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

AWS Transit Gateway is purpose-built for large-scale, hub-and-spoke network architectures. It simplifies connectivity between multiple VPCs and on-premises environments, which is ideal for managing hundreds of VPCs.

“AWS Transit Gateway enables you to connect your VPCs and on-premises networks through a central hub. This simplifies your network and puts an end to complex peering relationships.”

— Transit Gateway Documentation

Features:

Scales to thousands of VPCs.

Integrates with AWS Direct Connect via Direct Connect Gateway.

Centralized routing control.

Incorrect Options:

A: VPC endpoints are for private access to AWS services—not VPC-to-VPC connectivity.

C: Route 53 is DNS, not a network transport layer.

D: Secrets Manager is for secret storage, not networking.

DynamoDB Accelerator DAX is the best answer because it is a fully managed in-memory cache built specifically for DynamoDB. AWS documentation states that DAX is highly available, is designed for read-heavy workloads, and can deliver major latency improvements while reducing direct reads to DynamoDB. The question highlightskey-based lookupsandthroughput exceedederrors, which is the classic DAX use case. ElastiCache could be made to work, but it requires more application-side cache management and is not as tightly integrated with DynamoDB. Simply increasing read capacity manually is less cost-efficient and less adaptive. Copying the data to RDS adds unnecessary complexity and architectural drift. For the fewest changes and best DynamoDB-specific optimization, DAX is the correct answer. (AWS Documentation)

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Amazon EFS is a “fully managed, elastic, shared file system” that provides NFSv4 access across many EC2 instances and AZs, ideal for lift-and-shift of Linux NFS workloads. AWS DataSync “automates moving data between on-premises NFS servers and Amazon EFS,” performing incremental, parallel transfers with encryption and integrity checks, enabling cutover with minimal disruption. FSx for Lustre (A) targets HPC and S3-backed workloads, not general NFS shares. FSx for Windows (D) exposes SMB, not NFS. S3 (C) is object storage and not directly NFS-accessible by multiple EC2 hosts. EFS + DataSync satisfies NFS compatibility, multi-client access, and low-touch migration while remaining cost-effective for a 200-GB dataset.

AWS documentation states that the most secure method for granting private S3 access from VPCs is to use gateway VPC endpoints for Amazon S3. Endpoint policies enforce least privilege by allowing only specific IAM roles access to specific S3 buckets. Because users can obtain temporary credentials through IAM roles, no permanent access keys must be distributed.

S3 bucket policies based on CIDR ranges (Option B) are less secure because CIDR-based access is broader and can grant unintended access. Access points (Option C) still rely on public S3 endpoints unless combined with VPC-only access, which is not stated here. Option D exposes S3 to public internet egress and depends on public IPs, violating least-privilege principles.

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To decouple the monolith and enhance scalability, AWS best practice is to introduce an asynchronous message queue, such as Amazon SQS, between the web/API tier and the order-processing logic.

AWS Lambda functions consuming from the SQS queue provide serverless, auto-scaling processing without managing servers.

To track and reprocess failed orders, SQS supports dead-letter queues (DLQs). Messages that cannot be processed successfully after a configurable number of attempts are automatically moved to the DLQ, where operations teams or automated processes can inspect and reprocess them.

Why others are not correct:

B: ECS tasks can consume an SQS queue, but this requires managing container infrastructure and does not inherently provide as simple reprocessing/visibility as combining Lambda with a DLQ. Visibility timeout is not a tracking or archival mechanism.

C: Kinesis is a streaming service designed for ordered event streams, not primarily for order-queue semantics and DLQs; SQS is simpler and purpose-built for this pattern.

D: Long polling reduces empty responses and API calls but does nothing for tracking or reprocessing failed messages; without a DLQ, failed orders are harder to manage

A cost-optimized pattern is to stream DynamoDB changes to Amazon S3 and then query and visualize from the data lake. AWS documentation explains that DynamoDB changes can be captured in near real time and delivered to Amazon S3 by using Kinesis Data Streams and Amazon Data Firehose. AWS also notes that Firehose delivery to S3 supports high-performance, cost-efficient analytics with services such as Athena and QuickSight. Athena is serverless and queries data directly in S3, which avoids maintaining a data warehouse for this historical reporting use case. QuickSight can connect to Athena for dashboards and reports. This combination gives the company low-cost archival storage in S3, SQL query capability through Athena, and visualization through QuickSight, all without keeping old reporting data in the operational DynamoDB table.

Here is thenext batch of 10 TXT-only unique questionsthat werenot found in the Word file, in your required format.

AWS Budgets allows you to set custom cost and usage budgets. When actual or forecasted usage exceeds the threshold, AWS Budgets can automatically send alerts to an Amazon SNS topic. You can use AWS Cost Explorer in parallel for visual tracking of spending. This solution requires no code and has minimal operational overhead.

Option Aintroduces complexity and does not scale well.

Option Bcreates a read replica, offloading read traffic from the primary RDS instance without impacting the critical application.

Option Cis manual and inefficient.

Option Dmight help for caching frequently queried data but is not ideal for ad-hoc reporting.Therefore, Option B is the best choice.

The ALB must be in a public subnet to receive internet traffic. The EC2 instances and the RDS database should be in private subnets to prevent direct internet access, minimizing the attack surface. This aligns with AWS security best practices for web application architectures.

Reference Extract:

" Internet-facing ALBs should be placed in public subnets; EC2 instances and RDS databases should be in private subnets to restrict direct internet access. "

Source: AWS Certified Solutions Architect – Official Study Guide, Network Security and Design section.

The most cost-effective solution for serving video content with different bitrates is to store multiple versions of each video inAmazon S3. S3 provides scalable and cost-effective storage for largemedia files. Serving the videos from a single Amazon EC2 instance ensures low-latency delivery, and S3 storage helps minimize costs.

Option A (ElastiCache): Caching large video files in memory would be prohibitively expensive and unnecessary.

Option B (Auto Scaling group): Using Auto Scaling groups to serve video is less cost-effective compared to leveraging S3 for static storage.

Option D (Kinesis Video Streams): Kinesis Video Streams is designed for real-time video streaming and is not suitable for storing and serving pre-recorded videos.

AWS References:

Amazon S3 for Media Storage

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 application must stay private in bothnetwork accessandDNS resolution. Aninternal ALBensures the load balancer is reachable only from within the VPC or connected private networks. ARoute 53 private hosted zoneensures the DNS name is resolvable only from associated VPCs. AWS documentation states that private hosted zones return answers only when queries come from associated VPCs or approved hybrid resolvers, while queries from outside are not resolved from that private zone. A public hosted zone would expose DNS resolution publicly, and an internet-facing ALB would violate the private-access requirement. Therefore, the correct solution isan internal ALB plus a private hosted zone. (AWS Documentation)

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Lambda supports mounting an Amazon EFS file system inside your function to store larger dependencies beyond the 250 MB layer quota.

EFS automatically encrypts data in transit using TLS.

“You can configure your Lambda function to mount an Amazon EFS file system, enabling your function to access large amounts of data or large dependencies.”

“Amazon EFS automatically encrypts all data at rest and in transit.”

— Lambda with Amazon EFS

This is the least operational overhead approach.

The correct answers areA and D. The requirement is to replace third-party middleware with an AWS-native solution that supportsasynchronous communication,exactly-once delivery, and theleast infrastructure management.Amazon SQS FIFO queuesare the best messaging component because FIFO queues are designed for workloads that requireordered processingandexactly-once message deliverysemantics. That makes optionDthe correct messaging choice.

For the compute layer,AWS Lambdaprovides the least infrastructure management because it is a fully managed serverless compute service. Lambda removes the need to manage virtual machines, operating systems, or cluster infrastructure. It integrates naturally with queue-based asynchronous architectures and can be invoked to process messages from SQS while scaling automatically based on queue depth and workload demand. That makes optionAthe best choice for minimizing operational burden.

Option B is incorrect because EC2 instances would require the company to manage instance provisioning, patching, scaling, and availability. Option C is incorrect becauseAmazon SNSis a pub/sub messaging service and does not provide exactly-once delivery guarantees likeSQS FIFO. Option E is incorrect becauseAmazon EKSintroduces Kubernetes management overhead and is not the lowest-management compute option.

AWS best practices recommend using managed messaging and serverless compute to reduce undifferentiated operational work. For a migration that requires asynchronous processing with exactly-once delivery and minimal infrastructure management, the most appropriate architecture isAWS Lambda functionswithAmazon SQS FIFO queues.

Amazon Elastic File System (EFS) is the ideal solution for migrating legacy applications that require NFS (Network File System) communication. EFS provides fully managed, scalable NFS storage in the cloud, and it supports the standard NFS protocols, allowing the legacy application to continue using NFS without modification after migration to AWS.

Key AWS features:

NFS Support: EFS natively supports the NFSv4 protocol, which makes it the best solution for workloads that rely on NFS communication.

Scalability and Availability: EFS automatically scales as application demands grow, making it a highly available and reliable storage solution.

AWS Documentation: According to AWS’s best practices for file storage, EFS is recommended for any workloads requiring NFS support in a cloud environment​​.

Deploying the web application on EC2 instances in private subnets behind an internal ALB ensures that the application is not directly accessible from the internet. By setting up a Site-to-Site VPN connection, the application can be accessed securely from the company ' s office network. Deploying NAT gateways in public subnets allows instances in private subnets to initiate outbound connections to the internet for downloading security patches.

Versioning in S3 preserves every version of every object — preventing permanent overwrites. This ensures compliance where data cannot be overwritten or lost.

SSE-S3 ensures server-side encryption.

“When you enable versioning, Amazon S3 stores every version of every object. With versioning, you can preserve, retrieve, and restore every version of every object stored in an S3 bucket.”

— S3 Versioning

This satisfies regulatory requirements for protecting data from overwriting indefinitely.

Incorrect Options:

B: Object Lock with retention period is time-bound, not indefinite.

C: Legal hold blocks deletion but doesn’t directly prevent overwriting.

D: Storage Lens is analytics, not protection.

Enabling Multi-AZ deployment for an Amazon RDS DB instance is the simplest and most effective way to improve database availability and eliminate a single point of failure. Multi-AZ deployments provide automatic failover to a standby instance in case of a failure of the primary instance. This approach is managed by AWS and only requires a modification to the existing instance, with minimal manual intervention or downtime, thus providing the least implementation effort.

Reference Extract from AWS Documentation / Study Guide:

" With Multi-AZ deployments, Amazon RDS automatically creates a primary DB Instance and synchronously replicates the data to a standby instance in a different Availability Zone (AZ). In case of a failure of the primary DB Instance, Amazon RDS automatically fails over to the standby so that database operations can resume quickly. "

Source: AWS Certified Solutions Architect – Official Study Guide, RDS High Availability section.

The application requires independent scaling, ordered asynchronous processing, and relational data storage. Option A provides a microservices-oriented, decoupled architecture using managed services.

Amazon ECS with AWS Fargate enables containerized workloads without server management and allows each component to scale independently. Amazon RDS supports relational data storage for user profiles and content. Amazon SQS ensures reliable, ordered message processing and decouples long-running background tasks, allowing services to evolve independently.

Option B uses SNS, which does not guarantee message ordering. Option C uses DynamoDB, which does not meet the relational data requirement. Option D offers less granular scaling and higher coupling.

Therefore, A best meets scalability, resilience, and modularity requirements.

Usingcross-account IAM rolesis the most secure and scalable way to share data between AWS accounts.

Atrust relationshipallows the analytics team ' s account to assume the role in the main account and access the DynamoDB table directly.

Ais feasible but involves data duplication and additional costs for storing the JSON files in S3.

B and Cviolate security best practices by allowing public access to sensitive data and sharing credentials, which is highly discouraged.

AWS Documentation Reference:

Cross-Account Access with Roles

Best Practices for Amazon DynamoDB Security