Table Of Contents
Table Of Contents

Django Channels Layer (Optional)

Last Updated: September 2022

Production installations that use the WebSockets and/or Bokeh Server functionality that comes with Tethys, require the a CHANNEL_LAYER.

Key Concepts

A CHANNEL_LAYER provides a backend where WebSocket messages can be stored and then accessed by different app instances (ASGI processes).

Adding a REDIS CHANNEL_LAYER

Development installations make use of the default InMemoryChannelLayer, however this layer has some limitations in production (See Django Channels documentation). To address these limitations, Django Channels suppports a REDIS CHANNEL LAYER, however other CHANNEL_LAYERS can be configured. The following documentation demonstrates how to configure a REDIS CHANNEL LAYER.

First, install the channels_redis Python package in your Tethys conda environment.

conda activate tethys
pip install channels_redis

Second, add or modify the CHANNEL_LAYERS parameter in the portal_config.yml as follows:

CHANNEL_LAYERS:
  default:
    BACKEND: channels_redis.core.RedisChannelLayer
    CONFIG:
      hosts:
      - [127.0.0.1, 6379]

Finally, start a redis instance. This can easily be done with docker as shown below.

docker run -p 6379:6379 -d redis:5

Once a production CHANNEL_LAYER has been configured, the number of ASGI_PROCESSES can be increased as in the example below:

tethys gen asgi_service --asgi-processes <desired_number_of_instances> --conda-prefix <path_to_tethys_conda_environment>

Warning

Bokeh Server does not currently support the use of multi intance processes. Therefore, it does not work with more than one ASGI process (ASGI_PROCESSES must be equal to 1) (See Bokeh Server documentation).

With Tethys Docker

If using Tethys Docker, the CHANNEL_LAYERS_BACKEND, CHANNEL_LAYERS_CONFIG, and ASGI_PROCESSES parameters can be set on the Dockerfile or docker-compose. Below is an example of how to set these variables in a Dockerfile.

ENV ASGI_PROCESSES 1
ENV CHANNEL_LAYERS_BACKEND "channels_redis.core.RedisChannelLayer"
ENV CHANNEL_LAYERS_CONFIG "\"{\"hosts\": [[127.0.0.1, 6379]]}\""

Finally, make sure that a REDIS Server is running. This can easily be done with a Docker container either by running it directly or adding it to a docker-compose.

Directly:

docker run -p 6379:6379 -d redis:5

With docker-compose: (add the following piece of code at the same level as the db and geoserver containers)

redis:
  image: redis:5
  restart: always
  networks:
    - "internal"
  ports:
    - "6379:6379"