I have experience working as an equity research associate.
Question 1- What is the best storage, or combination of storage systems, to use for AI machine learning? I've been asking around and have been hearing that using Pure Storage and NetApp as a hybrid provides the best combination from a performance, scalability, and high availability standpoint with Pure Storage providing the first while NetApp provides the other two. Do you agree? And if not, what do you recommend?
Question 2- I'm not a Pure Storage user but have been hearing that performance becomes subpar after two years of usage and storage increasing to 50%+ of capacity. From your experience, can you attest to this claim?
Thanks! I appreciate the help.