Free Amazon Web Services SAA-C03 Practice Exam with Questions & Answers | Set: 3

Amazon SQS is the best messaging layer here because it providesdurable bufferingand decouples microservices so they can scale independently while absorbing bursts without losing data. AWS recommends SQS for decoupled architectures where producers and consumers operate at different speeds. For compute,AWS Fargatereduces operational overhead because AWS manages the underlying servers, patching, and capacity layer. API Gateway and WebSockets are not the primary answer for internal asynchronous microservice communication, and SNS is fanout-oriented rather than the most natural queueing model for durable work processing between services. Therefore, SQS plus ECS on Fargate is the most appropriate low-overhead design.

============

To restrict S3 access to a specific VPC, AWS documentation specifies using a Deny policy with aws:SourceVpc for all unmatched VPCs:

Deny if aws:SourceVpc != vpc-11aabb22

This ensures only that VPC can reach the bucket via a VPC endpoint.

Allow policies (Options B and C) are incorrectly structured or use the wrong condition logic.

Option D limits by account, not VPC, and does not enforce VPC-level access.

=====================================================

AWSService Catalogis designed to allow organizations to manage a catalog of approved products (including AMIs) that users can deploy. By creating a portfolio that contains only EC2 instances launched with preapproved AMIs, the company can enforce compliance with the approved operating system and software for all EC2 instances. Service Catalog also streamlines the process of launching EC2 instances, reducing the lead time while ensuring that developers use only the approved configurations.

Option B (EC2 Image Builder): While EC2 Image Builder helps in creating and managing AMIs, it doesn ' t provide the enforcement mechanism that Service Catalog does.

Option C (EventBridge rule and Systems Manager script): This solution is reactive and involves more operational complexity compared to Service Catalog.

Option D (AWS Config rule): This option is reactive (it terminates non-compliant instances after launch) and introduces additional operational overhead.

AWS References:

AWS Service Catalog

Amazon S3 Glacier Flexible Retrieval is a low-cost archival storage class that supports retrieval of data within minutes (expedited access ~1–5 minutes), making it ideal for audit scenarios where occasional, quick access to archived data is required. In contrast, Glacier Deep Archive takes hours to retrieve.

The best practice for secure access control in AWS is to use IAM roles with least-privilege policies, granting only the permissions necessary to perform required tasks. Assigning roles individually ensures that developers cannot overstep their intended access boundaries.

Sharing credentials or using permanent access keys increases the risk of security breaches. Cognito is primarily intended for managing user access to applications, not AWS infrastructure. Thus, Option B best meets security and access control requirements.

Spot Instances can be interrupted when AWS needs the capacity back. To reduce interruptions and improve availability, AWS provides the capacity-optimized allocation strategy.

Capacity-optimized strategy launches Spot Instances from the most available Spot capacity pools instead of the lowest-priced ones, reducing interruption rates.

By adding multiple instance types (e.g., using Instance Type Flexibility), the Auto Scaling group can launch instances in a broader set of pools, improving the chance that capacity is available.

Scheduled scaling actions combined with a diverse set of instances under the capacity-optimized strategy ensure higher resilience and better timing for instance launches.

This approach directly supports the Resiliency design principle in the AWS Well-Architected Framework.

???? References:

Best Practices for EC2 Spot Instances

Capacity-Optimized Allocation Strategy

The best design is todecouple the two stages with SQS queuesand scale each Auto Scaling group based onqueue depth. Amazon SQS provides durable message storage, so orders are not lost if one processing tier scales slowly or temporarily falls behind. AWS recommends queue-based scaling when producers and consumers operate at different speeds. Monitoring CPU alone does not reflect business backlog accurately, but queue length directly represents pending work. Using two queues also lets the company scale collection and fulfillment independently, which is important because fulfillment takes longer than collection. This is the most resilient and scalable pattern for variable order traffic.

============

Among the listed choices, the best solution is to place an AWS Lambda function in the same VPC and use it as the EventBridge target. EventBridge natively supports Lambda as a target, and a Lambda function that runs in the VPC can call the private API without exposing that API publicly. The internet-facing ALB and NLB options violate the requirement to avoid public IP exposure. The direct-target option is also not expressed correctly for a plain private API endpoint, because modern direct private API targeting in EventBridge requiresconnections and VPC Lattice resource configurations, not simply naming a private VPC endpoint as a raw target. Therefore, Lambda as the bridge component is the correct answer from the provided choices. (AWS Documentation)

============

A. API Gateway + DynamoDB:Provides high scalability, low latency, and seamless integration with Amazon Comprehend for NLP tasks.

B. HTTP API + Translate + ElastiCache:Translate is not relevant for NLP tasks like sentiment analysis or entity recognition. ElastiCache is unsuitable for permanent storage.

C. SQS + EC2 + RDS:Increases complexity and operational overhead. RDS may not scale effectively for high concurrent loads.

D. WebSocket API + Textract:Textract is irrelevant for NLP tasks. WebSocket API is not the optimal choice for this use case.

Amazon S3 is suitable for storing data that needs to be accessed weekly and integrates with AWS Key Management Service (KMS) to provide encryption at rest with server-side encryption using KMS-managed keys (SSE-KMS).

SSE-KMS uses envelope encryption and allows automatic key rotation and logging through AWS CloudTrail, satisfying the requirements for audit trails and compliance.

S3 Glacier Deep Archive is unsuitable due to its high retrieval latency. SSE-C requires customer-side management of encryption keys, with no support for automatic rotation or audit. SSE-S3 does not use customer-managed keys and lacks fine-grained control and auditing.

Amazon Managed Streaming for Apache Kafka (Amazon MSK) is a fully managed service that makes it easy to build and run applications that use Apache Kafka to process streaming data. By using Amazon ECS with the AWS Fargate launch type, you can run containers without managing servers or clusters. This combination reduces operational overhead and provides scalability.

The key requirements are shared file access, NFS protocol compatibility, and no application changes. Amazon Elastic File System (EFS) is a fully managed, scalable file system that natively supports the NFS protocol, making it an ideal drop-in replacement for on-premises shared file systems used by Linux applications.

Option C allows the existing web servers to mount the EFS file system using standard NFS mount commands, preserving application behavior and avoiding code changes. EFS is designed to be accessed concurrently by multiple EC2 instances across Availability Zones, providing high availability and elasticity without manual capacity management. This aligns well with typical web server architectures that rely on shared content or assets.

Option A and B use Amazon S3, which is an object storage service and does not support NFS semantics. Migrating to S3 would require application changes to use object-based APIs instead of file system operations. Option D uses Amazon FSx for Windows File Server, which supports SMB, not NFS, and is intended for Windows-based workloads.

Therefore, C is the correct solution because Amazon EFS provides NFS compatibility, shared access, high availability, and minimal operational overhead while requiring no changes to the existing Linux-based web server applications.

S3 Standard is appropriate for temporary files that will be processed and moved quickly because it has no minimum storage-duration charge. S3 Standard-IA would be inefficient for short-lived temporary objects because it applies minimum storage-duration and minimum billable object-size considerations. S3 Event Notifications can invoke Lambda directly when objects are created, enabling event-driven preprocessing without polling. Lambda event source mappings are used with supported stream and queue sources, such as Amazon SQS or Kinesis, rather than directly with S3 buckets. Combining very small files into a larger ZIP archive reduces the number of archived objects, retrieval requests, and per-object metadata overhead associated with archival storage. Moving each small file to S3 One Zone-IA would add an unnecessary intermediate tier and provide lower resilience before archival. Therefore, A, B, and D form the most economical workflow.

================

The correct solution is to create anIAM roleand attach it to the EC2 instance profile. AWS documentation states that applications running on EC2 should use IAM roles so the instance can receivetemporary credentials automaticallythrough the instance metadata service. This avoids embedding long-term access keys in code or on the server. DynamoDB supports IAM and temporary credentials, so the application can use the role’s permissions to access the table securely. EC2 key pairs are only for SSH access and have nothing to do with DynamoDB authorization. IAM users and long-term access keys are less secure and create unnecessary credential management overhead.

============

CloudFront geographic restrictions (also known as geo-blocking) allow you to allow or deny content delivery to specific countries with minimal configuration.

“You can use geo restriction, also known as geoblocking, to prevent users in specific geographic locations from accessing content that you ' re distributing through a CloudFront web distribution.”

— CloudFront Geo Restriction

This is the most operationally efficient approach — no code, no signed URL logic.

Incorrect Options:

A/C: Signed URLs/cookies are for individual access control, not geo-blocking.

D: OAC controls access between CloudFront and S3, not to block specific countries.

AWSSecrets Manageris the best solution for securely storing and managing sensitive information, such as usernames and passwords. Secrets Manager provides automatic rotation, fine-grained access control, and encryption of credentials. It is designed to integrate easily with other AWS services, such as CloudFormation, to automate the retrieval of secrets via theBatchGetSecretValue API.

Secrets Manager has a lower operational overhead than manually managing credentials, and it offers features like automatic secret rotation that reduce the need for human intervention.

Option A and C (Parameter Store): While Systems Manager Parameter Store can store secrets, Secrets Manager provides more specialized capabilities for securely managing and rotating credentials with less operational overhead.

Option B and C (AWS Batch): Introducing AWS Batch unnecessarily complicates the solution. Secrets Manager already provides simple API calls for retrieving secrets without needing an additional service.

AWS References:

AWS Secrets Manager

Secrets Manager with CloudFormation

IAM Access Analyzeris the correct service because AWS documents that it helps identify and reviewunused accessfor IAM users and roles across AWS accounts and organizations. It can generate findings that show where permissions are broader than necessary and can recommend narrower policies when applicable. Network Access Analyzer focuses on network reachability, not IAM over-permission. CloudWatch alarms on user activity do not analyze granted permissions, and Amazon Inspector is not the service for IAM permission-rightsizing. Since the company wants the least administrative overhead across multiple accounts managed with AWS Organizations, IAM Access Analyzer is the AWS-native service purpose-built for this kind of access review. (AWS Documentation)

============

Workload Discovery on AWS is a tool that automatically discovers AWS resources across multiple accounts and Regions and builds visual architecture diagrams that show resource relationships. It is specifically designed to help teams understand and document existing workloads with minimal manual effort.

This service provides multi-account visibility, relationship mapping, and exportable diagrams, which directly satisfies the need to “build and map the relationship details of the various workloads” with the least operational overhead.

Systems Manager Inventory (Option A) focuses on collecting configuration and inventory data (primarily for instances and some resources) and does not generate architecture diagrams or full relationship views.

Step Functions (Option B) and X-Ray (Option D) would require custom collection and manual diagramming and are not purpose-built for environment discovery and mapping.

Key Requirements:

Serverless architecture.

Handle traffic bursts with high availability.

Process orders asynchronouslyin the order they are received.

Analysis of Options:

Option A:Amazon SNS delivers messages to subscribers. However, SNS does not ensure ordering, making it unsuitable for FIFO (First In, First Out) requirements.

Option B:Amazon SQS FIFO queues support ordering and ensure messages are delivered exactly once. AWS Lambda functions can be triggered by SQS to process messages asynchronously and efficiently. This satisfies all requirements.

Option C:Amazon SQS standard queues do not guarantee message order and have " at-least-once " delivery, making them unsuitable for the FIFO requirement.

Option D:Similar to Option A, SNS does not ensure message ordering, and using AWS Batch adds complexity without directly addressing the requirements.

AWS References:

Amazon SQS FIFO Queues

AWS Lambda and SQS Integration

Amazon SQS supports Interface VPC endpoints (AWS PrivateLink), enabling private connectivity from your VPC to SQS without using public IPs, traversing the public Internet, or requiring NAT/IGW. You can restrict access by attaching a queue resource policy that allows only the specific VPC endpoint and denies all other principals/paths, enforcing that all traffic stays on the AWS network. SSE-SQS (B) encrypts data at rest but does not influence network pathing. STS temporary credentials (C) handle authentication/authorization, not routing. VPC Flow Logs (D) are monitoring/visibility and do not prevent public egress. Creating an SQS VPC endpoint and tightening the queue policy satisfies the requirement of no public IP usage while maintaining secure, private access from serverless components in VPC subnets.