Numerify & AppDynamics
Change success is hard – there are demands for accelerating velocity. However, the data that can predict whether or not a change is risky resides in different process and system silos, both upstream in the development process and downstream in the impact of the change. E.g., Have similar changes caused performance degradation (measured by APM systems) or user-reported incidents (in ITSM systems)? What was the root cause of these change failures?
Together, AppDynamics and Numerify can help teams correlate APM alerts and metrics with ITSM change, incident, and problem data as well as DevOps toolchain data. Teams can use this to directly measure the impact of development process metrics, like code quality and test results, on application performance and user-reported incidents. Doing so will allow teams to identify issues in any part of the value chain and ensure that AI Learning models in identifying failed changes and predicting the risk of future major incidents.
Numerify leverages the AppDynamics REST APIs. Using ADQL, Numerify’s API Adapter performs full or incremental extracts at scheduled intervals. It extracts metrics for AppDynamics’ End-User Monitoring and APM Transaction Analytics modules currently providing aggregated business transactions, application response time, active user session, and other business performance metrics. Numerify extracts application raw transaction metrics and end-user metrics aggregated at the source for 10-minute intervals by browser, device, and location, as available and needed for our solutions. Numerify’s IT Business Analytics platform then transforms and loads this to Numerify’s data warehouse to be used by our BI and AI/ML framework supporting our various solutions.
Provided is an example of one of the Numerify Change Risk Prediction solution dashboards and the complementary data provided by AppDynamics.
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