Elasticsearch & Kibana Docker Boilerplate

Overview

This boilerplate provides a configuration for running Elasticsearch and Kibana in Docker containers. It's based on the official Docker Compose file from Elastic, but with custom enhancements for greater flexibility and control. Additionally, it includes a separate Docker Compose setup for a custom application that interacts with Elasticsearch and Kibana.

Features

• Single-node Elasticsearch setup: Configured for a single-node (es01) setup, suitable for development and testing environments.
• Default Elasticsearch version: Sets the Elasticsearch version to 8.11.2 by default, adjustable via the ELASTIC_STACK_VERSION environment variable.
• Security toggle: Provides the option to enable or disable Elasticsearch security features using the ELASTIC_SECURITY_ENABLED environment variable; Kibana is automatically configured to adapt to the security configuration and healthcheks are adjusted accordingly.
• Elasticsearch plugin script: Includes a script to automate the management of Elasticsearch plugins, driven by environment variables.
• Volume for Elasticsearch plugins: Allocates a specific volume for Elasticsearch plugins to speed up container startup.
• Restart policy: Use the RESTART_POLICY environment variable to configure the restart policy for Elasticsearch and Kibana containers centrally. The default is set to no.
• Separate Docker Compose file for a custom Python app: Quickly set up a Python app as part of the stack interact using the docker-compose-app.yml). The app should be set up in the same directory as the Docker files.

Getting Started

Running Elasticsearch and Kibana

First, ensure that vm.max_map_count is set to at least 262144.

1. Ensure correct vm.max_map_count: See https://www.elastic.co/guide/en/elasticsearch/reference/current/docker.html#_set_vm_max_map_count_to_at_least_262144
2. Set Environment Variables: Copy .env.example to .env and set the required variables.
3. Start Services: Run docker compose up to start the Elasticsearch and Kibana services (or docker compose up -d to run in detached mode in the background).
4. Access Kibana: Once the services are up, access Kibana at http://localhost:${KIBANA_PORT}.

Running with Custom App

To run the Elasticsearch stack along with a custom application:

1. Set up your app: Set up your Python app in the same directory as the Docker files. Make sure a requirements.txt file is present, even if empty.
2. Set Up the Elasticsearch Stack: Follow the steps above to set up the environment variables and start the Elasticsearch and Kibana services.
3. Start All Services Including the App: Run docker compose -f docker-compose.yml -f docker-compose-app.yml up to start all services, including the custom application.

The app will have access to the same Docker network, so the service names (es01 and kibana) should be used as host names, not localhost.

Customization

• Elasticsearch Plugins: Adjust ELASTIC_PLUGINS in the .env file to manage plugins.
• Security Toggle: Use ELASTIC_SECURITY_ENABLED in .env to enable or disable Elasticsearch security features.