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Enable Shared Elasticsearch

Grove supports deploying an ElasticSearch cluster that is shared between all instances.

The Open edX platform uses ElasticSearch (ES) in multiple ways, when doing a search for courses, when searching for forum posts, for course discovery, etc. For each deployment, tutor adds an ES pod which uses about 1.3GB of RAM. For operators that are running multiple instances, this isn't ideal as you'll be dedicating a large chunk of memory to idle processes.

How it works

ElasticSearch indices are unique and the edx-platform assumes that indices are dedicate the currently running instance. This means that in order to run multiple instances, we need to make sure there aren't collisions with the index names.

Grove does this by modifying the underlying platforms to consider prefixed indices. For example an instance will assume it's writing to courses index but the underlying code will rout the request instead to {instance-name}-courses instead.

Turning it on

To enable the feature, add to your cluster.yml.

TF_VAR_enable_shared_elasticsearch: "true"

And apply the changes with terraform.

cd control
./tf plan
./tf apply

For each instance you would like to use the cluster, add the below block the config.yml. The ELASTIC_* variables will be overridden by Grove:

ELASTICSEARCH_HOST: set-via-environment
ELASTICSEARCH_HTTP_AUTH: set-via-environment
ELASTICSEARCH_CA_CERT_PEM: set-via-environment


Grove exposes a shared_elasticsearch configuration hash which has the following keys:

  • heap_size: Defaulting to 2g, this is the minimum and maximum heap size that will be used for each node in the cluster.
  • replicas: Defaults to 2. The number of replicas to create for the cluster. Do not set this number higher than your number of nodes as each pod is meant to run on a dedicated node.
  • search_queue_size: Defaults to 5000. This number determines the throughput (and resource usage) of your cluster. It should be increased only if there's more CPU available.
  • cpu_limit: Defaults to 2000m.
  • memory_limit: Defaults to 4Gi.

Example configuration in cluster.yml:

TF_VAR_elasticsearch_config: |
    heap_size: "5g"
    memory_limit: "10Gi"