In a private cloud the data center, physical machines, and storage are all owned by the company that uses them. Sharing happens within the company. The usage of the resources can ebb and flow as determined by different departments and applications. The size of the shared cloud is likely to be smaller than within a public cloud, which may reduce the value of the sharing. Still, it is attractive to many companies because they do not need to trust an outside cloud provider. So far, we have seen only private-cloud IaaS. The new PaaS offerings are not yet being made available for individual companies to use in their private clouds.

Forces driving us to the cloud. A number of forces are prompting increased movement of applications to the cloud:

Data-center economics. Very large data centers can offer computation, storage, and networking at a relatively cost-effective price. Power is an ever-increasing portion of data-center costs, and it can be obtained more effectively by placing the data center near inexpensive sources of electricity such as hydroelectric dams. Internet ingress and egress is less expensive near Internet main lines. Containerized servers with thousands of machines delivered in a shipping container offer lower cost for computation and storage. Shared administration of the servers offers cost savings in operations. All of this is included in the enormous price tag for the data center. Few companies can afford such a large investment. Sharing (and charging for) the large investment reduces the costs. This provides economic drive for both the cloud providers and users.

Shared data. Increasingly, companies are finding huge (and serendipitous) value in maintaining a “big-data” store. More and more, vast amounts of corporate data are placed into one store that can be addressed uniformly and analyzed in large computations. In many cases the value of the discoveries grows as the size of the data store increases. It is becoming a goal to store all of an enterprise’s data in a common store, allow analysis, and see surprising value.

Shared resources. By consolidating computation and storage into a shared cloud, it is possible to provide higher

Power is
an ever-increasing
portion of
data-center costs,
and it can be
obtained more
effectively by
placing the data
center near
inexpensive
sources of
electricity such
as hydroelectric
dams.

utilization of these resources while maintaining strong SLAs for the higher-priority work. Low-priority work can be done during slack times while being preempted for higher-priority work during the busy times. This requires that resources are fluid and fungible so that the lower-priority work can be bumped aside and the resources reallocated to the higher-priority work.

SaaS: Front end, back end, and decision support. Let’s look more closely at a typical pattern seen in a SaaS implementation. In general, the application has two major sections: the front end, which handles incoming Web requests; and the back end, which performs offline background processing to prepare the information needed by the front end. In addition to its work preparing data for the front end, the back-end application is usually shared with decision-support processing (see Figure 2).

In a typical SaaS implementation the front end offers user-facing services dealing with Web services or HTML. It is normal for this Web-serving code to have aggressive SLAs, typically of only 300ms–500ms, sometimes even tighter. The back-end processing consumes crawled data, partner feeds, and logged information generated by the front end and other sources, and it generates reference data for use by the front end. You may see product catalogs and price lists as reference data, or you may see inverted search indices to support systems such as Google or Bing search. In addition to the generation of reference data, the back-end processing typically performs decision-support functions for the SaaS owner. These allow “what-if” analyses that guide the business.

Patterns in saas apps:
the front end

Here, I explore a common pattern used in building the front-end portion of SaaS applications. By leveraging the pattern used by these applications, a number of very useful concierge services can be supplied by the PaaS plumbing.

Many service applications fit nicely within a pattern of behavior. The goal of these applications is to implement the front end of a SaaS application. Incoming Web-service requests or HTML