bitnami/elasticsearch repository overview

⁠Bitnami Elasticsearch Stack

⁠What is Elasticsearch?

Overview of Elasticsearch⁠ Trademarks: This software listing is packaged by Bitnami. The respective trademarks mentioned in the offering are owned by the respective companies, and use of them does not imply any affiliation or endorsement.

⁠TL;DR

docker run --name elasticsearch bitnami/elasticsearch:latest

You can find the available configuration options in the Environment Variables⁠ section.

⁠Why use Bitnami Secure Images?

Those are hardened, minimal CVE images built and maintained by Bitnami. Bitnami Secure Images are based on the cloud-optimized, security-hardened enterprise OS Photon Linux⁠. Why choose BSI images?

• Hardened secure images of popular open source software with Near-Zero Vulnerabilities
• Vulnerability Triage & Prioritization with VEX Statements, KEV and EPSS Scores
• Compliance focus with FIPS, STIG, and air-gap options, including secure bill of materials (SBOM)
• Software supply chain provenance attestation through in-toto
• First class support for the internet’s favorite Helm charts

Each image comes with valuable security metadata. You can view the metadata in our public catalog here⁠. Note: Some data is only available with commercial subscriptions to BSI⁠.

If you are looking for our previous generation of images based on Debian Linux, please see the Bitnami Legacy registry⁠.

⁠How to deploy Elasticsearch in Kubernetes?

Deploying Bitnami applications as Helm Charts is the easiest way to get started with our applications on Kubernetes. Read more about the installation in the Bitnami Elasticsearch Chart GitHub repository⁠.

⁠Why use a non-root container?

Non-root container images add an extra layer of security and are generally recommended for production environments. However, because they run as a non-root user, privileged tasks are typically off-limits. Learn more about non-root containers in our docs⁠.

⁠Supported tags and respective Dockerfile links

Learn more about the Bitnami tagging policy and the difference between rolling tags and immutable tags in our documentation page⁠.

You can see the equivalence between the different tags by taking a look at the tags-info.yaml file present in the branch folder, i.e bitnami/ASSET/BRANCH/DISTRO/tags-info.yaml.

Subscribe to project updates by watching the bitnami/containers GitHub repo⁠.

⁠Get this image

The recommended way to get the Bitnami Elasticsearch Docker Image is to pull the prebuilt image from the Docker Hub Registry⁠.

docker pull bitnami/elasticsearch:latest

To use a specific version, you can pull a versioned tag. You can view the list of available versions⁠ in the Docker Hub Registry.

docker pull bitnami/elasticsearch:[TAG]

If you wish, you can also build the image yourself by cloning the repository, changing to the directory containing the Dockerfile and executing the docker build command. Remember to replace the APP, VERSION and OPERATING-SYSTEM path placeholders in the example command below with the correct values.

git clone https://github.com/bitnami/containers.git
cd bitnami/APP/VERSION/OPERATING-SYSTEM
docker build -t bitnami/APP:latest .

⁠Persisting your application

If you remove the container all your data will be lost, and the next time you run the image the application will be reinitialized. To avoid this loss of data, you should mount a volume that will persist even after the container is removed.

For persistence you should mount a directory at the /bitnami path. If the mounted directory is empty, it will be initialized on the first run.

docker run \
    -v /path/to/elasticsearch-data-persistence:/bitnami/elasticsearch/data \
    bitnami/elasticsearch:latest

or by making a minor change to the docker-compose.yml⁠ file present in this repository:

elasticsearch:
  ...
  volumes:
    - /path/to/elasticsearch-data-persistence:/bitnami/elasticsearch/data
  ...

It is also possible to use multiple volumes for data persistence by using the ELASTICSEARCH_DATA_DIR_LIST environment variable:

elasticsearch:
  ...
  volumes:
    - /path/to/elasticsearch-data-persistence-1:/elasticsearch/data-1
    - /path/to/elasticsearch-data-persistence-2:/elasticsearch/data-2
  environment:
    - ELASTICSEARCH_DATA_DIR_LIST=/elasticsearch/data-1,/elasticsearch/data-2
  ...

⁠Connecting to other containers

Using Docker container networking⁠, an Elasticsearch server running inside a container can easily be accessed by your application containers.

Containers attached to the same network can communicate with each other using the container name as the hostname.

⁠Using the Command Line

⁠Step 1: Create a network

docker network create app-tier --driver bridge

⁠Step 2: Launch the Elasticsearch server instance

Use the --network app-tier argument to the docker run command to attach the Elasticsearch container to the app-tier network.

docker run -d --name elasticsearch-server \
    --network app-tier \
    bitnami/elasticsearch:latest

⁠Step 3: Launch your application container

docker run -d --name myapp \
    --network app-tier \
    YOUR_APPLICATION_IMAGE

⁠Using a Docker Compose file

When not specified, Docker Compose automatically sets up a new network and attaches all deployed services to that network. However, we will explicitly define a new bridge network named app-tier. In this example we assume that you want to connect to the Elasticsearch server from your own custom application image which is identified in the following snippet by the service name myapp.

version: '2'

networks:
  app-tier:
    driver: bridge

services:
  elasticsearch:
    image: bitnami/elasticsearch:latest
    networks:
      - app-tier
  myapp:
    image: YOUR_APPLICATION_IMAGE
    networks:
      - app-tier

Launch the containers using:

docker-compose up -d

⁠Configuration

⁠Environment variables

⁠Customizable environment variables

⁠Read-only environment variables

Note: the README for this container is longer than the DockerHub length limit of 25000, so it has been trimmed. The full README can be found at https://github.com/bitnami/containers/blob/main/bitnami/elasticsearch/README.md⁠