AWS advises using serverless event-driven processing to minimize operational burden and scale automatically with demand. Amazon SQS can be directly configured as an event source for AWS Lambda.
With this setup, Lambda polls the queue, invokes the function, and processes messages without requiring the customer to manage infrastructure. Scaling is automatic, based on the volume of messages in the queue.
Option A (increasing instance size) still leaves scaling and management challenges. Option B reduces cost when idle but does not address scaling. Option D requires manual triggering and does not meet continuous processing requirements. Migrating the script to Lambda (C) fully eliminates the need for instance management, providing scalability, reliability, and reduced operational overhead.
References:* Amazon SQS Developer Guide - Using AWS Lambda with Amazon SQS* AWS Well- Architected Framework - Operational Excellence Pillar

Amazon Data Lifecycle Manager (DLM) automates the creation, retention, and deletion of EBSsnapshots.
This allows organizations to define policies that ensure snapshots are only kept as long as needed, reducing costs automatically and minimizing manual effort. AWS recommends using DLM for optimizing storage and managing backup lifecycle with minimal overhead.
Reference: AWS Documentation - Amazon Data Lifecycle Manager

Using S3 gateway endpoints allows private and cost-free access to S3 without routing traffic through a NAT gateway. NAT gateway traffic incurs charges, especially when used across multiple Availability Zones.
By using an S3 gateway endpoint, EC2 instances in private subnets can access S3 directly without needing internet access, reducing both data transfer and NAT gateway costs.
Interface endpoints are more expensive and typically used for services like API Gateway or Systems Manager.

* 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.

As the number of VPCs grows, managing individual VPC connections becomes complex and unscalable.
AWS Transit Gateway is specifically designed to act as a central hub that connects multiple VPCs and on- premises networks through Direct Connect.
Option B simplifies network architecture by allowing hundreds or thousands of VPCs to connect through a single gateway, reducing routing complexity and operational overhead. Transit Gateway supports scalable routing, centralized inspection, and simplified expansion.
The other options do not address network connectivity or scaling challenges. Therefore, B is the correct solution.