Free Amazon Web Services SAA-C03 Practice Exam with Questions & Answers | Set: 6

AWS Glue provides a serverless ETL solution requiring minimal development. Glue supports conversion to Parquet with managed jobs and integrates with S3 for output.

AWS Documentation References:

AWS Glue Overview

For SQS-backed worker architectures, AWS recommends scaling consumers based on queue metrics (e.g., ApproximateNumberOfMessagesVisible, AgeOfOldestMessage). EC2 Auto Scaling can “scale out based on Amazon CloudWatch alarms” tied to SQS backlog, increasing worker capacity to reduce latency as demand grows. DAX (A) accelerates DynamoDB reads, not message processing. API Gateway (B) and CloudFront (C) optimize request ingress and content delivery, not the asynchronous email-sending application. The bottleneck is consumer throughput; scaling workers with an SQS-driven policy restores timely processing without downtime and follows Well-Architected patterns for decoupled, elastic systems.

The requirement is an event-driven pub/sub system that guarantees ordered delivery of events.

Amazon SNS FIFO topics provide the publish-subscribe model along with FIFO (First-In-First-Out) delivery and exactly-once message processing, ensuring ordered delivery to multiple subscribers.

Option A, EventBridge, provides event buses but does not guarantee event ordering across multiple subscribers. Option C (SNS standard topics) provides pub/sub but without ordering guarantees. Option D (SQS FIFO queues) guarantees order but are point-to-point queues, not pub/sub.

Thus, Amazon SNS FIFO topics meet the requirements for ordered pub/sub messaging.

The requirement that the security team manage key lifecycle actions such as creation, deletion, and rotation points tocustomer managed AWS KMS keys, not SSE-S3. Customer managed KMS keys allow fine-grained IAM authorization for both the Lambda execution role and the security administrator group. That supports least privilege because the Lambda role can be restricted to decrypt usage, while the administrator group can be limited to the KMS management actions it actually needs. The other answers either do not provide the required KMS management control or grant permissions too broadly. Therefore, using customer managed KMS keys with separate, scoped IAM permissions for decryption and key administration is the correct design.

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AWS WAF (Web Application Firewall) is designed to protect public-facing web applications from common web exploits and allows for deep inspection of HTTP and HTTPS requests. By enabling logging on AWS WAF, you can gain insights into traffic flow, request sources, and blocked requests, which improves both security visibility and posture. Integrating AWS WAF logging with Amazon Kinesis Data Firehose allows automatic, near-real-time delivery of log data to Amazon S3 for analysis, reporting, or integration with analytics tools. This solution not only secures the website but also enables comprehensive traffic analysis, satisfying both requirements efficiently.

Reference Extract from AWS Documentation / Study Guide:

" AWS WAF provides detailed logs of web requests, which can be delivered to Amazon S3 via Amazon Kinesis Data Firehose. This logging enables analysis of web traffic and sources, supporting both security and operational monitoring. "

Source: AWS Certified Solutions Architect – Official Study Guide, Security and Compliance section; AWS WAF Developer Guide (Logging and Monitoring).

DynamoDB on-demand capacity mode is the best fit when traffic is unpredictable and the application must automatically scale read and write throughput without capacity planning. In on-demand mode, DynamoDB instantly accommodates changing request rates and charges based on actual read and write requests, which avoids over-provisioning for unknown traffic patterns. The DynamoDB Standard table class is appropriate because the workload expects moderate to high read and write activity. DynamoDB Standard-IA is designed for tables where storage is dominant and access is infrequent, so it is not the best match for an actively used web application backend. Provisioned capacity with auto scaling can be cost-effective for predictable workloads, but unpredictable traffic makes on-demand mode the safer and more operationally efficient choice.

Amazon Route 53 supports failover routing policies, which use health checks to route DNS queries to a secondary Region only if the primary endpoint fails. This design ensures only one Region is active for traffic at any given time. This is the recommended architecture for active-passive, multi-Region DR strategies.

AWS Documentation Extract:

“Failover routing lets you route traffic to a primary resource, such as a web server in one Region, and a secondary resource in another Region. If the primary fails, Route 53 can route traffic to the secondary resource automatically.”

(Source: Amazon Route 53 documentation, Routing Policy Types)

A, D: These options do not configure DNS failover for external users.

C: Geolocation routing is for regional distribution, not DR failover.

Amazon EFSwithMax I/O performance modeis designed for workloads that require high levels of parallelism, such as video processing across multiple EC2 instances. EFS provides shared file storage that can be mounted on both Windows and Linux EC2 instances, and the Max I/O mode ensures the best performance for handling large files and concurrent access across multiple instances.

Option A and B (FSx for Windows File Server): FSx for Windows File Server is optimized for Windows workloads and would not be ideal for Linux instances or high-throughput, parallel workloads.

Option D (EFS General Purpose mode): General Purpose mode offers lower latency but doesn ' t support the high throughput needed for large, concurrent workloads.

AWS References:

Amazon EFS Performance Modes

The requirements specify capturing unpredictable and sudden spikes in customer activity, integrating easily with other web applications, and including authorization.

Amazon API Gateway with Lambda authorizer provides a secure, scalable entry point with flexible authorization mechanisms including token validation.

Amazon Kinesis Data Firehose is a fully managed service to reliably load streaming data into destinations such as Amazon S3, which fits well for capturing streaming customer activity data.

API Gateway integrates natively with Firehose for direct ingestion.

This combination supports unpredictable traffic, smooth scaling, and simple authorization.

Option B uses Kinesis Data Streams, which requires more management than Firehose and is less optimized for direct API integration. Options A and D use Gateway Load Balancer and ECS containers plus EFS, which add complexity and are less suited for unpredictable traffic with integrated authorization.

To process each form exactly once and ensure no data is lost, using an Amazon SQS FIFO (First-In-First-Out) queue is the most appropriate solution. SQS FIFO queues guarantee that messages are processed in the exact order they are sent and ensure that each message is processed exactly once. This ensures data consistency and reliability, both of which are crucial for processing user-submitted forms without data loss.

SQS acts as a buffer between the web application server and the worker tier, ensuring that submitted forms are stored reliably and forwarded to the worker tier for processing. This also decouples the application, improving its scalability and resilience.

Option B (API Gateway): API Gateway is better suited for API management rather than acting as a message queue for form processing.

Option C (SQS Standard Queue): While SQS Standard queues offer high throughput, they do not guarantee exactly-once processing or the strict ordering needed for this use case.

Option D (Step Functions): Step Functions are useful for orchestrating workflows but add unnecessary complexity for simple message queuing and form processing.

AWS References:

Amazon SQS FIFO Queues

Decoupling Application Tiers Using Amazon SQS

For high availability, Amazon ElastiCache for Redis supports Multi-AZ with automatic failover, which provides primary and replica nodes in different Availability Zones. If the primary node fails, Redis automatically promotes a replica to primary.

From AWS Documentation:

“When you enable Multi-AZ with automatic failover, Amazon ElastiCache automatically detects failures and promotes a read replica to primary with minimal downtime.”

(Source: Amazon ElastiCache for Redis User Guide)

Why B is correct:

Multi-AZ provides automatic failover and data replication.

Ensures continuous availability and protects against node or AZ failures.

Fully managed with no manual intervention needed.

Why others are incorrect:

A: Manual promotion is not automatic.

C & D: Restoring from backup is slow and meant for disaster recovery, not failover.

Aurora I/O-Optimized: This storage configuration is designed to provide consistent high performance for Aurora databases. It automatically scales IOPS as the workload increases, without needing to provision IOPS separately.

Cost-Effectiveness: With Aurora I/O-Optimized, you only pay for the storage and I/O you use, making it a cost-effective solution for applications with varying and unpredictable I/O demands.

Implementation:

During the creation of the Aurora PostgreSQL Serverless v2 cluster, select the I/O-Optimized storage configuration.

The storage system will automatically handle scaling and performance optimization based on the application load.

Operational Efficiency: This configuration reduces the need for manual tuning and ensures optimal performance without additional administrative overhead.

Amazon CloudWatch Container Insightsis designed for monitoring containerized environments like EKS. It provides native support for collecting and visualizing metrics and logs in a centralized location through CloudWatch dashboards, offering the most operationally efficient solution.

Option A:Using the CloudWatch agent provides basic metrics but lacks the specific insights required for containerized applications.

Option B:Kinesis Data Streams and Firehose add unnecessary complexity for this use case.

Option C:CloudTrail is for auditing API activity and is not designed for application metrics and log aggregation.

AWS Documentation References:

Amazon CloudWatch Container Insights

To achieve a 60-second RTO, pre-warming the DR environment (including running EC2 instances and Route 53 health checks) is essential. Active/passive failover using Route 53 with health checks ensures fast redirection when the primary Region becomes unavailable. S3 cross-region replication ensures document availability.

Comprehensive and Detailed Explanation (from AWS Solutions Architect documentation):

Amazon DynamoDB supports two read consistency models: eventually consistent reads and strongly consistent reads. When an application must always receive the most up-to-date data, it must use strongly consistent reads. Eventually consistent reads can return stale data because they provide best-effort propagation across storage nodes.

Since the problem states that requests are “not returning the latest data,” the correct solution is to enable strongly consistent reads, which immediately reflect all successful writes. This is the explicit AWS-recommended method for ensuring clients always receive the most current version of an item.

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AWS Lambda is not suitable for long-running jobs that can take up to 20 minutes, as Lambda has a maximum execution duration of 15 minutes.

Amazon ECS with AWS Fargate allows you to run containers without managing EC2 instances, providing a scalable and highly available environment. You can scale Fargate tasks to handle large and parallel video processing jobs. Amazon Aurora is a highly available, managed relational database. S3 Intelligent-Tiering is cost-effective for storing large video files with variable access patterns.

AWS Documentation Extract:

" AWS Fargate lets you run containers without managing servers or clusters, providing a highly available and scalable compute environment. Fargate is suitable for running data processing workloads that require long-running compute tasks. "

(Source: AWS Fargate documentation, Use Cases)

A: Lambda is not suitable for long-running (over 15 min) or heavy compute jobs.

C: Amazon EMR is optimized for big data analytics, not specific video processing. FSx for Lustre and Kinesis are not best fit for this use case.

D: EKS with EC2 adds operational overhead and RDS in a single AZ is not highly available; Glacier Deep Archive is not suitable for frequently accessed video files.

Using Amazon SQS decouples the API from the database, allowing the system to handle write bursts without data loss. The queue buffers incoming requests, and AWS Lambda processes them asynchronously, writing to the RDS instance at a sustainable rate.

From AWS Documentation:

“Amazon SQS acts as a buffer between components that produce and consume data, allowing each to operate independently. You can use AWS Lambda to process messages from SQS and write them to other services such as Amazon RDS.”

(Source: Amazon SQS Developer Guide)

Why C is correct:

SQS absorbs write surges and ensures durable message retention.

Lambda scales automatically with message volume and reduces DB connections.

Prevents timeout errors by smoothing traffic spikes.

Why others are incorrect:

A: Scaling RDS vertically doesn’t address connection spikes.

B: Multi-AZ is for availability, not write throughput.

D: SNS is for fan-out message delivery, not queue-based buffering.

AWS Lambda function URLs are specifically designed to give a Lambda function a simple direct HTTP(S) endpoint. AWS documentation describes function URLs as a straightforward way to invoke a Lambda function through an HTTP request, and AWS even provides a webhook tutorial built around Lambda function URLs. That makes this the most operationally efficient option because it avoids placing an ALB in front of the function or building an unnecessary messaging layer with SNS or SQS. The requirement is simply to expose the Lambda function so a third party can call it through a webhook. Function URLs are the lightest-weight AWS-native feature for that use case and provide the fastest path from webhook sender to function execution. (AWS Documentation)

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Amazon RDS for MySQL supports read replicas that offload read-intensive workloads such as reporting, leaving the primary instance free for write operations.

“You can use Amazon RDS read replicas to elastically scale out beyond the capacity constraints of a single DB instance for read-heavy database workloads.”

— Working with Read Replicas

This is the recommended approach for minimizing performance impact on the primary DB instance.

To meet the requirement of controlling key rotation with minimal operational overhead, creating acustomer managed key(CMK) in AWS KMS is the optimal solution. With CMKs, you can define custom key rotation policies, ensuring that you retain control over the key lifecycle, including enabling automatic key rotation every year.

Key AWS features:

Custom Key Management: A customer managed key allows you to control the key policies, lifecycle, and enable key rotation for compliance.

Least Operational Overhead: Using a customer managed key simplifies encryption management while offering more flexibility than AWS managed or owned keys.

AWS Documentation: The AWS Well-Architected Framework recommends customer managed keys for environments where key control and flexibility are required​.