Your company produces customer commissioned one-of-a-kind skiing helmets combining high fashion with custom technical enhancements. Customers can show off their individuality on the ski slopes and have access to head-up-displays. GPS rear-view cams and any other technical innovation they wish to embed in the helmet. The current manufacturing process is data-rich and complex, including assessments to ensure that the custom electronics and materials used to assemble the helmets are the highest standards. Assessments are a mixture of human and automated assessments. You need to add a new set of assessments to model the electronics` failure modes using GPUs with CUDA across a cluster of servers with low latency networking. What architecture would allow you to automate the existing process using a hybrid approach and ensure that the architecture can support the evolution of processes over time?

Answer options:

A.Use AWS Data Pipeline to manage the movement of data & meta-data and assessments. Use an Auto Scaling group of G2 instances in a placement group.
B.Use AWS Step Functions to manage assessments, movement of data, & meta-data. Use an Auto Scaling group of G2 instances in a placement group.
C.Use Amazon Simple Workflow (SWF) to manage assessments movement of data & meta-data. Use an Auto Scaling group of C3 instances with SR-IOV (Single Root I/O Virtualization).
D.Use AWS data Pipeline to manage the movement of data & meta-data and assessments. Use an Auto Scaling group of C3 with SR-IOV (Single Root I/O virtualization).

Answer - B
The main point to consider in this question is that the assessments include human interaction as well. In most such cases, always look for AWS Step Functions in the options.
Option A is incorrect because this will be useful during the batch jobs, which deal with the automated assessments. For the human assessment, this will not be a useful option.
Option B is CORRECT because (a)it enables assessment via human interaction, (b) uses Auto Scaled G2 instances that are efficient in automated assessments due to their GPU and low latency networking.
Please refer the below link for AWS Step Functions
https://docs.aws.amazon.com/step-functions/latest/dg/welcome.html
Option C is incorrect because although SWF can be used for human tasks, C3 instances and SR-IOV will not provide the required GPU.
Option D is incorrect because (a) this will be useful during the batch jobs, which deal with the automated assessments. This will not be a useful option for the human assessment, and (b) C3 instances and SR-IOV will not provide the required GPU.