.

Why Other Options Are Not Ideal:

Option A: Network ACLs operate at the subnet level and can become complex to manage for dynamic or evolving IP ranges.

Option C: Managing IP-based rules in security groups and ACLs lacks scalability and does not provide country-based filtering.

Option D: Configuring host-based firewalls increases operational overhead and does not leverage AWS-managed solutions.

AWS References:

AWS WAF Geomatch:AWS Documentation - WAF Geomatch

Private subnets require outbound internet access to download updates, but they must not have public IPs or direct inbound access.

The recommended AWS solution is to create a NAT gateway in a public subnet. Private subnet route tables are updated to route internet-bound traffic (0.0.0.0/0) to the NAT gateway. The NAT gateway then uses the internet gateway attached to the VPC to communicate with the internet.

Option B (NAT instances) is an older approach and less scalable/maintainable than NAT gateways. Option C (egress-only internet gateway) is for IPv6 outbound-only traffic, not IPv4. Option D is invalid because NAT gateways must be deployed in public subnets.

To securely integrate Amazon S3 with an application that uses Amazon Cognito for user authentication, the following two steps are essential:

Step 1: Create an Amazon Cognito Identity Pool (Option A)

Amazon Cognito Identity Poolsallow users to obtain temporary AWS credentials to access AWS resources, such as Amazon S3, after successfully authenticating with the Cognito user pool. The identity pool bridges the gap between user authentication and AWS service access by generating temporary credentials using AWS Identity and Access Management (IAM).

Once a user logs in using theCognito User Pool, the identity pool providesIAM roles with specific permissionsthat the application can use to access S3 securely. This ensures that each user has appropriate access controls while accessing the S3 bucket.

This is a secure way to ensure that users only have temporary and least-privilege access to the S3 bucket for their documents.

Step 2: Create an Amazon S3 VPC Endpoint (Option C)

By creating anAmazon S3 VPC endpoint, the company ensures that communication between the application (which is hosted in a private subnet) and the S3 bucket occurs over theAWS private network, without the need to traverse the internet. This enhances security and prevents exposure of data to public networks.

TheVPC endpointallows the application to access the S3 bucket privately and securely within the VPC. It also ensures that traffic stays within the AWS network, reducing attack surface and improving overall security.

Why the Other Options Are Incorrect:

Option B: This is incorrect becauseAmazon Cognito User Poolsare used for user authentication, not for generating S3 access tokens. To provide S3 access, you need to useAmazon Cognito Identity Pools, which offer AWS credentials.

Option D: ANAT gatewayis unnecessary in this scenario. Using aVPC endpointfor S3 access provides a more secure and cost-effective solution by keeping traffic within AWS.

Option E: Attaching a policy to restrict access based on IP addresses is not scalable or efficient. It would require managing users’ dynamic IP addresses, which is not an effective security measure for this use case.

AWS References:

Amazon Cognito Identity Pools

Amazon VPC Endpoints for S3

Detailed Explanation:

A. RDS:Suitable for relational databases but does not provide native support for data lakes or row-level access.

B. Redshift:Primarily for analytics, not designed for large-scale data lake governance.

C. S3 + Lake Formation:Provides native support for data lakes with granular access control, including row-level permissions.

D. Glue Catalog + DataBrew:Focused on data preparation and metadata management, not row-level access control.

Amazon Elastic File System (Amazon EFS) is a fully managed, elastic, shared file system that can be mounted concurrently by multiple EC2 instances across multiple Availability Zones. EFS automatically grows and shrinks as files are added or removed, providing seamless scalability for unpredictable and growing storage needs. It supports simultaneous access from multiple compute resources, making it ideal for applications where several EC2 instances must read and write to the same data set concurrently. EBS volumes cannot be shared across multiple Availability Zones, and S3 Glacier is intended for archival and infrequent access, not for active, hourly data analysis.

Reference Extract from AWS Documentation / Study Guide:

"Amazon EFS provides a scalable, fully managed elastic NFS file system for use with AWS Cloud services and on-premises resources. It can be mounted to many EC2 instances across multiple Availability Zones and is ideal for shared data scenarios."

Source: AWS Certified Solutions Architect – Official Study Guide, Storage Solutions section; Amazon EFS User Guide.