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Overview

Make sure you have reviewed the overall installation process

Before you proceed with the instructions on this page, make sure you have reviewed the whole installation procedure as described in Installing Artifactory.

Artifactory Docker images can be pulled from Bintray and run as a Docker container.

To do this, you need to have Docker client properly installed and configured on your machine. For details about installing and using Docker, please refer to the Docker documentation.

Running with Docker for Artifactory 4.x

Artifactory as a Docker container has been completely redesigned in version 5.0. If you are running previous versions of Artifactory, please refer to Running with Docker in the Artifactory 4.x User Guide

Docker Compose

The way we recommend running Artifactory on Docker is to orchestrate your setup using Docker Compose. This will ensure you have all the required services specified in a single YAML file with pre-configured parameters.

 


Using Docker Compose

To setup an Artifactory environment made of multiple containers (for example, a database, an NGINX load balancer and Artifactory each running in a different container), you can use docker-compose.

For more details on Docker Compose, please refer to the  Docker documentation.

Artifactory OSSArtifactory Pro and Artifactory HA can all be run using Docker Compose. For detailed documentation and sample Compose files showing a variety of ways to setup Artifactory with Docker Compose, please refer to the  artifactory-docker-examples repository on GitHub.


Artifactory on Docker

Running Artifactory as a container is simple and straightforward, and involves the following basic steps:

Since the Artifactory instance running in a Docker container is mutable, all data and configuration files will be lost once the container is removed. If you want your data to persist (for example when upgrading to a new version), you should also follow the next step.

Pulling the Artifactory Docker Image

The Artifactory Docker image may be pulled from Bintray by executing the corresponding Docker command below depending on whether you are pulling Artifactory OSS or Artifactory Pro:

Pulling the Artifactory Pro Docker Image
docker pull docker.bintray.io/jfrog/artifactory-pro:latest

or

Pulling the Artifactory OSS Docker Image
docker pull docker.bintray.io/jfrog/artifactory-oss:latest

or

Pulling the Artifactory CE Docker Image
docker pull docker.bintray.io/jfrog/artifactory-cpp-ce

Running an Artifactory Container

You can list the Docker images you have downloaded using the docker images command, which should display something like the following output:

$ docker images
 
REPOSITORY                                 TAG                 IMAGE ID            CREATED             SIZE
docker.bintray.io/jfrog/artifactory-pro    latest 		       da70b82904e7        2 days ago          861.5 MB
...

To start an Artifactory container, use the corresponding command below according to whether you are running Artifactory Pro or Artifactory OSS:

Running Artifactory Pro in a container
$ docker run --name artifactory -d -p 8081:8081 docker.bintray.io/jfrog/artifactory-pro:latest    

or

Running Artifactory OSS in a container
$ docker run --name artifactory -d -p 8081:8081 docker.bintray.io/jfrog/artifactory-oss:latest    

or

Running Artifactory CE in a container
$ docker run --name artifactory -d -p 8081:8081 docker.bintray.io/jfrog/artifactory-cpp-ce:latest    

Passing in Java arguments

When running an Artifactory Docker container, you can pass in Java arguments using the -e EXTRA_JAVA_OPTIONS flag. For example, to specify a maximum memory allocation of 8 GB, you could run:

$ docker run --name artifactory -d -p 8081:8081 -e EXTRA_JAVA_OPTIONS=-Xmx8g docker.bintray.io/jfrog/artifactory-pro:latest   

HA-Specific Environment Variables

Passing Environment Variables to the entrypoint script

The entrypoint script of the Artifactory Pro Docker image accepts various environment variables. These are documented in the table below, and can be used to manipulate various HA-specific settings. Setting the following variables is particularly useful when using an orchestration tool such as Kubernetes or Docker Compose to spin up new Artifactory nodes. For more details on configuring the ha-node.properties please refer to Setting Up Your Storage Configuration.

Variable

Functionality

Default value
$HA_IS_PRIMARY
Determines whether the node is set as a Primary node or as a Member node in the cluster.-
$HA_NODE_ID
The value of the 'node.id' parameter in the ha-node.properties file.node-$(hostname)
$HA_HOST_IP
The IP of the container. This variable is used to compose a full context.url, only when the $HA_CONTEXT_URL variable is not set. Determined by running 'hostname -i'.$(hostname -i)
$HA_CONTEXT_URL
The value of the 'context.url' parameter in the generated ha-node.properties file. This is the node URL exposed to cluster members. If not set, the $HA_HOST_IP variable will be used to derive the full context.url.http://$HA_HOST_IP:8081/artifactory
$HA_MEMBERSHIP_PORT
The Hazelcast membership port of the node.10002
$ART_PRIMARY_BASE_URL
Set this on a member node only if the nodes are not going to be a part of the same docker network, so that they're not reachable to each other by the container name, or if you the name of the primary node container is not "artifactory-node1". The entrypoint script would send an HTTP request to the primary node using this URL to wait for the Primary node to start up.http://artifactory-node1:8081/artifactory
$HA_DATA_DIR
The value for the 'artifactory.ha.data.dir' parameter in the ha-node.properties file./var/opt/jfrog/artifactory/data
$HA_BACKUP_DIR
The value for the 'artifactory.ha.backup.dir' parameter in the ha-node.properties file./var/opt/jfrog/artifactory/backup

 


Managing Data Persistence

The "artifactory" user

Previously, the Artifactory Docker container started as user root, but was run by user artifactory. From version 6.2, user artifactory is used to both start and run the Docker container. Note that:

  • the artifactory user default ID is 1030
  • the artifactory user must have write privileges to any persistent storage mounted on the Artifactory container

For your data and configuration to remain once the Artifactory Docker container is removed, you need to store them on an external volume mounted to the Docker container. There are two ways to do this:

  • Using Host Directories
  • Using a Docker Named Volume

Using Host Directories

The external volume is a directory in your host's file system (such as /var/opt/jfrog/artifactory). When you pass this to the docker run command, the Artifactory process will use it to read configuration and store its data.

To mount the above example, you would use the following command:

$ docker run --name artifactory-pro -d -v /var/opt/jfrog/artifactory:/var/opt/jfrog/artifactory -p 8081:8081 docker.bintray.io/jfrog/artifactory-pro:latest

This mounts the /var/opt/jfrog/artifactory directory on your host machine to the container's /var/opt/jfrog/artifactory and will then be used by Artifactory for configuration and data.

Using a Docker Named Volume

In this case, you create a docker named volume and pass it to the container. By default, the named volume is a local directory under /var/lib/docker/volumes/<name>, but can be set to work with other locations. For more details, please refer to the Docker documentation for  Docker Volumes.

The example below creates a Docker named volume called artifactory_data and mounts it to the Artifactory container under /var/opt/jfrog/artifactory:

$ docker volume create --name artifactory5_data
$ docker run --name artifactory-pro -d -v artifactory5_data:/var/opt/jfrog/artifactory -p 8081:8081 docker.bintray.io/jfrog/artifactory-pro:latest

In this case, even if the container is stopped and removed, the volume persists and can be attached to a new running container using the above docker run command. 


Extra Configuration Directory

You can mount extra configuration files, such as binarystore.xml, artifactory.lic or db.properties, that are needed for your Artifactory installation.
To do this, you need to mount the file or directory on the host into the Artifactory Docker container's /artifactory_extra_conf folder. When the Artifactory Docker container starts, it will copy the files from /artifactory_extra_conf to ARTIFACTORY_HOME/etc (usually /var/opt/jfrog/artifactory/etc).

 

The files mounted into /artifactory_extra_conf will be copied over to ARTIFACTORY_HOME/etc every time the container starts, so you should avoid modifying the files in ARTIFACTORY_HOME/etc.

 

Example 1: Passing in a custom db.properties file

 

$ docker run --name artifactory-pro -d -v /var/opt/jfrog/artifactory:/var/opt/jfrog/artifactory -v /conf/db.properties:/artifactory_extra_conf/db.properties -p 8081:8081 docker.bintray.io/jfrog/artifactory-pro:latest

 

Example 2: Passing in a custom binarystore.xml

 

$ docker run --name artifactory-pro -d -v /var/opt/jfrog/artifactory:/var/opt/jfrog/artifactory -v /conf/binarystore.xml:/artifactory_extra_conf/binarystore.xml -p 8081:8081 docker.bintray.io/jfrog/artifactory-pro:latest

 


Artifactory NGINX Docker image

The Artifactory Docker image can be run with an Nginx Docker image that can be used to manage SSL, reverse proxy and other web server features. For configuration details, please refer to Configuring NGINX.

A custom Docker image that is already setup for Artifactory with NGINX and is available at: `docker.bintray.io/jfrog/nginx-artifactory-pro`

Docker Compose

We recommend running this container along with the Artifactory container using an orchestration tool such as docker-compose, which allows easy networking and linking of the two containers. See artifactory docker-compose examples in JFrog's artifactory-docker-examples repository on GitHub.

Artifactory NGINX Docker user

From version 6.2, the Artifactory Nginx Docker container starts and runs as user nginx. Note that:

  • the nginx user ID is 104; the group ID is 107
  • any mounted volume must be writable by the nginx user

 

To run the image locally, use:

$ docker run --name artifactory-pro-nginx -d -p 8000:80 -p 8443:443 docker.bintray.io/jfrog/nginx-artifactory-pro:latest

This will start an NGINX instance with default settings

  • NGINX listening on ports 80 and 443
  • Self signed SSL key and certificate
  • Forwarding requests to host `artifactory`

Custom Configurations

We recommend customizing the Artifactory NGINX container to your needs as described below.

Using Your Own SSL Key and Certificate

  • Place your SSL key and certificate in a directory on your host
  • Mount the directory into the Artifactory NGINX container to /var/opt/jfrog/nginx/ssl

    $ docker run --name artifactory-pro-nginx -d -p 8000:80 -p 8443:443 -v $HOST_SSL_PATH:/var/opt/jfrog/nginx/ssl docker.bintray.io/jfrog/nginx-artifactory-pro:latest

Using a Custom Artifactory Configuration File

To customize the artifactory.conf file used by the NGINX container, create your own artifactory.conf file and mount it into the container to: /var/opt/jfrog/nginx/conf.d/artifactory.conf.

$ docker run --name artifactory-pro-nginx -d -p 8000:80 -p 8443:443 -v $CUSTOM_ART_CONF_FILE:/var/opt/jfrog/nginx/conf.d/artifactory.conf docker.bintray.io/jfrog/nginx-artifactory-pro:latest

 


Upgrading Artifactory

For details on how to upgrade Artifactory running in a Docker container, please refer to Running in a Docker Container in the Upgrading Artifactory page.  


Running Artifactory With a Different Database

By default, Artifactory runs with an embedded Derby Database that comes built-in, however, Artifactory supports additional databases. To switch to one of the other supported databases, please refer to Changing the Database


Building Artifactory OSS From Sources

The Artifactory OSS Docker image sources are available for download allowing you to build the image yourself. For details, please refer to Building Artifactory OSS


Accessing Artifactory

Once the Artifactory container is up and running, you access Artifactory in the usual way by browsing to: 

http://SERVER_DOMAIN:8081/artifactory

 


Docker for Windows limitation

There is a known limitation with running with Docker on Windows.

The limitation is described in the following JIRA issue. There is an optional workaround there, but it's not recommended for production deployments.


Troubleshooting Docker

Please refer to the main Troubleshooting page. 

 


Watch the Screencast

 

 

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