There is a lot of value in visualizing data in Kibana but that value quickly reaches a limit unless you can also drill down to access the less obvious characteristics of your data. There are a number of ways to filter your data in Kibana from using the time picker with time-series data, crafting Kibana Query Language (KQL) queries, or just using the filtering mechanisms built in to the user interface. In this hands-on lab, we will explore the various ways to filter data in Kibana so that you can quickly discover the insights buried in your data.
Learning Objectives
Successfully complete this lab by achieving the following learning objectives:
- Create the `logs_1` Saved Search
- Navigate to the Discovery tab.
- Add the necessary filter(s) and/or Kibana Query Language (KQL) to meet the search criteria for the logs_1 query.
- Save the search as logs_1.
- Create the `logs_2` Saved Search
- Navigate to the Discovery tab.
- Add the necessary filter(s) and/or Kibana Query Language (KQL) to meet the search criteria for the logs_2 query.
- Save the search as logs_2.
- Create the `logs_3` Saved Search
- Navigate to the Discovery tab.
- Add the necessary filter(s) and/or Kibana Query Language (KQL) to meet the search criteria for the logs_3 query.
- Save the search as logs_3.
