Currently is not easy to use Elastic Search in Azure Container instance, this is a docker image prepared for that, but only for testing purposes, you should consider other alternatives for production environments.

The image can be downloaded directly from docker hub.

Here is an example of how you can use this image with terraform:

resource "azurerm_container_group" "elasticSearchServer" {
  name                = "aci-elastic-dev-001"
  #Change to the correct location here:
  location            = azurerm_resource_group.rgServices.location
  #Change the resource group here:
  resource_group_name = azurerm_resource_group.rgServices.name
  ip_address_type     = "public"
  dns_name_label      = "qvaCar-elastic-dev"
  os_type             = "Linux"

  container {
    name   = "elastic-server"
    image  = "josecdom94/es-aci-dev:7.9.2"
    cpu    = "0.5"
    memory = "1.0"
    environment_variables = {     
      ES_JAVA_OPTS     = "-Xms512m -Xmx512m"
    }

    ports {
      port     = "9200"
      protocol = "TCP"
    }
  }
}

Although it doesn’t make much sense to use docker locally since is not much different from the original elastic search, you can still use docker locally:

docker run -dt --name elastic-search -p 9200:9200 josecdom94/es-aci-dev:7.9.2

After a while you can check that the status of the cluster is green by typing this URL in the browser http://localhost:9200/_cluster/health and get something similar to this:

{
    "cluster_name": "docker-cluster",
    "status": "green",
    "timed_out": false,
    "number_of_nodes": 1,
    "number_of_data_nodes": 1,
    "active_primary_shards": 0,
    "active_shards": 0,
    "relocating_shards": 0,
    "initializing_shards": 0,
    "unassigned_shards": 0,
    "delayed_unassigned_shards": 0,
    "number_of_pending_tasks": 0,
    "number_of_in_flight_fetch": 0,
    "task_max_waiting_in_queue_millis": 0,
    "active_shards_percent_as_number": 100.0
}

The magic is just setting an environment variable discovery.type=single-node before starting the cluster, but bear in mind that this is a single node cluster and is not recommended for production environments. You can check the docker file for more details.