SAA-C03 Exam Dumps - Amazon Web Services AWS Certified Associate Questions and Answers

Amazon SQS FIFO queues support deduplication and ordering. AWS documents thatMessageDeduplicationIdis used with FIFO queues to prevent duplicate delivery within a5-minute deduplication window, which matches this requirement exactly. Standard queues do not provide this deduplication guarantee, and SNS filter policies are not a deduplication mechanism for this use case. Because the company wants the least development effort, using API Gateway to place messages directly on an SQS FIFO queue with a deduplication token is the cleanest approach.

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Amazon RDS Custom for Oracle: This service allows you to bring your own Oracle Database licenses and provides the flexibility to customize the database settings, making it suitable for applications that require privileged access and third-party database features.

BYOL (Bring Your Own License):

RDS Custom supports the BYOL model, allowing you to use your existing Oracle licenses and comply with licensing requirements.

This helps in leveraging existing investments and reducing migration costs.

Customization and Third-Party Features:

RDS Custom allows for deeper customization of the database environment compared to standard RDS instances.

This makes it possible to support the third-party features that your application relies on without significant changes.

Migration Process:

Use native Oracle tools like Data Pump or RMAN to migrate the database to RDS Custom.

Customize the database settings post-migration to ensure compatibility with third-party features.

AWS PrivateLinkis the most suitable solution for providing fine-grained access control while allowing multiple VPCs, potentially across multiple accounts, to access the new application. This approach offers the following advantages:

Fine-grained control: Endpoint policies can restrict access to specific services or principals.

No need for route table updates: Unlike VPC peering or transit gateways, AWS PrivateLink does not require complex route table management.

Scalable architecture: PrivateLink scales to support traffic from multiple VPCs.

Secure connectivity: Ensures private connectivity over the AWS network, without exposing resources to the internet.

Why Other Options Are Not Ideal:

Option A:

VPC peering is not scalable when connecting multiple VPCs or accounts.

Route table management becomes complex as the number of VPCs increases.Not scalable.

Option B:

While transit gateways provide scalable VPC connectivity, they are not ideal for fine-grained access control.

Transit gateways allow connectivity but do not inherently restrict access to specific applications.Not ideal for fine-grained access control.

Option D:

Exposing the application through an ALB over the internet is not secure and does not align with the requirement to use private network resources.Security risk.

AWS References:

AWS PrivateLink:AWS Documentation - PrivateLink

AWS Networking Services Comparison:AWS Whitepaper - Networking Services

Protecting an application from layer 7 (application layer) DDoS attacks is best achieved by using AWS WAF (Web Application Firewall), which provides customizable protection against common web exploits including DDoS attacks at the application layer. AWS WAF supports managed rule groups maintained by AWS, which offer robust, tested protections against OWASP top 10 vulnerabilities and common attack patterns without requiring extensive manual rule creation.

While AWS Shield Standard provides basic network-layer DDoS protection automatically at no additional charge, it does not offer application-layer filtering capabilities. Therefore, option A alone is insufficient.

Option B, involving only custom rules, requires significant operational overhead and expertise, whereas AWS managed rules offer a turnkey solution with ongoing updates from AWS security teams.

Option D, using CloudFront in front of the ALB, can provide additional protection benefits such as caching and geographic restrictions, but the question specifically asks for protecting against layer 7 DDoS on the ALB directly. CloudFront plus WAF is a valid enhanced solution, but the direct and recommended answer in AWS official documents is to use AWS WAF managed rules directly with ALB for application-level protection.

To securely migrate an on-premises Oracle database to Amazon Aurora, the following steps are recommended:

Use AWS Schema Conversion Tool (AWS SCT) and AWS Database Migration Service (AWS DMS): AWS SCT helps convert the source database schema to a format compatible with the target database (Aurora). AWS DMS facilitates the actual data migration, ensuring minimal downtime and data integrity.

Use AWS Site-to-Site VPN: Establishing a Site-to-Site VPN connection provides a secure and encrypted tunnel between the on-premises environment and AWS. This ensures that data transferred during the migration is protected against interception and unauthorized access.

To decouple distributed workloads and improve scalability and resiliency, Amazon SQS should be used as a reliable job queue. The compute nodes (workers) can poll the SQS queue for tasks, and EC2 Auto Scaling can dynamically scale instances based on the ApproximateNumberOfMessages metric.

From AWS Documentation:

“Amazon SQS enables you to decouple application components, allowing each part to scale independently. You can scale EC2 instances automatically based on the number of messages in the queue.”

(Source: Amazon SQS Developer Guide – Scaling Consumers with Auto Scaling)

Why B is correct:

Eliminates the single point of failure (the primary coordinator).

Enables event-driven scaling based on queue depth.

Provides durability and resiliency since messages are stored redundantly.

Fully managed and integrates seamlessly with Auto Scaling policies.

Why other options are incorrect:

A: Scheduled scaling does not respond to variable workloads.

C & D: Misuse of CloudTrail/EventBridge; not intended for workload coordination.

AWS Database Migration Service can migrate relational data toAmazon S3 in Apache Parquet format, which is a strong archival format for analytics. AWS also documents that Parquet in S3 can be queried byAmazon Athena, which removes the need to keep a database engine running just for annual reports. This is much lower-overhead than maintaining RDS or EC2 instances solely for occasional querying. Among the options, D is the only one that uses a serverless query service over archived relational data. Glacier Flexible Retrieval also fits archived data better than keeping a live relational instance. This makes D the most cost-effective and least operationally heavy approach. (docs.aws.amazon.com)

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AmazonTextractcan extract text from the PDFs, andAmazon Comprehendis the most suitable service to analyze the extracted text for sentiment and insights. Comprehend offers a fully managed, low-operational overhead solution for analyzing text data. The results can then be stored in anAmazon S3bucket, ensuring scalability and easy access.

Option A: Athena is for querying structured data and is not suitable for sentiment analysis.

Option B: SageMaker adds complexity and is not necessary when Comprehend can handle sentiment analysis natively.

Option D: QuickSight is used for visualization and analytics, but it does not provide sentiment analysis.

AWS References:

Amazon Comprehend

Amazon Textract

AWS STS is the best choice because it issuestemporary security credentialsthat expire automatically, which removes the need to create and later deactivate long-lived IAM users. AWS guidance for third-party and short-term access explicitly recommends roles and temporary credentials instead of sharing long-term credentials. Using predefined IAM roles also makes it easy to assign different permission levels to different contractors while keeping access centrally controlled. IAM users create more administrative effort and leave credential-lifecycle management to the company. AWS Config and CloudTrail are useful for governance and auditing, but they are not the primary mechanism for granting short-term role-based access. Therefore, STS with predefined roles is the most secure and lowest-overhead solution.

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AWS Step Functions is designed to coordinate multiple AWS services into serverless workflows, handling errors, retries, and complex logic. By configuring Amazon S3 Event Notifications to trigger an Amazon EventBridge rule, you can automatically start a Step Functions workflow when a new object is uploaded to S3. Step Functions can manage retries for failed uploads and orchestrate calls to various AWS services with minimal operational effort.

AWS Documentation Extract:

“You can use Amazon EventBridge to initiate AWS Step Functions workflows in response to events from S3 buckets. Step Functions can orchestrate the sequence of AWS service calls and automatically handle retries and errors, making it ideal for automating and managing complex workflows.”

(Source: AWS Step Functions documentation, Using Step Functions with EventBridge and S3)

Other options:

A: Requires manual implementation of orchestration and error handling.

B & C: Involve additional infrastructure management and custom logic for workflow orchestration and error handling, increasing operational effort.

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.

TheGateway Load Balancer (GWLB)is specifically designed to route traffic through a security appliance in a hub-and-spoke model, making it the ideal solution for inspecting traffic between multiple AWS accounts. GWLB enables you to simplify, scale, and deploy third-party virtual appliances transparently, and it can work across multiple VPCs or accounts using interface endpoints (Gateway Load Balancer Endpoints).

Key AWS features:

Traffic Inspection: The GWLB allows the centralized security appliance to inspect traffic between different VPCs, making it suitable for inspecting inter-account interactions.

Interface VPC Endpoints: By using interface endpoints in the application accounts, traffic can securely and efficiently be routed to the security appliance in the networking account.

AWS Documentation: The use of GWLB aligns with AWS’s best practices for centralized network security, simplifying architecture and reducing operational complexity​.

AWS Firewall Manager integrates with AWS Organizations to centrally manage and apply security group policies, AWS WAF rules, and AWS Shield Advanced protections. It automates the propagation of rules across accounts and Regions and can also audit and remediate noncompliant configurations.

AWS guidance for global, highly available, low-latency applications using a relational database recommends:

Amazon CloudFront with Amazon S3 for static content to cache data at edge locations globally and minimize latency for static assets.

A regional application tier deployed close to users using managed container services such as Amazon ECS on AWS Fargate, which removes the need to manage servers and scales automatically, reducing operational overhead.

A relational database tier using Amazon Aurora global database, which is purpose-built for globally distributed applications. Aurora global database provides a primary cluster in one Region with low-latency read replicas in secondary Regions and fast cross-Region replication, enabling low-latency reads and high availability for global users.

Option A uses only a single Region, which does not meet the “global users with low latency” requirement.

Option C uses RDS and DMS-based replication, which requires more management and does not provide Aurora’s integrated global database features.

Option D replaces the relational database with DynamoDB, which violates the requirement that the application interacts with a relational database.

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.

Amazon EFS lifecycle management is the correct solution because it reduces storage cost while preserving the same file-system interface and mount points. The files are frequently accessed for the first 90 days and then become rarely accessed, so transitioning inactive files to EFS Infrequent Access matches the access pattern. This requires no application change and no remounting because the same EFS file system remains mounted on the EC2 instances. Amazon EFS Regional file systems can store data across multiple Availability Zones for high availability, and lifecycle policies can move files from Standard storage to IA based on access age. Moving to S3 or Glacier would change access patterns and introduce operational work that the company wants to avoid.

Amazon SQS decouples video uploads from processing and buffers bursts when many videos arrive simultaneously. Lambda polls the queue, retrieves messages in batches, and scales the number of concurrent processing environments according to queue demand. Reserved or maximum concurrency can protect downstream resources and prevent uncontrolled scaling. API Gateway does not solve asynchronous workload buffering, and continuously polling S3 with one Fargate task would process videos inefficiently and create a scalability bottleneck. However, the Lambda function timeout must also be configured high enough for the processing duration. AWS Lambda supports a maximum timeout of 900 seconds, or 15 minutes. Therefore, option C is the intended scalable architecture, provided the function timeout and SQS visibility timeout are configured to exceed the expected processing duration.

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Amazon Athenais a serverless query service that allows you to run SQL queries directly on data stored in Amazon S3 without the need for a data warehouse. It is cost-effective because you only pay for the queries you run, and it can handleApache Parquetfiles efficiently. Additionally, Athena integrates with KMS, making it suitable for querying encrypted data.

Key AWS features:

Cost-Effective: Athena charges only for the data scanned by the queries, making it a more cost-effective solution compared to Redshift or EMR for occasional queries.

Direct S3 Querying: Athena supports querying data directly in S3, including Parquet files, without needing to move the data.

AWS Documentation: Athena ' s compatibility with encrypted Parquet files in S3 makes it the ideal choice for this scenario, reducing both cost and complexity​​.

AWS Service Catalogallows organizations to centrally manage commonly deployed IT services and offers self-service deployment capabilities to customers. By creatingService Catalog products, the consulting company can package their solutions and tools for easy reuse by customers while maintaining central control over configuration and access. This provides a standardized and automated solution with the least operational overhead for managing and deploying solutions across different customers.

Option A (CloudFormation): CloudFormation templates are useful but don ' t provide the same level of management and user-friendly self-service capabilities as Service Catalog.

Option C (Systems Manager): Systems Manager is more focused on managing infrastructure and doesn ' t offer the same self-service capabilities.

Option D (AWS Config): AWS Config is used for tracking resource configurations, not for deploying solutions.

AWS References:

AWS Service Catalog