elasticsearch index sink ElasticSearch Index Sink

Provided by: "Apache Software Foundation"

Support Level for this Kamelet is: "Preview"

This sink stores documents into ElasticSearch.

Input data must have JSON format according to the index used.

  • indexId / ce-indexId: as the index ID for Elasticsearch

If the header won’t be set the exchange ID will be used as index.

  • indexName / ce-indexName: as the index Name for Elasticsearch

If the header won’t be set the exchange ID will be used as index name.

Configuration Options

The following table summarizes the configuration options available for the elasticsearch-index-sink Kamelet:

Property Name Description Type Default Example

clusterName *

ElasticSearch Cluster Name

Name of the cluster.

string

"quickstart"

hostAddresses *

Host Addresses

Comma separated list with ip:port formatted remote transport addresses to use.

string

"quickstart-es-http:9200"

enableSSL

Enable SSL

Do we want to connect using SSL?

boolean

true

indexName

Index in ElasticSearch

The name of the index to act against.

string

"data"

password

Password

Password to connect to ElasticSearch.

string

user

Username

Username to connect to ElasticSearch.

string

Fields marked with (*) are mandatory.

Usage

This section summarizes how the elasticsearch-index-sink can be used in various contexts.

Knative Sink

The elasticsearch-index-sink Kamelet can be used as Knative sink by binding it to a Knative object.

elasticsearch-index-sink-binding.yaml
apiVersion: camel.apache.org/v1alpha1
kind: KameletBinding
metadata:
  name: elasticsearch-index-sink-binding
spec:
  source:
    ref:
      kind: InMemoryChannel
      apiVersion: messaging.knative.dev/v1
      name: mychannel
  sink:
    ref:
      kind: Kamelet
      apiVersion: camel.apache.org/v1alpha1
      name: elasticsearch-index-sink
    properties:
      clusterName: "quickstart"
      hostAddresses: "quickstart-es-http:9200"

Make sure you have Camel K installed into the Kubernetes cluster you’re connected to.

Save the elasticsearch-index-sink-binding.yaml file into your hard drive, then configure it according to your needs.

You can run the sink using the following command:

kubectl apply -f elasticsearch-index-sink-binding.yaml

Binding to Knative using the Kamel CLI:

The procedure described above can be simplified into a single execution of the kamel bind command:

kamel bind channel/mychannel elasticsearch-index-sink -p "sink.clusterName=quickstart" -p "sink.hostAddresses=quickstart-es-http:9200"

This will create the KameletBinding under the hood and apply it to the current namespace in the cluster.

Kafka Sink

The elasticsearch-index-sink Kamelet can be used as Kafka sink by binding it to a Kafka topic.

elasticsearch-index-sink-binding.yaml
apiVersion: camel.apache.org/v1alpha1
kind: KameletBinding
metadata:
  name: elasticsearch-index-sink-binding
spec:
  source:
    ref:
      kind: KafkaTopic
      apiVersion: kafka.strimzi.io/v1beta1
      name: my-topic
  sink:
    ref:
      kind: Kamelet
      apiVersion: camel.apache.org/v1alpha1
      name: elasticsearch-index-sink
    properties:
      clusterName: "quickstart"
      hostAddresses: "quickstart-es-http:9200"

Ensure that you’ve installed Strimzi and created a topic named my-topic in the current namespace. Make also sure you have Camel K installed into the Kubernetes cluster you’re connected to.

Save the elasticsearch-index-sink-binding.yaml file into your hard drive, then configure it according to your needs.

You can run the sink using the following command:

kubectl apply -f elasticsearch-index-sink-binding.yaml

Binding to Kafka using the Kamel CLI:

The procedure described above can be simplified into a single execution of the kamel bind command:

kamel bind kafka.strimzi.io/v1beta1:KafkaTopic:my-topic elasticsearch-index-sink -p "sink.clusterName=quickstart" -p "sink.hostAddresses=quickstart-es-http:9200"

This will create the KameletBinding under the hood and apply it to the current namespace in the cluster.