by Greg Shields

Yet this top-level approach to network monitoring is only the first of the capabilities you need. Aggregating statistics from multiple sources, crunching their data, and presenting them to a dashboard gives you only the highest-level representation of your network’s health.

Sometimes you need to dig deeper into the communications that occur between devices on your network. Sometimes you need to analyze the individual conversations that occur between two servers or two applications. These “transactions” between different components tell a lot about the interactions between servers. They further tell a lot about when those interactions are and aren’t going well.

This is particularly the case with custom-built applications, where deep application monitoring may not have been coded into the product. It is also powerful in situations where your organization has integrated many off-the-shelf applications to create what amounts to a homegrown application out of many disparate parts.

I talk more in more detail about exactly how transactions can be measured in Chapter 4 of my book The Definitive Guide to Application Performance Management. In the following quote, I discuss how an Application Performance Management solution’s agentless monitoring can watch the entire network at once to construct how well servers are interacting:

When thinking about this concept of transactions, it is important to consider the individual conversations between the different elements on a system. Consider, for example, the types of conversations that could potentially occur between a generic Web server and [an Application Server that it relies upon]. Those conversations have both a source and destination IP address, but they also operate over a known set of TCP or UDP ports. Within a single set of ports, individual Web services at both ends can transfer multiple types of information, with the ultimate end consumer of this information being different services on each server.

A result of this level of detail is that conversational elements and areas of unacceptable time lag can be identified within the individual code elements of each server’s Web services. For example, if a particular callback from one server to another shows a high rate of delay, while the network itself can be eliminated as a source of lag, it grows very easy to flag the situation to developers. Ultimately, the end goal is to quickly identify the problem and come to a resolution that can be patched into the system.

Solutions like Compuware Vantage, Quest Foglight, radware Insite, and Precise Transaction Performance Management, among others, include transaction monitoring capabilities to get you this server-to-server or server-to-device data that you need. These solutions, commonly grouped together under the banner of Application Performance Management, are specifically designed to highlight root causes for failures while at the same time profiling application behaviors over time.

About the Author

Greg Shields is an independent author, speaker, and IT consultant, as well as a Partner and Principal Technologist with Concentrated Technology. With 15 years in information technology, Greg has developed extensive experience in systems administration, engineering, and architecture specializing in Microsoft OS, remote application, systems management, and virtualization technologies. He is a Contributing Editor and columnist for TechNet Magazine and Redmond Magazine, and serves as the Series Editor for Realtime Publishers, the world’s leading provider of high-quality content for the IT market. Greg is a highly sought-after and top-ranked speaker for both live and recorded events, and is seen regularly at conferences like TechMentor Events, Microsoft Tech Ed, VMworld, and more. He is a multiple recipient of Microsoft “Most Valuable Professional” award.