Only requirement for production deployment is an existing PostgresSQL database.

ella primarily uses Docker for deployment. Not using Docker is also possible, but is not documented.

Build image

First build the docker image as follows:

docker build -t {image_name} .

where {image_name} is what you want to name the image.

Mount points

The production container defines a few mount points. If you're not using containers for deployment, you can skip this section.

Destination Description
/logs/ Destination for the log files
/data/ Data files
/socket/ Location for unix sockets (optional)
/tmp/ Location for temporary files (optional)

Data directory

The recommended approach is to have one data directory for ella, which contains imported analyses, attachments and IGV data. This directory is outside of the container, and can be mounted in to /data.

One possible structure is this:

  attachments/ - Storage of user attachments
    incoming/  - New analyses for analysis watcher
    imported/  - Analyses that are imported
  igv-data/    - IGV resources, global and usergroup tracks.
  fixtures/    - Any kind of data that is imported into database. Examples:

Setup environment

There are a few environment variables that should be set.

Variable Description Values
DB_URL URI to PostgreSQL database. ex. postgresql://dbuser@host/dbname
PORT Listen port for nginx. Default: 3114
ANALYSES_PATH Path to imported analyses. path, ex. /data/analyses/imported
ANALYSES_INCOMING Path to incoming analyses. Used by analysis watcher to import new analyses path, ex. /data/analyses/incoming
IGV_DATA Path to IGV resources. path, ex. /data/igv_data
ATTACHMENT_STORAGE Path to where to store attachments. path, ex. /data/attachments/
ANNOTATION_SERVICE_URL URL to anno service. URL, ex. "http://localhost:6000"
OFFLINE_MODE Whether used in offline environment. Adjusts whether links should be copied to clipboard. TRUE/FALSE (default: FALSE )

Start container

We can launch a new container like the following

docker run \
  --name {container_name} \
  -p 80:80 \
  -v /local/logs/path:/logs \
  -v /local/logs/path:/logs \
  -e DB_URL={db_url} \
  -e ANALYSES_PATH=/data/analyses/imported \
  -e ANALYSES_INCOMING=/data/analyses/incoming \
  -e ATTACHMENT_STORAGE=/data/attachments \
  -e IGV_DATA=/data/igv_data \
  -e ANNOTATION_SERVICE_URL=http://localhost:6000 \

Behind the scenes

Internally, the supervisord will spin up several services:

  • nginx - acting as reverse proxy and serving static files
  • gunicorn - launching several API workers
  • analyses-watcher - handles watching for and importing new analyses
  • polling - watches for and handles new import jobs


To spin up a new demo instance, run the following: make demo

Inside the container an environment variable VIRTUAL_HOST will be set equal to the value DEMO_NAME for use with the nginx-proxy docker container.

If you want to bind the demo directly to the local host you can instead run it manually like this:

docker run -d \
	--name {container_name} \
	-p 80:80 \
	{image_name} \
	supervisord -c /ella/ops/demo/supervisor.cfg

docker exec {container_name} make dbreset

The demo container runs an internal PostgreSQL server for easier deployment.

Last Updated: 12/17/2018, 1:52:14 PM