Analytics Overview¶
The Analytics area of Kibana is where you work with the data your NetEye.Cloud tenant collects in Elasticsearch. Logs, events and metrics are stored as indexed documents, and Analytics gives you the tools to search them, look at them in detail and turn them into visual information you can share.
This section covers the Analytics applications available in your tenant, starting with the simplest way of working with data, and moving on to more structured views:
Discover: search and explore raw documents over a chosen time range, filter and sort results, inspect individual fields and save searches to reuse later. It also explains data views, which decide which indices or data streams each Analytics application works on.
Visualize Library: build charts, tables and metrics from your data and store them as reusable visualizations.
Dashboards: put several visualizations, saved searches and controls together in one view to keep track of the information that matters most to you.
Canvas: make free-form, presentation-style workpads that combine live data with text and images.
Maps: show geospatial data on interactive maps.
Machine Learning: analyze data to detect anomalies and identify patterns automatically.
Graph: explore connections and relationships between values in your indexed data.
The search bar, filters and time picker work the same way in every Analytics application. They’re explained in detail in the Discover chapter, and the later chapters build on that.
Note
What you can do in each application depends on your ELK role. Users with the VIEWER role can view data and existing objects. EDITOR and ADMIN users can also create and change saved objects such as searches, visualizations and dashboards. Each chapter has a Roles and Permissions note that lists the operations allowed for each role.