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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:
docker pull docker.bintray.io/jfrog/artifactory-pro:latest
docker pull docker.bintray.io/jfrog/artifactory-oss:latest
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:
$ docker run --name artifactory -d -p 8081:8081 docker.bintray.io/jfrog/artifactory-pro:latest
$ docker run --name artifactory -d -p 8081:8081 docker.bintray.io/jfrog/artifactory-oss:latest
$ docker run --name artifactory -d -p 8081:8081 docker.bintray.io/jfrog/artifactory-cpp-ce:latest
Setting Java Memory Parameters
To control the memory used by Artifactory, you can pass the environment variable EXTRA_JAVA_OPTIONS.
$ docker run --name artifactory -d -p 8081:8081 -e EXTRA_JAVA_OPTIONS='-Xms512m -Xmx2g -Xss256k -XX:+UseG1GC' docker.bintray.io/jfrog/artifactory-pro:latest
Supported Environment Variables
Artifactory Docker images can be customized using environment variables.
Pass the values as environment variables with your Docker execution command.
docker run -d --name art -e SERVER_XML_ARTIFACTORY_MAX_THREADS=500 -p 8081:8081 docker.bintray.io/jfrog/artifactory-pro:6.6.3
Artifactory will start with maxThreads set to "500" in the Tomcat server.xml.
Java system properties
You can pass Java system properties to the JVM running Artifactory
|Pass Java options to Artifactory JVM|
The database environment variables are documented in Changing the Database page
|Sets the custom Artifactory port.||8081|
|Sets the custom Artifactory maxThreads.||200|
|sets the custom Access maxThreads.||50|
|Adds an extra Artifactory connector config.|
|Adds an extra Access connector config|
|Add another connector to Tomcat. For example to support SSL.|
HA-Specific Environment Variables
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
|Determines whether the node is set as a Primary node or as a Member node in the cluster.||-|
|The value of the 'node.id' parameter in the ha-node.properties file.||node-$(hostname)|
|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)|
|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|
|The Hazelcast membership port of the node.||10002|
|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.|
|The value for the 'artifactory.ha.data.dir' parameter in the ha-node.properties file.||/var/opt/jfrog/artifactory/data|
|The value for the 'artifactory.ha.backup.dir' parameter in the ha-node.properties file.||/var/opt/jfrog/artifactory/backup|
Managing Data Persistence
Previously, the Artifactory Docker container started as user
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
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
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
The files mounted into
$ 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`
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.
From version 6.2, the Artifactory Nginx Docker container starts and runs as 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`
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
$ 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:
For this, you should disable the auto update of the configuration feature using the SKIP_AUTO_UPDATE_CONFIG environment variable
$ docker run --name artifactory-pro-nginx -d -p 8000:80 -p 8443:443 \ -e SKIP_AUTO_UPDATE_CONFIG=true \ -v $CUSTOM_ART_CONF_FILE:/var/opt/jfrog/nginx/conf.d/artifactory.conf docker.bintray.io/jfrog/nginx-artifactory-pro:latest
Running Artifactory Docker with a Custom User/Group ID
Artifactory Docker container can be configured to run with a custom user/group ID by passing the following parameter: "--user $uid:$gid".
The mounted host directory must be writable by the given user id.
The following example will get Artifactory running as user ID 1234 and Group ID 4321.
$ docker run --name artifactory-pro --user 1234:4321 -d -v /var/opt/jfrog/artifactory:/var/opt/jfrog/artifactory -p 8081:8081 docker.bintray.io/jfrog/artifactory-pro:latest
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.
Once the Artifactory container is up and running, you access Artifactory in the usual way by browsing to:
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.
Please refer to the main Troubleshooting page.
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