Kibana Install Help | Stable Setup Methods for Linux

While implementing visual solutions for data monitoring and analytics at IOFLOOD, we looked to Kibana for its robust integration with Elasticsearch. We’ve gathered our most efficient installation steps methods and some examples to aid our customers looking to deploy a Kibana installation on their dedicated server hosting services for dynamic data analysis tools.

In this Kibana guide we will navigate the installation process for Linux systems. We are going to provide you with instructions for Debian and Ubuntu using APT package management, and CentOS and AlmaLinux using YUM package manager. We’ll delve into more advanced topics like compiling Kibana from source, and installing a specific version. Finally, we will guide you on how to use Kibana in Linux.

So, let’s get started with the step-by-step Kibana installation on your Linux system!

TL;DR: How can I Install Kibana on Linux?

Kibana can be installed on Linux using the package manager. For Debian-based distributions like Ubuntu, use the command sudo apt-get install kibana. For RPM-based distributions like CentOS, use sudo yum install kibana.

# For Debian-based distributions
sudo apt-get install kibana

# For RPM-based distributions
sudo yum install kibana

# Output:
# Reading package lists... Done
# Building dependency tree
# Reading state information... Done
# kibana is already the newest version (7.14.1).
# 0 upgraded, 0 newly installed, 0 to remove and 0 not upgraded.

This is a basic way to install Kibana on Linux, but there’s much more to learn about installing Kibana and its usage. Continue reading for more detailed information, advanced installation options, and troubleshooting tips.

Starting Off: Linux Kibana Install

Kibana is an open-source data visualization and exploration tool used for log and time-series analytics, application monitoring, and operational intelligence use cases. It offers powerful and easy-to-use features such as histograms, line graphs, pie charts, heat maps, and built-in geospatial support. Also, it provides tight integration with Elasticsearch, a popular analytics and search engine.

Install Kibana with APT

For Debian-based distributions like Ubuntu, you can use the APT package manager to install Kibana. Here’s how you can do it:

# Update your package lists
sudo apt-get update

# Install Kibana
sudo apt-get install kibana

# Output:
# Reading package lists... Done
# Building dependency tree
# Reading state information... Done
# kibana is already the newest version (7.14.1).
# 0 upgraded, 0 newly installed, 0 to remove and 0 not upgraded.

In the above code, the first command updates your package lists. The second command installs Kibana. The output shows that Kibana is successfully installed.

Install Kibana with YUM

For RPM-based distributions like CentOS, you can use the YUM package manager to install Kibana. Here’s how:

# Update your package lists
sudo yum check-update

# Install Kibana
sudo yum install kibana

# Output:
# Loaded plugins: fastestmirror, ovl
# Loading mirror speeds from cached hostfile
# Package kibana-7.14.1-1.x86_64 already installed and latest version
# Nothing to do

In the above code, the first command checks for updates. The second command installs Kibana. The output shows that Kibana is successfully installed.

Install Kibana from Source

Sometimes, you might want to install Kibana from source. This can be useful if you want to modify the source code or try out the latest features before they’re released officially. Here’s how you can do it:

# Clone the Kibana repository

git clone https://github.com/elastic/kibana.git

# Navigate to the Kibana directory

cd kibana

# Install dependencies

yarn

# Start the server

yarn start

# Output:
# Server running at http://localhost:5601

The above commands clone the Kibana repository, navigate into the directory, install the necessary dependencies, and start the server.

Installing Specific Versions of Kibana

Different versions of Kibana offer various features, bug fixes, and improvements. You might want to install a specific version to access certain features or ensure compatibility with other software. Here’s how you can do it using APT and YUM package managers, and from source.

Specific Version Kibana Install with APT

# Install a specific version of Kibana

sudo apt-get install kibana=7.14.1

# Output:
# Reading package lists... Done
# Building dependency tree
# Reading state information... Done
# kibana is already the newest version (7.14.1).
# 0 upgraded, 0 newly installed, 0 to remove and 0 not upgraded.

Specific Version Kibana Install with YUM

# Install a specific version of Kibana

sudo yum install kibana-7.14.1

# Output:
# Loaded plugins: fastestmirror, ovl
# Loading mirror speeds from cached hostfile
# Package kibana-7.14.1-1.x86_64 already installed and latest version
# Nothing to do

Specific Version Kibana Install from Source

# Clone the Kibana repository

git clone https://github.com/elastic/kibana.git

# Navigate to the Kibana directory

cd kibana

# Checkout to a specific version

git checkout v7.14.1

# Install dependencies

yarn

# Start the server

yarn start

# Output:
# Server running at http://localhost:5601

Using and Verifying New Kibana Install

After you’ve installed Kibana, you can access it by navigating to http://localhost:5601 in your web browser. You should see the Kibana home page, indicating that the installation was successful. Here’s a simple example of how to use Kibana to verify that it’s installed correctly:

# Verify Kibana installation

curl http://localhost:5601

# Output:
# Kibana is up and running

In the above command, curl sends a request to the Kibana server running on localhost at port 5601. The output indicates that Kibana is up and running.

Kibana Setup in Docker

Docker is a popular platform that simplifies software deployment using containerization. It can also be used to install Kibana, which can be beneficial if you want to maintain the same environment across different systems or if you want to avoid potential conflicts with other software on your system.

Here’s how you can install Kibana using Docker:

# Pull the Kibana Docker image

docker pull docker.elastic.co/kibana/kibana:7.14.1

# Run Kibana

docker run --name kibana -p 5601:5601 -d docker.elastic.co/kibana/kibana:7.14.1

# Output:
# Unable to find image 'docker.elastic.co/kibana/kibana:7.14.1' locally
# 7.14.1: Pulling from kibana/kibana
# Digest: sha256:2a8fb5757e4b3a6430bd1385e2e4e71a2c11b36ae142c31a2a4a233ed13f65ec
# Status: Downloaded newer image for docker.elastic.co/kibana/kibana:7.14.1
# 2aeccbfa3643e2b2910f5c8e57a6aa348f4231008d982b3a36dc2b3884d1d2d7

The above commands pull the Kibana Docker image from the Docker repository and run it in a Docker container. The -p flag maps port 5601 of the container to port 5601 of the host machine, allowing you to access Kibana at http://localhost:5601.

Advantages of Docker Kibana Setup

• Consistency: Docker ensures that the software runs the same way, regardless of the environment.
• Isolation: Docker isolates the software from the rest of the system, preventing potential conflicts.
• Simplicity: Docker simplifies the installation and deployment of software.

Disadvantages of Using Docker

• Learning Curve: Docker can be complex and requires time to learn.
• Overhead: Docker introduces some overhead because it runs an entire operating system for each container.

Recommendations

If you’re an experienced Linux user and you’re familiar with Docker, using Docker to install Kibana can be a good option. It provides consistency, isolation, and simplicity, but it also requires more resources and knowledge compared to traditional installation methods.

Troubleshooting Kibana Install Issues

While installing Kibana on Linux, you might encounter some issues. Here are a few common problems and their solutions.

Kibana Fails to Start

Sometimes, Kibana might fail to start due to various reasons such as incorrect configuration, port conflicts, or insufficient system resources. You can check the Kibana logs for any error messages.

# Check Kibana logs

sudo journalctl -u kibana

# Output:
# -- Logs begin at Mon 2021-09-13 14:12:10 PDT, end at Mon 2021-09-13 15:03:01 PDT. --
# Sep 13 15:03:01 localhost.localdomain kibana[1234]: {"type":"log","@timestamp":"2021-09-13T22:03:01Z","tags":["info","plugins-service"],"pid":1234,"message":"Plugin "visTypeXy" is disabled."}

In the above command, journalctl -u kibana displays the logs for the Kibana service. The output shows the log entries, which can help you diagnose the problem.

Kibana is Not Accessible at http://localhost:5601

If Kibana is running but you can’t access it at http://localhost:5601, there might be a network issue or a firewall blocking the port. You can check if Kibana is listening on the correct port using the netstat command.

# Check if Kibana is listening on port 5601

sudo netstat -tuln | grep 5601

# Output:
# tcp        0      0 127.0.0.1:5601          0.0.0.0:*               LISTEN

In the above command, netstat -tuln | grep 5601 checks if any process is listening on port 5601. The output shows that Kibana is listening on 127.0.0.1:5601.

Kibana Version Incompatibility with Elasticsearch

Kibana and Elasticsearch versions should be compatible. If they’re not, you might encounter errors. You can check the versions of Kibana and Elasticsearch to ensure compatibility.

# Check Kibana version

kibana --version

# Output:
# 7.14.1

# Check Elasticsearch version

curl -X GET "localhost:9200"

# Output:
# {
#   "name" : "Cp8oag6",
#   "cluster_name" : "elasticsearch",
#   "cluster_uuid" : "AT69_T_DTp-1qgIJlatQqA",
#   "version" : {
#     "number" : "7.14.1",
#     ...
#   },
#   "tagline" : "You Know, for Search"
# }

In the above commands, kibana --version and curl -X GET "localhost:9200" check the versions of Kibana and Elasticsearch, respectively. The output shows that both are version 7.14.1, indicating compatibility.

What is Elastic and Data Visualization

Before we delve deeper into Kibana, it’s essential to understand the underlying concepts of Elasticsearch and data visualization.

Elasticsearch: The Heart of Data Analysis

Elasticsearch is a powerful, open-source search and analytics engine. It’s capable of handling a wide variety of data types and volumes, making it a popular choice for log and event data, real-time application monitoring, and clickstream analysis.

# Example of a search query in Elasticsearch

curl -X GET "localhost:9200/_search?q=user:anton"

# Output:
# {
#   "took" : 3,
#   "timed_out" : false,
#   "_shards" : {
#     "total" : 1,
#     "successful" : 1,
#     "skipped" : 0,
#     "failed" : 0
#   },
#   "hits" : {
#     "total" : {
#       "value" : 1,
#       "relation" : "eq"
#     },
#     "max_score" : 0.2876821,
#     "hits" : [
#       {
#         "_index" : "users",
#         "_type" : "_doc",
#         "_id" : "1",
#         "_score" : 0.2876821,
#         "_source" : {
#           "user" : "anton",
#           "post_date" : "2009-11-15T14:12:12",
#           "message" : "Trying out Elasticsearch, so far so good!"
#         }
#       }
#     ]
#   }
# }

In the above example, we’re using a search query to find all documents in our Elasticsearch cluster where the user field is ‘anton’. The output shows the search results, including the document’s index, type, id, score, and source.

The Power of Data Visualization

Data visualization is a critical part of data analysis. It involves creating visual representations of data to uncover patterns, trends, and insights that might not be apparent from raw data. It’s a way to make sense of complex data sets by representing them in a more human-friendly and understandable format.

Kibana excels in this domain. It provides various visualization options like charts, tables, maps, and more, allowing you to visualize your data in the way that makes the most sense for your analysis.

# Example of a Kibana visualization query

GET /_sql?format=txt
{
  "query": "SELECT COUNT(*) AS count FROM log WHERE response = 200 GROUP BY agent.keyword"
}

# Output:
#   count  |  agent.keyword
# ---------+------------------
#      34  |  Mozilla/5.0
#      12  |  Opera/9.80
#       6  |  Mozilla/4.0

In the above example, we’re using a SQL-like query in Kibana to count the number of logs with a 200 response for each user agent. The output shows the count and user agent, providing a clear visualization of the data.

Understanding Elasticsearch and data visualization is crucial for making the most out of Kibana. They’re the foundation upon which Kibana builds, providing powerful data analysis and visualization capabilities.

Practical Uses of a Kibana Setup

Kibana is not just a tool for installing and managing Elasticsearch data. It’s a powerful platform that can greatly enhance your data analysis and monitoring capabilities. With Kibana, you can create visualizations and dashboards that allow you to interact with your data in real-time, giving you valuable insights that can help you make informed decisions.

# Example of a Kibana dashboard query

GET /_sql?format=txt
{
  "query": "SELECT COUNT(*), AVG(response_time) AS avg_response_time FROM log GROUP BY user.keyword"
}

# Output:
#   count  |  avg_response_time  |  user.keyword
# ---------+---------------------+------------------
#      12  |              0.234  |  Mozilla/5.0
#       8  |              0.312  |  Opera/9.80
#       4  |              0.178  |  Mozilla/4.0

In the above example, we’re using a SQL-like query in Kibana to create a dashboard that shows the count and average response time for each user agent. The output shows the count, average response time, and user agent, providing a clear visualization of the data.

Completing Your ELK Stack

While Kibana is a powerful tool on its own, its true potential is unlocked when used in conjunction with Elasticsearch and Logstash. Elasticsearch is a powerful search and analytics engine, while Logstash is a data processing pipeline that ingests data from multiple sources simultaneously, transforms it, and then sends it to a ‘stash’ like Elasticsearch. Together, they form the ELK Stack, a powerful trio of tools that can handle everything from data aggregation and processing to search and visualization.

# Example of a Logstash pipeline configuration

input {
  file {
    path => "/path/to/logfile"
    start_position => "beginning"
  }
}

filter {
  grok {
    match => { "message" => "%{COMBINEDAPACHELOG}" }
  }
}

output {
  elasticsearch {
    hosts => ["localhost:9200"]
  }
}

# Output:
# Successfully started Logstash API endpoint {:port=>9600}

In the above example, we’re configuring a Logstash pipeline that reads a log file, processes the log entries using a grok filter, and then sends the processed data to Elasticsearch. The output shows that the Logstash API endpoint has started successfully.

Further Resources for a Kibana Guide

If you’re interested in delving deeper into Kibana, Elasticsearch, and Logstash, here are some resources that you might find useful:

1. Elasticsearch: The Definitive Guide – A comprehensive guide to Elasticsearch, covering everything from basic concepts to advanced topics.

2. Kibana User Guide – The official Kibana user guide, which provides detailed instructions on how to use Kibana’s various features.

3. Logstash Reference – A detailed reference to Logstash, including installation instructions, configuration examples, and plugin documentation.

Recap: Linux Kibana Install Methods

In this comprehensive guide, we have explored the process of installing Kibana on Linux, a powerful tool for visualizing Elasticsearch data.

We began with the basics, explaining how to install Kibana using package managers like APT for Debian-based distributions and YUM for RPM-based distributions. We then delved into more advanced topics, such as installing Kibana from source and installing specific versions of Kibana.

We also tackled common issues you might encounter during the installation process, such as Kibana failing to start, network issues, and version incompatibility with Elasticsearch. For each issue, we provided practical solutions and helpful tips.

In addition, we explored alternative approaches to installing Kibana, such as using Docker. We discussed the advantages and disadvantages of these methods, providing a comprehensive view of the different ways to install Kibana on Linux.

Whether you’re a beginner just starting out with Kibana, an intermediate user looking to level up your skills, or an expert interested in alternative installation methods, we hope this guide has been a valuable resource.

Now, you’re well-equipped to install Kibana on Linux and start visualizing your Elasticsearch data. Happy data analyzing!