Apache Atlas Docker image

This Apache Atlas is built from the 2.1.0-release source tarball and patched to be run in a Docker container.

Atlas is built with embedded HBase + Solr and it is pre-initialized, so you can use it right after image download without additional steps.

If you want to use external Atlas backends, set them up according to the documentation.

Basic usage

1. Pull the latest release image:

docker pull sburn/apache-atlas

2. Start Apache Atlas in a container exposing Web-UI port 21000:

docker run -d \
    -p 21000:21000 \
    --name atlas \
    sburn/apache-atlas \
    /opt/apache-atlas-2.1.0/bin/atlas_start.py

Please, take into account that the first startup of Atlas may take up to few mins depending on host machine performance before web-interface become available at http://localhost:21000/

Web-UI default credentials: admin / admin

Usage options

Gracefully stop Atlas:

docker exec -ti atlas /opt/apache-atlas-2.1.0/bin/atlas_stop.py

Check Atlas startup script output:

docker logs atlas

Check interactively Atlas application.log (useful at the first run and for debugging during workload):

docker exec -ti atlas tail -f /opt/apache-atlas-2.1.0/logs/application.log

Run the example (this will add sample types and instances along with traits):

docker exec -ti atlas /opt/apache-atlas-2.1.0/bin/quick_start.py

Start Atlas overriding settings by environment variables (to support large number of metadata objects for example):

docker run --detach \
    -e "ATLAS_SERVER_OPTS=-server -XX:SoftRefLRUPolicyMSPerMB=0 \
    -XX:+CMSClassUnloadingEnabled -XX:+UseConcMarkSweepGC \
    -XX:+CMSParallelRemarkEnabled -XX:+PrintTenuringDistribution \
    -XX:+HeapDumpOnOutOfMemoryError -XX:HeapDumpPath=dumps/atlas_server.hprof \
    -Xloggc:logs/gc-worker.log -verbose:gc -XX:+UseGCLogFileRotation \
    -XX:NumberOfGCLogFiles=10 -XX:GCLogFileSize=1m -XX:+PrintGCDetails \
    -XX:+PrintHeapAtGC -XX:+PrintGCTimeStamps" \
    -p 21000:21000 \
    --name atlas \
    sburn/apache-atlas \
    /opt/apache-atlas-2.1.0/bin/atlas_start.py

Start Atlas exposing logs directory on the host to view them directly:

docker run --detach \
    -v ${PWD}/atlas-logs:/opt/apache-atlas-2.1.0/logs \
    -p 21000:21000 \
    --name atlas \
    sburn/apache-atlas \
    /opt/apache-atlas-2.1.0/bin/atlas_start.py

Start Atlas exposing conf directory on the host to place and edit configuration files directly:

docker run --detach \
    -v ${PWD}/pre-conf:/opt/apache-atlas-2.1.0/conf \
    -p 21000:21000 \
    --name atlas \
    sburn/apache-atlas \
    /opt/apache-atlas-2.1.0/bin/atlas_start.py

Start Atlas with data directory mounted on the host to provide its persistency:

docker run --detach \
    -v ${PWD}/data:/opt/apache-atlas-2.1.0/data \
    -p 21000:21000 \
    --name atlas \
    sburn/apache-atlas \
    /opt/apache-atlas-2.1.0/bin/atlas_start.py

Tinkerpop Gremlin support

Image contains build-in extras for those who want to play with Janusgraph, and Atlas artifacts using Apache Tinkerpop Gremlin Console (gremlin CLI).

1. You need Atlas container up and running as shown above.

2. Install gremlin-server and gremlin-console into the container by running included automation script:

docker exec -ti atlas /opt/gremlin/install-gremlin.sh

3. Start gremlin-server in the same container:

docker exec -d atlas /opt/gremlin/start-gremlin-server.sh

4. Finally, run gremlin-console interactively:

docker exec -ti atlas /opt/gremlin/run-gremlin-console.sh

Gremlin-console usage example:

         \,,,/
         (o o)
-----oOOo-(3)-oOOo-----

gremlin>:remote connect tinkerpop.server conf/remote.yaml session
==>Configured localhost/127.0.0.1:8182-[d1b2d9de-da1f-471f-be14-34d8ea769ae8]
gremlin> :remote console
==>All scripts will now be sent to Gremlin Server - [localhost/127.0.0.1:8182]-[d1b2d9de-da1f-471f-be14-34d8ea769ae8] - type ':remote console' to return to local mode
gremlin> g = graph.traversal()
==>graphtraversalsource[standardjanusgraph[hbase:[localhost]], standard]
gremlin> g.V().has('__typeName','hdfs_path').count()

Environment Variables

The following environment variables are available for configuration:

Bug Tracker

Bugs are tracked on GitHub Issues. In case of trouble, please check there to see if your issue has already been reported. If you spotted it first, help us smash it by providing detailed and welcomed feedback.

Maintainer

This image is maintained by Vadim Korchagin

• https://github.com/sburn/docker-apache-atlas