One of my chores at home as a husband is doing the food shopping (I also take out the trash, play with the kids, and even cook Saturday evening dinner – truly husband of the year!). Food shopping should actually be very easy to do. The decision maker (a.k.a. wife) hands me the list, and I need to deliver. However, sometimes the instructions I get are not accurate enough and I need to use my judgment (while in the field) and decide which product I should buy.
For example, last week I had to buy olive oil. Since I didn’t know exactly what kind to buy, and since there are tons of them, I found myself going back and forth across the shelves, trying to figure out which one to choose.
Marketers would pay a fortune to understand how to influence my decision-making process when I shop. One of the interesting ways to do so is by observing the shoppers’ behavior while they shop, analyze the data and get conclusions that will improve their ability to influence. Using this method, they try to analyze how people behave when they buy and what makes them eventually to get a decision. For example, in order to determine the best location on the shelf, they would see: how many people pass by; how many stopped; how long they stayed in front of the shelf; and whether or not they made a purchase, bought the competition, or didn’t buy at all.
Understanding the behavior of “objects” in order to learn how best to impact or change them is a concept that works well in almost any discipline. For example, lately I heard about an implementation of Thermodynamics theories, where in order to understand how to build effective emergency exits, the human behavior (many people trying to rush out of a closed space) was modeled using the motion of particles and their microscopic behavior (random movements of many elements).
This concept makes a lot of sense. How can you impact something, improve something, or make a wise decision if you do not have a thorough understanding of the behavior of the element you are handling, right?
The same concept can be applied to Application Performance Management (APM). A transaction management solution which has cross-tier transaction behavior analysis and is capable of detecting changes in transaction and application behavior is key in order to be able to:
Transaction management has many facets. Since the market does not have a unanimous definition of what transaction management is, many vendors can claim to have this capability, however, when diving into these solutions you could see their capabilities are significantly different. When choosing a transaction management solution, enterprises are encouraged to pay attention to whether the solution has the capability of automatically generating transaction and application behavior models. This can be achieved by a two-step process:
1. Tracking every individual transaction (shopper) across all elements (shelves), and meter how much time the transaction (shopper) spends on each element (shelf) and how many times it invokes each element (how many times the shopper comes back to each shelf).
2. Analyzing this mass of contextual data to automatically generate the transaction model of behavior. For the observed period of time, we can see how much time the transactions spent processing in each element, how many times each element was invoked, and what the difference is between transactions that met their SLA (customer bought the product) or exceeded the SLA (customer bought the competition).
The result is a transaction management solution that provides most valuable information that any performance analyst is looking for as soon as a disruption is noted. In other words, what is the element that causes the degradation, what is the change (among all other changes that happened during last day or week) that has actually caused the disruption, and what can and should be done to improve overall end-user experience?
When looking for a transaction management solution, make sure that it is capable of automatically building the transaction behavior model. This is a key capability that will turn your Application Performance Management from one big mess to an almost completely scientific decision making process.