Chapter 11: User Interfaces

In an Elasticsearch ecosystem, it can be immensely useful to monitor nodes and clusters in order to manage and improve their performance and state.

Detecting malfunction or bad performance can be done through the API or through some frontends that are designed to be used in Elasticsearch.

Some of the frontends introduced in this chapter will allow you to have a working web dashboard in your Elasticsearch data; these work by monitoring cluster health, backing up or restoring your data, and allowing test queries before implementing them in the code. In this chapter, we will only briefly examine these frontends; this is due to their complexity and the large number of features, which are beyond the scope of this book. For an in-depth description, I suggest that you have a look at the official documentation of Kibana, which is available at https://www.elastic.co/guide/en/kibana/current/index.html.

In this chapter, we will explore some aspects of Kibana...

Installing Kibana

The most well-known Elasticsearch interface is Kibana, and it is always released with Elasticsearch.

Kibana is a pluggable interface and is free to use with Elasticsearch. It provides data visualization, and it can be extended with a commercial product called X-Pack that provides security, graph capabilities, cluster monitoring, and many other features.

In this chapter, we will mainly cover the Kibana core components. Kibana with X-Pack offers a lot of functionalities and, as these are beyond the scope of this book, I suggest that you look for books related to Kibana for a full description of all Kibana's capabilities.

Getting ready

You will need an up-and-running Elasticsearch installation, similar to the one that we described in the Downloading and installing Elasticsearch recipe in Chapter 1, Getting Started.

If you are installing using Docker Compose, which is available in the ch01 directory, then you don't need to manually install it...

Managing Kibana Discover

One of the most popular aspects of Kibana is the Discover dashboard. This is because it allows you to dynamically navigate your data. With the evolution of Kibana, a lot of new features have been added to the Discover dashboard in order to allow you to easily filter and analyze your data.

Getting ready

You will need an up-and-running Elasticsearch installation, similar to the one that we described in the Downloading and installing Elasticsearch recipe in Chapter 1, Getting Started. Additionally, a working Kibana instance is required, as described in the Installing Kibana recipe of this chapter.

If you have used Docker Compose, which is available in the ch01 directory, then everything should be correctly installed.

How to do it...

For managing Kibana dashboards, we will perform the following steps:

1. Access the Analytics | Discover section of Kibana, as shown in the following screenshot:

Figure 11.5 – Kibana...

Visualizing data with Kibana

Kibana allows you to create reusable data representations called visualizations. These are representations of aggregations and can be used to power up the dashboard using custom graphs. In general, you can consider visualization as a building block for your dashboard.

Getting ready

You will need an up-and-running Elasticsearch installation, similar to the one that we described in the Downloading and installing Elasticsearch recipe in Chapter 1, Getting Started. Additionally, a working Kibana instance is required, as described in the Installing Kibana recipe of this chapter.

If you have used Docker Compose, which is available in the ch01 directory, then everything should be correctly installed.

How to do it...

To use Kibana to create custom widgets, we will perform the following steps:

1. Access the Analytics | Visualize Library section of Kibana, as shown in the following screenshot:

Figure 11.10 – Visualize...

Using Kibana Dev Tools

Kibana provides a very useful section for developers: Dev Tools. This section contains four tools:

• Console: The place where the developer tests and executes commands.
• Search Profiler: A tool that is used to profile queries.
• Grok Debugger: This is useful for debugging Grok regular expressions.
• Painless Lab (beta): This enables you to test and debug Painless scripts.

Getting ready

You will need an up-and-running Elasticsearch installation, similar to the one that we described in the Downloading and installing Elasticsearch recipe in Chapter 1, Getting Started. Additionally, a working Kibana instance is required, as described in the Installing Kibana recipe of this chapter.

If you have used Docker Compose, which is available in the ch01 directory, then everything should be correctly installed.

How to do it...

To use Console, we will perform the following steps:

1. Access the Dev Tools section of Kibana, as shown in the...