For applications requiring high network throughput and low latency between EC2 instances, AWS recommends using a Cluster Placement Group:
Cluster Placement Group: Packs instances close together inside an Availability Zone, enabling workloads to achieve the low-latency network performance necessary for tightly-coupled node-to-node communication.
Enhanced Networking: Selecting instance types that support enhanced networking provides higher bandwidth, higher packet-per-second (PPS) performance, and consistently lower inter-instance latencies.
By combining a Cluster Placement Group with enhanced networking-enabled instance types, the company can meet the stringent performance requirements of its real-time industrial application.

Amixed Auto Scaling groupwith both On-Demand and Spot Instances is the best answer because AWS documents that mixed instances groups let you launch and automatically scale a fleet of On-Demand and Spot Instances in a single Auto Scaling group to optimize cost while maintaining scale and performance. Since the workload can tolerate occasional disruptions, Spot is appropriate, but keeping some On-Demand capacity adds stability. This is a more practical architecture than moving the whole workload to Spot alone. Continuing with only On-Demand or buying Reserved Instances would not optimize cost as well for variable usage.

Amazon EFS is a regional, elastic file system that "scales to petabytes" and can be accessed from "thousands of compute instances" concurrently. You can mount EFS across VPCs and across AWS accounts by providing network connectivity (e.g., VPC peering) to the EFS mount targets and allowing NFS (TCP 2049) in the mount target security group, optionally using EFS access points and a file system policy for cross-account access control. VPC peering has no hourly charge and minimal operational overhead, and EFS automatically scales as files are added-meeting the scalability and cost goals.
Option A duplicates data, incurs DataSync and extra storage costs, and adds sync lag.
Option C adds an extra Lambda hop and complexity without exposing a shared filesystem to the primary function.
Option D is impractical: Lambda layers are immutable artifacts with tight size limits (up to 50 MB compressed
/250 MB uncompressed) and are not suited for dynamic, growing file sets.
References: Amazon EFS User Guide - "Accessing EFS across VPCs and accounts," "Mount targets and security groups," "EFS access points," and "EFS automatically scales to petabytes."

AWS DataSync provides a fully managed, secure, and high-performance service for transferring large amounts of data between on-premises storage and Amazon S3. It uses TLS encryption in transit and automates data validation, scheduling, and monitoring.
From AWS Documentation:
"AWS DataSync securely and efficiently transfers large amounts of data online between on-premises storage and AWS services. All data is encrypted in transit using TLS." (Source: AWS DataSync User Guide - How DataSync Works) Why B is correct:
* Encrypts all data in transit automatically.
* Optimized for high-throughput WAN environments (100 Mbps to multi-Gbps).
* Fully managed, with no need to provision additional infrastructure.
* Integrates natively with S3 and supports incremental syncs.
Why others are incorrect:
* A: DMS is designed for database migration, not unstructured data.
* C: Snowball is for offline migrations, not needed given available connectivity.
* D: Direct Connect is costly for temporary data transfers and unnecessary here.
References:
AWS DataSync User Guide - "Security in AWS DataSync"
AWS Well-Architected Framework - Cost Optimization and Operational Excellence Pillars

AWS DataSync is the best fit because it is a managed service designed for repeated data movement between supported storage systems, includingAmazon S3andAmazon EFS. AWS documents that DataSync tasks can be configured to transferonly data that has changedby using theCHANGEDtransfer mode , which matches the overwrite-if-changed requirement. That removes the need to build custom synchronization code with Lambda or EC2. DataSync also has native support for S3 locations and EFS locations, so it directly covers both destinations in the question. Option A is therefore the lowest-overhead and most maintainable solution.