There is always a first cloud application. In every IT organization, some brave soul will either move an existing application to the cloud or create a new one there. In so doing, this person will gain an understanding— beyond all the hype—of what developing, testing, deploying, and maintaining a cloud application is all about.

When Microsoft IT began its cloud migration journey in 2009, it followed a similar process. First, it cataloged its operating system instances and application workloads. This assessment included both quantitative data that was mostly retrievable by tools as well as qualitative data that was partially retrievable by tools and also required examination by both the operations team and the business liaison team. This latter category of metadata included relationships, dependencies, and integration points.

Many IT organizations rely on the Information Technology Infrastructure Library (ITIL) framework for service management and operations. Over the years the ITIL has proven a useful set of practices for IT Service Management (ITSM) and for aligning IT investments and operations with business goals. Among its benefits, advocates and practitioners of ITIL point to increased reliability, uptime, and predictable costs.

Flexibility and a variety of options also characterize analytics in the cloud. There are many new possibilities with analytical analysis, but the most exciting possibility is predictive analytics; that is, the ability to predict future performance from historical data. The possibilities are almost limitless, but consider the use of Big Data for predictive analysis

Every major change in the way you conduct business entails some amount of risk; few aspects of the cloud have generated more discussion and controversy than those regarding its security and risk. In this time of breaches, nation-state hacking, and growing and profound concern with individual privacy on the Internet, cybersecurity has become a board-level concern, and rightly so.

The next step is to think about the data your applications can store in the cloud and how they might influence security and risk. Many companies classify their data according to its sensitivity: a marketing document has a very different security requirement than, say, a draft of a 10-K filing prior to earnings release.

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