In our fourth and final article on real-time metrics, we will look at how to easily implement them in order to obtain fast results.
Quick results are a critical success factor for every information initiative. The starting point is therefore an obvious business problem that can be solved by new or better data. For example, businesses have to understand which financial effects, such as lost sales, result from a system failure. Only then it can be determined, based on the data available, how much effort should be spent on preventing malfunctions.
The integration of data from various expert tools in LeanIX is easy and does not require in-depth expert knowledge.
All development resources for LeanIX Metrics are freely available. The code example shows the basic principle. A new data point is set up for a "measurement," e.g. CPU. This data point has a time reference, e.g. 2016-04-22 23:30. A field indicates the characteristic of the data point, e.g. the CPU "load." The fields are clearly assigned to a specific fact sheet in LeanIX, e.g., to an application, over the course of a day. The data points are transferred to Metrics via the LeanIX API.
Diagrams can be configured in the LeanIX Admin section without requiring programming expertise from the end-user. Metrics can be allocated via rules to specific fact sheet IDs or fact sheet types. Based on the type of data, a suitable diagram type can be selected and parameters such as chronological aggregation or colors can be adjusted as desired.
The view of the metrics can again be adjusted on the respective fact sheet. Thus it can be determined whether diagrams are displayed side by side or on top of each other. Furthermore, the end-user can aggregate the time data at will via the scroll bar.
Specific metrics not only refer to a fact sheet but also apply to an entire fact sheet type, for example. These metrics can be conveniently displayed in the reporting section.