Amazon EFS is a fully managed, scalable file storage service that can be accessed concurrentlyby thousands of EC2 instances. It supports General Purpose performance mode for latency-sensitive use cases and provides high availability and durability across multiple Availability Zones with minimal changes to application code.

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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Amazon S3 Storage Lens:

S3 Storage Lens provides organization-wide visibility into object storage usage and activity trends.

It can generate metrics and insights about your S3 buckets, including versioning status.

Configuration:

Enable S3 Storage Lens at the organization level.

Configure the dashboard to include the versioning status metric.

Identify Non-Versioned Buckets:

Use the S3 Storage Lens dashboard to filter and identify buckets that do not have versioning enabled.

Storage Lens provides detailed insights and reports which can be used to enforce compliance and manage storage effectively.

Operational Efficiency: Using S3 Storage Lens provides a centralized, easy-to-use interface for monitoring bucket configurations across multiple Regions and accounts, reducing the need for custom scripts or manual checks.

Amazon Aurora MySQL supports the SELECT INTO OUTFILE S3 SQL syntax to export query results directly to Amazon S3. This is an efficient and low-overhead method for archiving data.

Once data is in S3, Lifecycle rules can be configured to automatically transition older data to lower-cost storage classes (such as S3 Glacier) or delete it after a defined period, providing a cost-optimized and automated archive solution.

The Glue-based options involve more services and operational overhead. SCT is intended for database migrations, not for periodic data archival.

For maximum resiliency and fault tolerance in a mission-critical scenario, AWS recommends redundant Direct Connect connections from multiple data centers to multiple AWS Direct Connect locations.

This protects against:

Data center failure

Device failure

Location outages

“For workloads that require high availability, we recommend that you use multiple Direct Connect connections at multiple Direct Connect locations.”

— AWS Direct Connect Resiliency Recommendations

Option C follows AWS maximum resiliency model.

Amazon Elastic File System (EFS) is a managed file storage service that can be mounted across multiple EC2 instances. It provides a scalable and high-performing solution to share data among instances within a VPC.

High Performance: EFS provides scalable performance for workloads that require high throughput and IOPS. It is particularly well-suited for applications that need to share data across multiple instances.

Ease of Use: EFS can be easily mounted on multiple instances across different Availability Zones, providing a shared file system accessible to all the instances within the VPC.

Security: EFS can be configured to ensure that data remains within the VPC, and it supports encryption at rest and in transit.

Why Not Other Options?:

Option A (Amazon S3 bucket with APIs): While S3 is excellent for object storage, it is not a file system and does not provide the low-latency access required for shared data between instances.

Option B (S3 bucket as a mounted volume): S3 is not designed to be mounted as a file system, and this approach would introduce unnecessary complexity and latency.

Option C (EBS volume shared across instances): EBS volumes cannot be attached to multiple instances simultaneously. It is not designed to be shared across instances like EFS.

AWS References:

Amazon EFS- Overview of Amazon EFS and its features.

Best Practices for Amazon EFS- Recommendations for using EFS with multiple instances.

AWS Transfer Family (SFTP) allows clients to use standard SFTP clients and SSH keys without changes. By enabling service-managed users, clients can continue uploading files with their existing tools.

The service delivers the files directly into S3, reducing latency between upload and processing. This removes the need for EC2, custom scripts, and periodic transfers. It fully meets the requirement for a managed solution with minimal disruption to client processes.

The best answer is to enableS3 Block Public Access at the account leveland back it with theAWS Config s3-account-level-public-access-blocks ruleplus automated remediation. AWS states that S3 Block Public Access can be applied at the account level and overrides public bucket policies and ACLs so you can centrally prevent public access across the account. AWS Config provides a managed rule specifically for checking those account-level settings, and AWS Systems Manager includes an automation runbook to remediate drift. This is stronger and more scalable than relying on detection tools alone, because it both prevents exposure and automatically restores compliance if settings change. (AWS Documentation)

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State Machine Testing with Logs:

Changing the log level to ALL enables capturing detailed request and response data. This helps verify HTTP headers, body, and responses.

Incorrect Options Analysis:

Option A and B: The TestState API is not a valid option for Step Functions.

Option C: A data flow simulator does not exist for AWS Step Functions.

Instances in a private subnet cannot directly reach the internet because they do not have public IP addresses and the private subnet route table typically does not send 0.0.0.0/0 traffic to an internet gateway. However, these instances still need outbound-only internet access to download patches and updates while remaining inaccessible from the internet. The standard AWS design to achieve this is a NAT gateway deployed in a public subnet.

Option C is required because a NAT gateway must reside in a public subnet that has a route to the internet gateway. This allows the NAT gateway to forward outbound traffic from private instances to the internet and return responses, without allowing inbound connections initiated from the internet to those instances.

Option A is required because a NAT gateway uses an Elastic IP address to represent its public-facing identity on the internet. Without an Elastic IP, the NAT gateway cannot communicate with internet endpoints. The Elastic IP is associated with the NAT gateway, not with the internet gateway.

Option B is required because the private subnet needs a route for 0.0.0.0/0 (default route) that targets the NAT gateway. This ensures that outbound internet-bound traffic from the private instances is sent to the NAT gateway rather than being dropped.

Option D is incorrect because a NAT gateway in a private subnet would not have a working route to the internet gateway and would not provide internet egress. Option E is incorrect because the public subnet’s default route should point to the internet gateway, not to the NAT gateway. Option F is incorrect because you do not associate Elastic IPs with an internet gateway.

Therefore, A, B, and C correctly implement private subnet outbound internet access while keeping the instances unreachable from the internet.

Setting the RDS backup retention policy to 30 days forautomated backupsthrough AWS Backup allows the company to retain backups cost-effectively. Manual backups, however, are notautomatically managed by RDS ' s retention policy, so they need to be manually deleted if they are older than 30 days to avoid unnecessary storage costs.

Key AWS features:

Automated Backups: Can be configured with a retention policy of up to 35 days, ensuring that older automated backups are deleted automatically.

Manual Backups: These are not subject to the automated retention policy and must be manually managed to avoid extra costs.

AWS Documentation: AWS recommends using backup retention policies for automated backups while manually managing manual backups​.

This is a classic use case for Amazon Kinesis Data Streams + OpenSearch + QuickSight:

Kinesis Data Streams: For real-time ingestion and processing

OpenSearch Service: For fast full-text search, indexing, and analysis

QuickSight: For rich dashboard visualizations

This stack is fully managed, scalable, and native to AWS, minimizing operational overhead.

For infrequent or ad hoc querying of log data, Amazon S3 + Amazon Athena provides the most cost-effective, serverless, and scalable analytics solution.

From AWS Documentation:

“Amazon Athena is an interactive query service that makes it easy to analyze data in Amazon S3 using standard SQL. Athena is serverless, so there is no infrastructure to manage, and you pay only for the queries that you run.”

(Source: Amazon Athena User Guide)

Why A is correct:

Amazon S3 offers durable, scalable, and cost-efficient storage.

Athena allows SQL-based querying on structured or semi-structured data like logs.

No need to provision or manage infrastructure.

Ideal for occasional querying at low cost.

Why the others are not optimal:

Option B: OpenSearch adds cost and is best for frequent, low-latency log querying.

Option C: RDS is not optimized for large-scale write-heavy log ingestion and costs more.

Option D: CloudWatch Logs is suitable for real-time monitoring, not for long-term storage and analytics of large log volumes.

DynamoDB Accelerator (DAX) is a fully managed, in-memory cache for DynamoDB that delivers up to a 10x performance improvement—even at millions of requests per second. DAX requires minimal changes to existing applications and offloads the read workload from DynamoDB during report generation.

Reference Extract:

" DAX provides in-memory acceleration for DynamoDB tables, reducing response times from milliseconds to microseconds with minimal application changes. "

Source: AWS Certified Solutions Architect – Official Study Guide, DynamoDB and Performance section.

Amazon DynamoDB is a serverless, NoSQL database that is fully managed, highly available, and scales automatically. It is ideal for data without a fixed schema and for use cases where fields can vary by user. DynamoDB Streams enables the capture of changes to table items in real time, which is ideal for triggering additional processing or workflows on data modifications.

Reference Extract from AWS Documentation / Study Guide:

" DynamoDB provides a scalable, highly available NoSQL database service for applications requiring flexible schema. DynamoDB Streams captures table activity for processing changes in real time. "

Source: AWS Certified Solutions Architect – Official Study Guide, DynamoDB and Serverless section.

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

Why Option D is Correct:

IAM Roles with Instance Profiles: Allow applications to access AWS services securely without hardcoding long-term access keys.

Short-Term Credentials: IAM roles issue short-term credentials dynamically managed by AWS.

Why Other Options Are Not Ideal:

Option A and B: Embedding or retrieving long-term access keys introduces security risks and operational overhead.

Option C: Combining IAM roles with Parameter Store adds unnecessary complexity.

AWS References:

IAM Roles and Instance Profiles:AWS Documentation - IAM Roles

Why Option C is Correct:

NAT Gateway: Allows private subnets to access the internet for outbound requests while preventing inbound connections.

High Availability: Deploying NAT gateways in both AZs ensures fault tolerance.

Shared Route Table: Simplifies routing configuration for private subnets.

Why Other Options Are Not Ideal:

Option A: Creating separate route tables for each subnet adds unnecessary complexity.

Option B: Internet gateways allow inbound access, violating the requirement to block public IPv4 access.

Option D: Egress-only internet gateways are designed for IPv6, not IPv4.

AWS References:

Amazon VPC NAT Gateway:AWS Documentation - NAT Gateway

Durable storage of incoming orders with buffering and ability to handle surges is exactly what Amazon SQS is designed for. SQS provides highly durable, scalable queues that decouple producers from consumers.

Centrally tracking workflow steps is a core use case of AWS Step Functions, which gives a visual workflow and state machine, tracks the state of each order, and can orchestrate calls to multiple microservices (in this case, Lambda functions).

Combining SQS + Step Functions + Lambda gives:

Durable queueing for orders (SQS).

Loose coupling and surge handling (SQS decoupling + auto-scaling Lambda).

Central orchestration and tracking of order-processing steps (Step Functions).

Why the other options are not correct:

A: SNS is a pub/sub service, not a durable work queue, and is not designed for “store-and-retry until processed” workloads in the same way SQS is.

C: SQS + EventBridge provides decoupling but no central, stateful workflow tracking; EventBridge is event routing, not workflow orchestration.

D: SNS + EventBridge still lacks durable order storage and explicit centralized workflow/state tracking.

Detailed Explanation:

A. EventBridge Rule:Detects modifications to CloudFront distributions in real time and triggers the Lambda function for further action.

B. ALB + Config:Focuses on ALB security violations, not relevant for CloudFront logging changes.

C. Lambda + SNS:Provides real-time notifications about changes in logging configuration.

D. GuardDuty:Focuses on threat detection, not logging configuration changes.

E. API Gateway + WAF:Unrelated to CloudFront logging changes.