In Agile software development, release cycles are short (typically no longer than a month) and responsive to direction from product managers, who are in turn responsive to the needs and wants of end users. The Agile approach to software engineering typically includes continuous integration. Agile continuous integration regularly brings together the various parts of an application to ensure that the application functions as expected. Increasingly, leading software makers are utilizing an advanced application performance monitoring (APM) solution like Dynatrace to gain even more value and insight from the Agile continuous integration process.
Among the many software makers who use Agile, continuous integration details may vary but usually it involves these core practices and continuous integration tools:
In some Agile environments, along with continuous integration the application team strives for continuous delivery – meaning that at all times the latest successful build of the application is ready to be quickly released to production. This approach requires continuous delivery tools such as configuration management technologies that allow for fast, automated deployments of application packages and supporting assets.
Agile continuous integration tells you every day whether or not the latest instance of your application is functioning as expected. Many progressive web and mobile application makers are taking the next step by using Dynatrace APM to gain real-time visibility into how the latest code check-ins are impacting key performance attributes of their applications. Dynatrace integrates seamlessly with leading build servers to provide immediate deep insight into architectural metrics (such as memory allocation, method invocations, service calls, and database queries), execution timings, and much more. Dynatrace also supports agile modeling by auto-modeling the up-to-minute application architecture and flows. Dynatrace alerts team members of performance red flags or regressions, and makes it fast and easy to pinpoint the root cause of performance issues – down to the method level.