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Key Requirements:

High availability and automatic recovery.

Separate transactional and analytical queries with minimal performance impact.

Allow up to a 4-hour lag for analytical queries.

Analysis of Options:

Option A:

Multi-AZ deployments provide high availability but do not include read replicas for separating transactional and analytical queries.

Analytical queries on the secondary DB instance would impact the transactional workload.

Incorrect Approach:Does not meet the requirement of query separation.

Option B:

Multi-AZ DB clusters provide high availability and include a reader endpoint. However, these are better suited for Aurora and not RDS for MySQL.

Incorrect Approach:Not applicable to standard RDS for MySQL.

Option C:

Multiple read replicas allow separation of transactional and analytical workloads.

Queries can be pointed to a replica in a different AZ, ensuring no impact on transactional queries.

Correct Approach:Meets all requirements with high availability and query separation.

Option D:

Creating nightly snapshots and read-only databases adds significant operational overhead and does not support the 4-hour lag requirement.

Incorrect Approach:Not practical for dynamic query separation.

AWS Solution Architect References:

Amazon RDS Read Replicas

Multi-AZ Deployments

This solution leverages:

Amazon Redshift Spectrum to query S3 data directly from Redshift.

Amazon Athena for ad-hoc analysis of S3 data.

Amazon QuickSight for unified visualization from multiple data sources.

“Redshift Spectrum enables you to run queries against exabytes of data in Amazon S3 without having to load or transform the data.”

“QuickSight supports both Amazon Redshift and Amazon Athena as data sources.”

— Redshift Spectrum

— Amazon QuickSight Supported Data Sources

This architecture allows scalable querying and visualization with minimum ETL overhead, ideal for BI dashboards.

Incorrect Options:

A: The query editor is not a BI tool.

B, D: Grafana is better for time-series data, not structured analytics or BI reports.

The company needs a cloud-based storage solution for frequently accessed data with low latency, while retaining their current on-premises infrastructure for some data storage. AWS Storage Gateway ' sVolume Gateway with cached volumesis the most appropriate solution for this scenario.

AWS Storage Gateway - Volume Gateway (Cached Volumes):

Volume Gateway with cached volumesallows you to store frequently accessed data in the AWS Cloud while keeping the most recently accessed data cached locally on-premises. This ensures low-latency access to active data while providing scalability for the rest of the data in the cloud.

The cached volume option stores the primary data in Amazon S3 but caches frequently accessed data locally, ensuring fast access. This configuration is well-suited for applications that require fast access to frequently used data but can tolerate cloud-based storage for the rest.

Since the company is facing limited on-premises storage, cached volumes provide an ideal solution, as they reduce the need for additional on-premises storage infrastructure.

Why Not the Other Options?:

Option A (S3 File Gateway): S3 File Gateway provides a file-based interface (SMB/NFS) for storing data directly in S3. While it is great for file storage, the company’s need for block-level storage with iSCSI targets makes Volume Gateway a better fit.

Option C (Volume Gateway - Stored Volumes): Stored volumes keep all the data on-premises and asynchronously back up to AWS. This would not address the company ' s storage limitations since they would still need substantial on-premises storage.

Option D (Tape Gateway): Tape Gateway is designed for archiving and backup, not for frequently accessed low-latency data.

AWS References:

AWS Storage Gateway - Volume Gateway

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.