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The Critical Use Cases for Application Intelligence Among Higher Ed IT Departments

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Universities are extremely dependent on the performance of third-party applications in their environment such as Blackboard and Kuali Financial Systems. These applications are vital tools to ensure a seamless user experience and to modernize their course registration, records management, and even financial systems. For schools that had been using homegrown applications or archaic card systems, these applications have made lives immensely easier. However, there are real risks in using these third-party applications that can be easily mitigated with Application Intelligence.

Third-Party Application Monitoring

We’ve all been there when something goes wrong, and you’re on hold with your vendor’s support team trying to resolve the issue. The only problem in universities scenarios? It’s midnight, and 20,000 students are attempting to sign up for that semester’s classes. Higher education environments are unique in their inconsistent loads and zero-tolerance policy for downtime.

In the above scenario, you’re either reliant on the vendor – or, if it’s an open source solution, your own wits – to get the application back up and running before your students start complaining.

The right Application Intelligence tool can utilize Application Performance Monitoring (APM) to help universities troubleshoot their performance problems in their third-party applications on the fly. (For further reading, check out how Cornell University, Washington University of St. Louis, and Missouri State use AppDynamics to solve their performance issues.)

The IT staff at these universities are able to provide support teams with fine-grained detail about performance problems in production. When selecting an APM tool, however, these universities discovered that not all solutions are created equal. A good APM solution must be extremely intuitive, far-ranging in its capabilities, and able to speak the language of business – not the language of developers.

Use Business Transactions to Obtain End-to-end Visibility

Traditional monolithic applications often consisted of little more than a few JVMs talking to one another. In the present day, a typical IT environment consists of a multitude of open source and proprietary components and distributed tiers, all attempting to communicate together in order to perform complex business transactions.

Too often APM tools captures just a piece of this massive web of communication — but are unable to reveal the entire architecture, leaving blind spots in place. The right tool should not just provide visibility into what already exists, but be able to automatically discover, trace, correlate, and visualize transaction performance for new releases.

This is made possible with business transactions — check out my blog on the importance of using business transactions as a best practice here. Business transactions allow the tool to create a common language between developers and IT operations by representing the end user request, rather than a snippet of code.

A business transaction represents a “user generated” action. For example, a student might register for a class in Blackboard, or a member of your financial services department might approve a purchase order in Kuali Financial System. The APM tool needs to be able to make these actions highly visible to the IT operations team. This is an essential part of the simplicity and usability of an APM tool: the ability to talk in the language of business.

Dynamic Baselines Help With Alerting

Once the APM tool gives you a clear view into the application’s business transactions, then it’s possible to measure the performance of those transactions. In legacy APM tools, you have to set manual thresholds for each transaction. For example, you might say that the class registration transaction takes two seconds on average, or the student log-in takes half a second.

The problem with this approach is you may not have the data to set those thresholds yourself. You could make an educated guess, but the burden is on you to tell the APM tool how well your application performs. If the transaction responds to load differently on Sunday versus Monday, or at 9 a.m. versus 8 p.m., or in late November versus the middle of July, it’s up to you to specify the appropriate threshold for each time period. If your performance policies aren’t granular enough to reflect the true performance profile that occurs during the hours in which you operate, as well as to account for periodic variations, you’ll either lack visibility or be flooded with false alarms.

The importance of the dynamic baselines is compounded among universities IT teams since the environment has such inconsistent load — registering for classes, exams, etc. — will screw with static baselines.

An APM tool that leverages best practices should be able to set those thresholds for you. This means being able to set baselines for your application by discovering how each transaction’s performance may vary over specified operating periods. It observes periodic variations, accounts for them, and sets thresholds accordingly. A tool that sets dynamic baselines for each business transaction will be highly accurate and eliminate false alarms.

In Summary

Managing higher education applications is hard …. but there are things you can do to make it easier on yourself and the universities IT department. Use the tools available to you to help your students have a smooth user experience and avoid application downtime.

If you’re interested in a deeper discussion on how AppDynamics helps universities with their application issues, check out our white paper: 4 Critical Strategies for Managing Higher Ed Apps.

Also, don’t just take our word for it, test drive a FREE trial of AppDynamics today!

The post The Critical Use Cases for Application Intelligence Among Higher Ed IT Departments written by appeared first on Application Performance Monitoring Blog from AppDynamics.

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