As veteran of the IT industry, I fall inline with the 10,000 hour rule in reference to Linux/Unix Systems Administration. Needless to say, as a wrangler of *nix based operating systems, most people would consider me an expert; although, I rarely feel that way. However, as of recent I’ve been doing a lot of work on Big Data platforms, including Hadoop, Elastic Search, MongoDB, and using tools such as Storm and Impala. While the install of these platforms is trivial, I can unequivocally say that the tuning is not. This brings me to the point, The Case for Managed Services. I’m fortunate enough to be working with some very sharp guys in the Big Data industry right now, the folks over at InfoChimps. They have developed a Big Data managed service platform that is, in my opinion, unrivaled in the industry. This is the type of platform that it would take months, possibly years, and a team of systems engineers and developers to perfect; and that is the argument I make.

Welcome to the third and final part of my this blog series about choosing an SPI provider. During the previous two posts, one and two, I’ve discussed a number of issues and attributes you should consider before selecting an SPI provider. In this last piece, I’m going to give some recommendations based on my experience, references from people I trust, and what I see in the industry. I’m going to start from the bottom up, so let’s talk IaaS.

Welcome to part two of a three part blog series: How to choose an SPI (SaaS, PaaS, IaaS) service provider? If you haven’t read the first posting, you can find it here. We are going to pick up where we left off in addressing both the ROI and culture of a prospective SPI provider.