Right solution, right time
In Fall 2013, the AppDynamics France sales team visited the KIABI web IT department to propose a demonstration of its application performance management (APM) solution, oriented to production. The presentation was timely, since KIABI was beginning to consider ways of improving the productivity of its IT staff, particularly in terms of the identification and resolution of incidents.
KIABI web IT management was immediately impressed by the variety of back-end and front-end applications proposed by AppDynamics as well as the speed of implementation and ease-of-use. In addition, the AppDynamics tools were available in SaaS mode, unlike other legacy products on the market.
AppDynamics offered to perform a proof of value (POV), to ensure that its Application Intelligence Platform was a good fit for KIABI. The POV was conducted on the Spanish website, www.kiabi.es, during a high traffic sales period, which took place in January 2014. The web IT team was able to test two key modules offered by AppDynamics under production conditions, in order to explore the main features and ease of handling as well as analyze the indicators provided by the tool.
In parallel, AppDynamics worked on an ROI study with KIABI. An internal audit was conducted with technical and business teams including marketing, commercial operations and customer relations to collect metrics to develop plans for increased profits. It was clear from this study that the AppDynamics tool could reduce the time spent on troubleshooting by 50% within 6 to 9 months after the implementation of the solution.
"At the end of this POV, which was more than convincing, we decided to implement AppDynamics solutions on the French site www.kiabi.com in the month of February," said Théry.
Java APM solutions were deployed for monitoring application servers, and Browser Real User Monitoring (RUM) was put in place to monitor the browser behavior on the user-side of the site. [C1]
The AppDynamics Application Intelligence Platform utilizes a dynamic approach to performance management, learning and adjusting to trends. After a phase of collecting metrics, these adaptive tools set dynamic thresholds that make it easier to spot outliers. For example, a warning system could be programmed to alert of heap saturation in the Java Virtual Machine (JVM), slower web page response times, or degradation of call times for certain services such as the payments or package delivery tracking KIABI programmed alerts in servers and application layers, taking care that the metrics monitored had a direct impact on improving the business.