Connect Apache Kafka® to OpenSearch® with Terraform#

This example shows how to use a Kafka® Connector to take data from Apache Kafka® and ingest it into OpenSearch® using Apache Kafka Connect. As a use case, the data here is application logs going onto a Kafka topic, and being put into OpenSearch for short term storage and easy inspection, if needed. Aiven has a concept of service integrations to manage the relationships between components. Aiven Terraform Provider has a specific resource type in Terraform for service integration.

Before looking at the Terraform script, let’s visually realize how the services will be connected:

flowchart LR kafka[Kafka] sikafka{{Service Integration}} kconn[Kafka Connect] kcopensearch{{Kafka Connector:<br /> OpenSearch Sink}} opensearch[OpenSearch] kafka --> sikafka --> kconn --> kcopensearch --> opensearch

In the above diagram, KafkaConnect is the service that you create for connecting Kafka with external systems. The Kafka Connectors, OpenSearch Sink Connector for example, are ready-to-use components to send/receive data to common data sources/sinks.

Describe the setup#

Be sure to check out the getting started guide to learn about the common files required to execute the following recipe. For example, you’ll need to declare the variables for project_name and api_token.

Expand to check out the relevant common files needed for this recipe.

Navigate to a new folder and add the following files.

  1. Add the following to a new provider.tf file:

terraform {
  required_providers {
    aiven = {
      source  = "aiven/aiven"
      version = "~> 3.10.0"
    }
  }
}

provider "aiven" {
  api_token = var.aiven_api_token
}

You can also set the environment variable TF_VAR_aiven_api_token for the api_token property. With this, you don’t need to pass the -var-file flag when executing Terraform commands.

  1. To avoid including sensitive information in source control, the variables are defined here in the variables.tf file. You can then use a *.tfvars file with the actual values so that Terraform receives the values during runtime, and exclude it.

The variables.tf file defines the API token, the project name to use, and the prefix for the service name:

variable "aiven_api_token" {
  description = "Aiven console API token"
  type        = string
}

variable "project_name" {
  description = "Aiven console project name"
  type        = string
}

  1. The var-values.tfvars file holds the actual values and is passed to Terraform using the -var-file= flag.

var-values.tfvars file:

aiven_api_token     = "<YOUR-AIVEN-AUTHENTICATION-TOKEN-GOES-HERE>"
project_name        = "<YOUR-AIVEN-CONSOLE-PROJECT-NAME-GOES-HERE>"

Here is the sample Terraform file to stand-up and connect all the services. Keep in mind that some parameters and configurations will vary for your case. A reference to the Kafka and OpenSearch configurations are added at the end of this document.

services.tf file:

# Kafka service
resource "aiven_kafka" "application-logs" {
  project                 = var.project_name
  cloud_name              = "google-northamerica-northeast1"
  plan                    = "business-4"
  service_name            = "kafka-application-logs"
  maintenance_window_dow  = "monday"
  maintenance_window_time = "10:00:00"
  kafka_user_config {
    kafka_connect = true
    kafka_rest    = true
    kafka_version = "3.2"
    kafka {
      group_max_session_timeout_ms = 70000
      log_retention_bytes          = 1000000000
    }
  }
}

# Kafka topic
resource "aiven_kafka_topic" "topic-logs-app-1" {
  project      = var.project_name
  service_name = aiven_kafka.application-logs.service_name
  topic_name   = "logs-app-1"
  partitions   = 3
  replication  = 2
}

# Kafka connect service
resource "aiven_kafka_connect" "logs-connector" {
  project                 = var.project_name
  cloud_name              = "google-northamerica-northeast1"
  plan                    = "business-4"
  service_name            = "kafka-connect-logs-connector"
  maintenance_window_dow  = "monday"
  maintenance_window_time = "10:00:00"
  kafka_connect_user_config {
    kafka_connect {
      consumer_isolation_level = "read_committed"
    }
    public_access {
      kafka_connect = true
    }
  }
}

# Kafka connect service integration
resource "aiven_service_integration" "kafka-to-logs-connector" {
  project                  = var.project_name
  integration_type         = "kafka_connect"
  source_service_name      = aiven_kafka.application-logs.service_name
  destination_service_name = aiven_kafka_connect.logs-connector.service_name
  kafka_connect_user_config {
    kafka_connect {
      group_id             = "connect"
      status_storage_topic = "__connect_status"
      offset_storage_topic = "__connect_offsets"
    }
  }
}

# Kafka connector
resource "aiven_kafka_connector" "kafka-os-con1" {
  project        = var.project_name
  service_name   = aiven_kafka.application-logs.service_name
  connector_name = "kafka-os-con1"
  config = {
    "topics"                         = aiven_kafka_topic.topic-logs-app-1.topic_name
    "connector.class"                = "io.aiven.kafka.connect.opensearch.OpensearchSinkConnector"
    "type.name"                      = "os-connector"
    "name"                           = "kafka-os-con1"
    "connection.url"                 = "https://${aiven_opensearch.os-service1.service_host}:${aiven_opensearch.os-service1.service_port}"
    "connection.username"            = aiven_opensearch.os-service1.service_username
    "connection.password"            = aiven_opensearch.os-service1.service_password
    "key.converter"                  = "org.apache.kafka.connect.storage.StringConverter"
    "value.converter"                = "org.apache.kafka.connect.json.JsonConverter"
    "tasks.max"                      = 1
    "schema.ignore"                  = true
    "value.converter.schemas.enable" = false
  }
}

# Opensearch service
resource "aiven_opensearch" "os-service1" {
  project                 = var.project_name
  cloud_name              = "google-northamerica-northeast1"
  plan                    = "business-4"
  service_name            = "os-service1"
  maintenance_window_dow  = "monday"
  maintenance_window_time = "10:00:00"
  opensearch_user_config {
    opensearch_version = "2"
  }
}
Expand to check out how to execute the Terraform files.

The init command performs several different initialization steps in order to prepare the current working directory for use with Terraform. In our case, this command automatically finds, downloads, and installs the necessary Aiven Terraform provider plugins.

terraform init

The plan command creates an execution plan and shows you the resources that will be created (or modified) for you. This command does not actually create any resource; this is more like a preview.

terraform plan -var-file=var-values.tfvars

If you’re satisfied with the output of terraform plan, go ahead and run the terraform apply command which actually does the task or creating (or modifying) your infrastructure resources.

terraform apply -var-file=var-values.tfvars

This file creates three Aiven services - a Kafka service, a Kafka Connect service, and an OpenSearch service. Two service integrations among these three services and a Kafka topic within the Kafka service will also be created from this Terraform file. To validate, produce some messages on the Kafka topic and you should be seeing those appear on OpenSearch indices.

More resources#

You might find these related resources useful too: