Analytics/Elastic

If you activate service.monitor in map.apps and/or security.manager, concrete user interactions of the users are recorded and sent to Elasticsearch via the monitor-analytics webapp and a Logstash pipeline. You can view and analyze the collected data using the dashboards available in Kibana.

service.monitor also supports collecting ArcGIS Server and Portal for ArcGIS logfiles. Additional, it provides simple methods for visualization and analyzation of data.

Using Elasticsearch Metricbeat a more detailed understanding of the load on your ArcGIS Enterprise ArcSOC processes can be achieved. service.monitor provides diagrams that show the number of active SOC processes and their load (CPU, RAM) on your ArGIS host system(s).

service.monitor also allows the display of FME job information and logs output that has arisen during the execution of jobs. By regularly querying the FME job repository, detailed data on the use and utilisation of the FME infrastructure is available, which can be displayed statistically and visually on the dashboards.

In recent years, central log data aggregators have become very important for the successful operation of IT systems. This is one of the core competencies of the Elasticsearch Stack. The products and software artifacts developed at con terra support the storage of application log files in such central systems instead of writing this information to the local file system. service.monitor Analytics contains a logstash pipeline that can record and modify log events and send them to Elasticsearch for storage.

service.monitor Monitoring and Analytics can be linked together via a simple data transfer. If the transfer is active, all information about individual monitoring events (service, job, URL, success, error, etc.) is sent from the monitoring to a Logstash pipeline, where it is modified and sent to Elasticsearch for storage. You can then meaningfully analyze this data using the convenient interaction options of the dashboards.

This overview should help to better understand the interrelationships of data sources and necessary installation steps and give hints on how to check the successful data flow.