Question 3
An enterprise software designer wants to leverage the best of Google cloud to minimize the number of administrative overheads associated with her payment processing pipeline while also getting on-demand scalability without sacrificing flexibility. What option should she choose to best serve these needs?
Build the payment processer using VMs – one for Python for the logic, one forinvoking the external payment engine, and one for storing the results
Build the payment processor using Python running on Google Cloud Functionswhere the results are stored on GCS
Build the payment processor using MapReduce with input data and results arestored on HDFS, and deploy both on Dataproc
Build the payment processor using Dataflow on top of data stored on GCS