Let's understand user interaction before diving into the core components of Kibana. A typical user interaction flow is as depicted in the following diagram:

The following points will give you a clear idea of the user interaction flow in Kibana:

• Prior to using Kibana for data analysis, the user will have already loaded the data into Elasticsearch.
• In order to analyze the data using Kibana, the user has to first make Kibana aware of the data stored in ES indexes. So, the user will need to configure the indexes on which they want to perform analysis.
• Once configured, the user has to find out the data structure, such as the fields present in the document and the type of fields present in the document, and explore the data. This is done so that they can decide how they can visualize this, and what type of questions they want to pose and find answers for, in terms of the data.
• After understanding the data, and having formed questions to find answers to, the user will create appropriate visualizations that will help them seek the answers easily from huge amounts of data.
• The user then creates a dashboard from the set of visualizations created earlier, which will tell the story of the data.

• This is an iterative process and the user would juggle around the various stages to find answers to their questions. Thus, in this process, they might gain deeper insights into the data and discover answers to newly formed questions, that they might not even have thought of before beginning this process.

Now that we have an idea about how the user would use Kibana and interact with it, let's understand what Kibana is made up of. As seen in the left-hand side of the collapsible menu/sidebar, the Kibana UI consists of the following components:

• Discover: This page assists in exploring the data present in ES Indexes. It provides the ability to query data, filter data, and inspect document structures.
• Visualize: This page assists in building visualizations. It contains a variety of visualizations, such as bar charts, line charts, maps, tag clouds, and so on. The user can pick and choose the appropriate visualizations that help in analyzing the data.
• Dashboard: This page assists in bringing multiple visualizations on to a single page, and thus builds a story about the data.
• Dev Tools: This page consists of a set of plugins, each of which assists in performing different functionalities. By default, this page contains only a single plugin, called Console, which provides a UI to interact with the REST API of Elasticsearch.
• Management: This page assists in the configuring and managing of indexes. It also assists in the management (deleting, exporting, and importing) of existing visualizations, dashboards, and search queries.