Application Analytics By @AppDynamics | @DevOpsSummit [#APM #DevOps]

In my last blog post, I made a case for the powerful combo of APM and Analytics that you shouldn’t miss out on. Today, I’m going to explain what I mean by that with an example on how you can build better apps and write better code leveraging this powerful combination.

There is a common misperception that the only way a developer can write better code is by running profilers and by painstakingly collecting every call graph of their application to learn how its code is actually behaving. Cutting edge developers have started using application performance management (APM) to understand code performance and identify bottlenecks. The problem with both these approaches is that this often results into testing just the happy-path of your code. Negative or failure testing will catch exception scenarios but that is rarely coupled with stress testing scenarios. Rarely do testers test combine the two (negative and stress) to uncover scenarios that develop over time with cumulative or sequential failures.

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