Free Amazon Web Services SAA-C03 Practice Exam with Questions & Answers

Amazon MSK is a fully managed, highly available Apache Kafka service for streaming data with low latency. Kafka Connect and stream processors enable ingest from heterogeneous sources and perform in-stream transformation before delivery to consumers (e.g., the dashboard service). This satisfies real-time updates from diverse schemas and formats. Kinesis alternatives could work, but among the given choices, MSK is the only streaming option designed for sub-second, continuous pipelines. Kinesis Data Firehose (B) buffers and batches data to S3 and is optimized for delivery to storage, not low-latency dashboards. AWS DMS schema conversion (C) focuses on database migration, not ongoing real-time, multi-format streaming for dashboards. AWS DataSync (D) is for file/object transfer, not database change streams. Hence, MSK best meets minimal-latency, transform-in-flight needs with managed operations.

To improve the performance of the primary RDS PostgreSQL database during business hours and reduce the load, the best solution is to create aread replicain the same region (us-east-1). This will offload the read-heavy operations (like generating reports) to the replica, reducing the burden on the primary instance, which improves overall performance. Additionally, read replicas provide near real-time replication, making them ideal for real-time reporting use cases.

Option A (cross-Region read replica): This adds unnecessary latency for real-time reporting and increased costs due to cross-region data transfer.

Option B (Multi-AZ): Multi-AZ deployments are for high availability and disaster recovery but won’t offload the read traffic, as the standby database cannot serve read requests.

Option C (AWS DMS replication): This adds complexity and is not as cost-effective as using an RDS read replica for the same region.

AWS References:

Amazon RDS Read Replicas

Amazon RDS Performance Best Practices

Amazon Athena provides a cost-effective, serverless way to query data without affecting the performance of DynamoDB. By using the Athena DynamoDB connector, the company can perform the necessary SQL queries without consuming read capacity on the DynamoDB table, which is essential for minimizing impact on provisioned throughput.

Key benefits:

Minimal Impact on Provisioned Capacity: Athena queries do not directly impact DynamoDB’s read capacity, making it ideal for running analytics without affecting the customer-facing workloads.

Cost-Effective: Athena is a serverless solution, meaning you pay only for the queries you run, making it highly cost-effective compared to running a dedicated cluster like Amazon EMR or Redshift.

AWS Documentation: The use of Athena to query DynamoDB through its connector aligns with AWS's best practices for performance efficiency and cost optimization​​.

Amazon EFS provides a fully managed, highly available, and shared file system that can be mounted by instances across multiple Availability Zones. This ensures consistency of files between EC2 instances and avoids replication issues. EBS volumes, in contrast, are AZ-scoped and not designed for multi-instance sharing. Options A and B rely on custom replication or manual file handling, which increases operational overhead and risks inconsistencies. Option D does not solve the shared access and consistency requirement. By migrating storage to EFS, both EC2 instances will read and write to the same storage system, ensuring that users always access the latest files without 404 errors.

Comprehensive and Detailed Step-by-Step Explanation:

The requirement is toprevent data deletion by any user, including administrators, for 7 years while allowing automatic deletion afterward.

S3 Object Lock in Compliance Mode (Correct Choice - C)

Compliance mode ensures that even the root user cannot delete or modify the objects during the retention period.

After 7 years, the S3 Lifecycle policy automatically deletes the objects.

This meets bothimmutability and automatic deletionrequirements.

Governance Mode (Option B - Incorrect)

Governance mode prevents deletion,but administrators can override it.

The requirement explicitly states thateven administrators must not be able to delete the data.

S3 Bucket Policy (Option A - Incorrect)

An S3 bucket policy candeny deletes, but policies can be modified at any time by administrators.

It does not enforce strict retention like Object Lock.

S3 Batch Operations Job (Option D - Incorrect)

A legal hold does not have an automatic expiration.

Legal holds must be manually removed, which is not efficient.

Why Option C is Correct:

S3 Object Lock in Compliance Mode prevents deletion by all users, including administrators.

The S3 Lifecycle policy deletes the data automatically after 7 years, reducing operational overhead.

Amazon S3 Intelligent-Tiering is the most cost-effective solution for this scenario, providing both high availability and durability while adjusting automatically to changing access patterns. It moves data across two access tiers: one optimized for frequent access and another for infrequent access, based on usage patterns. This tiering ensures that the company avoids paying for unused storage while also keeping frequently accessed data in a more accessible tier.

Key AWS references and benefits ofS3 Intelligent-Tiering:

High Durability and Availability: Amazon S3 offers 99.999999999% durability and 99.9% availability for objects stored, ensuring data is always protected.

Automatic Tiering: Data is automatically moved between tiers based on access patterns, making it ideal for workloads with unpredictable or variable access patterns.

No Retrieval Fees: Unlike S3 One Zone-IA or Glacier, there are no retrieval fees, making this more cost-effective in scenarios where access patterns vary over time.

AWS Documentation: According to the AWS Well-Architected Framework under theCost Optimization Pillar, S3 Intelligent-Tiering is recommended for storage when access patterns change over time, as it minimizes costs while maintaining availability​.

AWS Secrets Manager is designed specifically to securely store and manage sensitive information such as database credentials. It integrates seamlessly with AWS services like Lambda and RDS, and it provides automatic credential rotation with minimal operational overhead.

AWS Secrets Manager: By storing the database credentials in Secrets Manager, you ensure that the credentials are securely stored, encrypted, and managed. Secrets Manager provides a built-in mechanism to automatically rotate credentials at regular intervals (e.g., every 30 days), which helps in maintaining security best practices without requiring additional manual intervention.

Lambda Integration: The Lambda function can be easily configured to retrieve the credentials from Secrets Manager using the AWS SDK, ensuring that the credentials are accessed securely at runtime.

Why Not Other Options?:

Option A (Parameter Store with Rotation): While Parameter Store can store parameters securely, Secrets Manager is more tailored for secrets management and automatic rotation, offering more features and less operational overhead.

Option C (Encrypted Lambda environment variable): Storing credentials directly in Lambda environment variables, even when encrypted, requires custom code to manage rotation, which increases operational complexity.

Option D (KMS with automatic rotation): KMS is for managing encryption keys, not for storing and rotating secrets like database credentials. This option would require more custom implementation to manage credentials securely.

AWS References:

AWS Secrets Manager- Detailed documentation on how to store, manage, and rotate secrets using AWS Secrets Manager.

Using Secrets Manager with AWS Lambda- Guidance on integrating Secrets Manager with Lambda for secure credential management.

AWS Step Functions provides a low-code, fully managed workflow service with a visual interface to orchestrate AWS Glue jobs in sequence. Step Functions integrates natively with AWS Glue and can be triggered by Amazon EventBridge based on events or schedules.

AWS Documentation Extract:

“AWS Step Functions makes it easy to coordinate multiple AWS services into serverless workflows so you can build and update apps quickly. Step Functions provides visual workflows and integrates with AWS Glue for ETL orchestration.”

(Source: AWS Step Functions documentation)

A: Manual scripting and dashboards do not provide a low-code or integrated visual workflow.

C: QuickSight is for BI, not workflow visualization.

D: ECS adds unnecessary complexity.

Amazon RDS read replicas provide a way to offload read traffic from the primary database, allowing read-intensive applications to query the replica without impacting the performance of the production (write) database. This is especially effective for workloads that involve frequently changing data but do not benefit from caching, since queries are rarely repeated.

Reference Extract from AWS Documentation / Study Guide:

"Read replicas allow you to elastically scale out beyond the capacity constraints of a single DB instance for read-heavy database workloads."

Source: AWS Certified Solutions Architect – Official Study Guide, RDS Read Replica section.

AWSDirect Connectis the best solution for establishing a consistent, low-latency connection from an on-premises data center to AWS without using the public internet. Direct Connect offers dedicated, high-throughput, and low-latency network connections, which are ideal for performance-sensitive applications like a trading platform that processes high volumes of market data and stock trades.

Direct Connect provides a private connection to your AWS VPC, ensuring that data doesn't traverse the public internet, which enhances both security and performance consistency.

AWS References:

AWS Direct Connectprovides a dedicated network connection to AWS services with consistent, low-latency performance.

Best Practices for High Performance on AWSfor performance-sensitive workloads like trading platforms.

Why the other options are incorrect:

A. AWS Client VPN: While this offers secure connectivity, it's over the public internet and is not designed for the low-latency, high-performance needs of a trading platform.

C. AWS PrivateLink: PrivateLink is used for connecting VPCs and services within AWS, but it is not designed for connecting on-premises data centers to AWS.

D. AWS Site-to-Site VPN: Although this provides secure connectivity, it uses the public internet, which can introduce latency and doesn't meet the low-latency requirements of the use case.

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.

AWS Secrets Manager is the recommended service for managing and automatically rotating database credentials. It integrates natively with Amazon RDS (including PostgreSQL), supports built-in rotation functionality, and requires minimal setup.

Secrets Manager also supports versioning and auditing, which enhances operational excellence and security. Parameter Store does not natively support credential rotation. AWS KMS manages key encryption—not application secrets—so it is not applicable here.

Use SQS FIFO to durably persist orders, guarantee order processing semantics, and decouple producers/consumers. FIFO queues provide “exactly-once processing” with message deduplication and “preserve message order.” Visibility timeouts and retries ensure messages are “processed eventually” without being lost; failed messages go to a DLQ for later reprocessing. This pattern aligns with Well-Architected reliability guidance to “queue work to protect against overload and failures” and to ensure “durable, idempotent processing” with retry and backoff. ALB/RDS Proxy/read replicas (A, B) improve availability/connection management but do not guarantee durable handoff or exactly-once processing. SNS (D) is pub/sub and does not provide FIFO semantics in this option, nor a DLQ per subscription for exactly-once. Therefore, frontends write orders to an SQS FIFO queue; backend workers in an Auto Scaling group consume, process idempotently, and use a DLQ for poison messages to meet “no lost orders,” “eventual processing,” and “exactly-once” requirements.

Comprehensive and Detailed Explanation:

To authenticate users using an on-premises Active Directory Federation Service (AD FS), AWS provides the AWS Directory Service AD Connector. AD Connector is a proxy that connects AWS applications to your on-premises Microsoft Active Directory without requiring complex directory synchronization or the need to set up a separate directory in the cloud.

By integrating AD Connector with the Application Load Balancer (ALB), you can authenticate and authorize users using your existing on-premises credentials. This setup allows the ALB to leverage the authentication capabilities of your on-premises AD FS, providing a seamless and secure user experience.