• Quick Reference
• Prerequisites
• Creating a DataStax Enterprise Container
  • Container examples
  • Managing the configuration
  • Volumes and Data
• Running DSE Commands and Viewing Logs
• Creating an OpsCenter Container
• Creating a Studio Container
• Building
• Licensing

The DataStax base image now uses OpenJDK. Previously we were building with Oracle JDK. Starting with the below image versions and moving forward, prebuilt images on Docker Hub will include OpenJDK. If you would like to use OpenJDK with a version that was built with Oracle JDK we have built new images including OpenJDK with a tag of version-openjdk8

• DSE 6.0.2 and 5.1.11
• OpsCenter 6.5.1 and 6.1.7
• Studio 6.0.1

DataStax Docker Docs, DataStax Slack, Github

Full documentation and advanced tutorials are located within DataStax Academy. Docker Compose examples for deploying DataStax Enterprise with Opscenter and Studio are available on our Github page

https://github.com/datastax/docker-images/issues

DataStax

Built on the best distribution of Apache Cassandra™, DataStax Enterprise is the always-on database designed to allow you to effortlessly build and scale your apps, integrating graph, search, analytics, administration, developer tooling, and monitoring into a single unified platform. We power your apps' real-time moments so you can create instant insights and powerful customer experiences.

• Basic understanding of Docker images and containers.

• Docker installed on your local system, see Docker Installation Instructions.

• When building custom images from the DataStax github repository, a DataStax Academy account.

• When using Docker for Mac or Docker for Windows, the default resources allocated to the linux VM running docker are 2GB RAM and 2 CPU's. Make sure to adjust these resources to meet the resource requirements for the containers you will be running. More information can be found here on adjusting the resources allocated to docker.

Docker for mac

Docker for windows

Use the options described in this section to create DataStax Enterprise server containers.

By default, the DSE server image runs in Cassandra-only mode.. To run with advanced DSE functionality, add the option that enables any combination of search, analytics, and graph to the end of the docker run command.

Combine startup options to run more than one feature. For more examples, see Starting DataStax Enterprise as a stand-alone process .

docker run -e DS_LICENSE=accept --name my-dse -d datastax/dse-server

docker run -e DS_LICENSE=accept --name my-dse -d datastax/dse-server -g

docker run -e DS_LICENSE=accept --name my-dse -d datastax/dse-server -k

docker run -e DS_LICENSE=accept --name my-dse -d datastax/dse-server -s

docker run -e DS_LICENSE=accept --name my-dse -d datastax/dse-server -s -k -g

Manage the DSE configuration using one of the following options:

• DSE configuration volume For configuration management, we’re providing a simple mechanism to let you provide custom configuration file(s) without customizing the containers or over using host volumes. You can add any of the approved config files to a single mounted host volume and we’ll handle the hard work of mapping them within the container.

• DSE environment variables that change the configuration at runtime.

  • Environment variables will trump any other settings meaning that if you set a custom snitch in cassandra.yaml and then a different one with an environment variable, the environment variable setting will be used.
  • DSE uses the default values defined for environment variables unless they are explicitly set at run time or unless overridden with the DSE_AUTO_CONF_OFF environment variable.

• Docker file/directory volume mounts

• Docker overlay file system

• DSE uses the default values defined for the environment variables unless explicitly set at run time.

• NOTE When using memory resource contraints, you must must set JVM heap size using the environment variable JVM_EXTRA_OPTS or custom cassandra-env.sh or DSE running inside the container due to java not honoring resource limits set for the container. Java utilizes the resources (memory and CPU) of the host. Otherwise DSE will set the heap to 1/4 of the physical ram of the docker host.

To use this feature:

1. Create a directory on your local host.
2. Download and customize the configuration files you want to use from the config-templates page.
3. Add the custom configuration files to the host directory you created.
   • The file name must match a corresponding configuration file in the image and include all the required values, for example cassandra.yaml, dse.yaml.
4. Mount the exposed Volume /config to the local directory.
5. Start the container. For example to start a database node:

docker run -e DS_LICENSE=accept --name my-dse  -v /dse/config:/config -d datastax/dse-server

Note When you make changes to or add config files to the /config volume, you will need to restart your container with docker restart container_name for DSE to pickup the changes. Restarting the container will restart DSE.

Configure the DSE image by setting environment variables when the container is created using the docker run command -e flag.

To persist data, pre-create directories on the local host and map the directory to the corresponding volume using the docker run -v flag.

NOTE: If the volumes are not mounted from the local host, all data is lost when the container is removed.

DSE images expose the following volumes.

• For DataStax Enterprise Transactional, Search, Graph, and Analytics workloads:

  • /var/lib/cassandra: Data from Cassandra
  • /var/lib/spark: Data from DSE Analytics w/ Spark
  • /var/lib/dsefs: Data from DSEFS
  • /var/log/cassandra: Logs from Cassandra
  • /var/log/spark: Logs from Spark
  • /config: Directory to add custom config files for the container to pickup.

• For OpsCenter: /var/lib/opscenter

• For Studio: /var/lib/datastax-studio

docker run -v <local_directory>:<container_volume>

See Docker docs > Use volumes for more information.

Use the docker exec -it <container_name> command to specific commands.

docker exec -it my-dse nodetool status

If the container is running in the background (using the -d), use the following command to open an interactive bash shell to run DSE commands.

docker exec -it <container_name> bash

To exit the shell without stopping the container type exit.

Use the following command to open cqlsh.

docker exec -it <container_name> cqlsh

You can view the DSE logs using the Docker log command. For example:

docker logs my-dse

Follow these steps to create an Opscenter container and a connected DataStax Enterprise server container on the same Docker host.

To create and connect the containers:

1. First create an OpsCenter container.

   • docker run -e DS_LICENSE=accept -d -p 8888:8888 --name my-opscenter datastax/dse-opscenter

   • See OpsCenter Docker run options for additional options that persist data or manage configuration.

2. Create a DataStax Enterprise (DSE) server container that is linked to the OpsCenter container.

   • docker run -e DS_LICENSE=accept --link my-opscenter:opscenter --name my-dse -d datastax/dse-server

3. Get the DSE container IP address:

   • On the host running the DSE container run

   • docker inspect my-dse | grep '"IPAddress":'

4. Open a browser and go to http://DOCKER_HOST_IP:8888.

5. Click Manage existing cluster.

6. In host name, enter the DSE IP address.

7. Click Install agents manually. Note that the agent is already installed on the DSE image; no installation is required.

OpsCenter is ready to use with DSE. See the OpsCenter User Guide for detailed usage and configuration instructions.

Follow these steps to create a DataStax Studio container that is connected to a DataStax Enterprise (DSE) server container on the same Docker host.

To create and connect the containers:

1. Create a DataStax Studio container:

docker run -e DS_LICENSE=accept --link my-dse --name my-studio -p 9091:9091 -d datastax/dse-studio

2. Open a browser and go to http://DOCKER_HOST_IP:9091

3. Create the new connection using my-dse as the hostname, see DataStax Studio User Guide > Creating a new connection for further instructions.

Studio is ready to use with DSE. See DataStax Studio User Guide for detailed usage and configuration instructions.

The code in this repository will build the DSE, Opscenter and Studio Docker images. To get started, clone this repo and modify for your requirements.

This repo uses Gradle to build the images.

By default, Gradle will download DataStax tarballs from DataStax Academy. Therefore you need to provide your credentials either via the command line, or in gradle.properties file located in the project root.

DataStax uses two separate Dockerfiles to build the individual images, a base for the OS and individual Dockerfiles for (server, opscenter, studio).

If you would like to customize the OS, install additional packages etc, you would modify the base Dockerfile.

If you would like to customize DSE, Opscenter or Studio you would modify their corresponding Dockerfile. For example: if you wanted to build DSE 5.1.10 with datastax-agent 6.1.4, you would modify the server 5.1 Dockerfile with

ARG VERSION=5.1.10
ARG DSE_AGENT_VERSION=6.1.4

To build specific versions of OpsCenter and Studio, you would modify ARG VERSION= in their corresponding Dockerfile.

Currently you have to build all 3 images

To build the images from your customized Dockerfile(s) run the following command specifying the Version branch for each image: For example to build DSE 5.1.10 with OpsCenter 6.1.4 and Studio 2.0 you would run the following adding your DataStax Academy Credentials

./gradlew buildServerImage -PserverVersion=5.1 -PopscenterVersion=6.1 -PstudioVersion=2.0 buildImages -PdownloadUsername=<your_DataStax_Acedemy_username> -PdownloadPassword=<your_DataStax_Acedemy_passwd>

Run ./gradlew tasks to get the list of all available tasks.

Head over to DataStax Academy for advanced documentation including

• Apache Cassandra™/Datastax configuration management
• Using environment variables
• Persisting data
• Exposing public ports
• Volumes and data directories
• Docker Compose examples to spin up connected clusters of DataStax Enterprise, Studio, and Opscenter (also on github)
• Step-by-step tutorials and examples
• How to build applications using Apache Cassandra™/ DataStax

• DataStax License Terms
• OpsCenter License Terms
• DataStax License Terms