Sizing Portal applications during Pre-sales activities
More and more customers have been asking for sizing inputs during RFP phase itself. Sizing depends on many factors and hence it is not a trivial exercise to arrive at sizing information at this stage. Some of the inputs that are required for sizing are:
- Page views per second
- Hits per second
- Hit to cache ratio
- Think time of users
- Service time
- Concurrent sessions
- Ratio of static and dynamic pages
- Usage of SSL
- Usage of clusters
The above is only a partial listing.
During the pre-sales stage, some customers might be able to give an idea of expected hits per second. However, if one were to ask a customer about number of portlets on a page to arrive at possible caching, most customers will be lost for ideas. Hence it is important to educate the customer that sizing at this stage can only be indicative and a correct figure can only be arrived at after a detailed analysis.
Approaches for Sizing
There are essentially three approaches for arriving at sizing recommendations:
1. Sizing based on some algorithm and formulae
2. Sizing based on Proof-of concept
3. Sizing based on benchmarked applications
The first approach (Sizing based on some algorithm and formulae) is probably more scientific and logical than others. However, portal applications are a completely new breed of applications and are evolving at a rapid pace. Hence there is not enough historical data to arrive at an algorithm to predict accurate sizing. Secondly, any algorithm or formulae will require inputs that will be difficult to obtain during pre-sales stage.
The second approach (Sizing based on Proof-of concept) will possibly give most accurate results. However, it is time and resource consuming and can not be carried out during the pre-sales stage.
The last approach (Sizing based on benchmarked applications) provides an optimal method to arrive at sizing recommendations. It is based on a set of assumptions and is based on a set of benchmarked applications. In this approach, the customer application is compared with a benchmark application using same or similar technologies. The results are extrapolated to arrive at approximate sizing figures.
I have a working example of this approach. Mail me if you need one.
Updated: 20th May, 2005