Cloud computing: two things to move to it today

Cloud computing is becoming a mainstream technology with the backing of almost every heavyweight in the industry. As details emerge and platforms and technologies are refined, many software vendors are evaluating the move to the cloud. Being a fairly new and emerging technology, there is a need to assess the value of cloud migration at minimal cost.

In this article, we’ll look at two pieces of software that a provider can move to the cloud without negative impact, and actually benefit from the inherent strengths of cloud platforms. These are significant, progressive steps toward cloud that have a good chance of being in parent cloud when the air clears around them.

Identify the pieces of your complete product and move them to a cloud-enabled data center

Each product has bells and whistles that create a complete experience for users. In product management jargon, this is called a Full Product or an Augmented Product, rather than just the software. The following are some examples of complete products:

1. All the rich content around a travel planning website, such as city guides, attractions, and images.
2. User Generated Content (UGC): The traditional definition of Full Product included only the things that product managers and companies included to complement the user experience of their product. For example, the iTunes Store completed the iPod user experience. In the realm of Web 2.0, user-generated content is one of those elements. Moving the pieces of the augmented product to the cloud is a smart idea for two reasons. First, it’s generally safe to say that augmented parts are an essential, but not core, part of your product that you’d like to manage easily and efficiently without losing your focus on the core. Second, UGC and other content are a big part of the user experience these days, and are inherently very elastic and growing unpredictable. Cloud computing will allow you to manage and scale them very effectively.

Move data with complex structural requirements to the cloud

The traditional way of looking at data has been in a relational model or perhaps a hierarchical model. Any other complex views of data were modeled on these forms, and the resulting performance impact was handled through denormalization and other techniques. However, with the data explosion we’ve seen in recent years, these models seem to be coming apart at the seams.

So the old taxonomy of entity, relationships, joins, etc. it is rapidly being replaced by priorities such as replication, redundancy, partitioning, and folksonomy. As you can imagine, these requirements actually require a large amount of computing power and scalability. Enter cloud computing. All cloud computing platforms have multiple data modeling architectures. Amazon uses SimpleDB, Google has BigTable, and Microsoft has SQL Data Services, which supports queues, (non-relational) tables, and blobs. Any part of your application that you feel has been forced into an RDBMS structure is best moved to this new data management paradigm. Some examples of such complex information are:

1. Tagging – When I first started using GMail, I was impressed with its email “Tagging” feature. Labels allow you to “tag” your email with different names. Tagging is clearly superior to using folders, because if you tag an email as Work, Project, and Web 2.0, you have not one, but three different ways to get to the email. So after a few years of using GMail, today I am wrestling with the idea of ​​having “folders” in my email client. Information tagging or tagging is practically not suitable for RDBMS or hierarchical databases. So if you have or plan to use tags or folksonomy in your product, you would be wise to move it to the cloud.
2. Data-centric applications that have multiple interconnections between nodes: This is self-explanatory, but there are many data-intensive applications that can benefit from a rethink in the way their data is modeled. This goes back to the force fit I referred to earlier, and you’d clearly be making the right move by moving it to the cloud.

So, viewed from a data modeling perspective, cloud computing becomes an extremely important piece of a puzzle. You need scalability when using some of these newer data models, and cloud computing is your best bet to get it right.