Adding ClickHouse/Hydrolix tables to existing Kibana/Elasticsearch ecosystem

WARNING

If you are using Hydrolix as your data source please follow to Adding Hydrolix tables to existing Kibana/Elasticsearch ecosystem subsection of this document for more information. If you plan to use ClickHouse, continue below.

In this scenario, user already has data in Elasticsearch/OpenSearch indices - let's assume index1, index2 and index3. Additionally, they have a ClickHouse instance with tables named siem and logs.

Quesma is configured to expose both ClickHouse tables via its Elasticsearch API, making them visible in Kibana/OpenSearchDashboards (OSD) as Elasticsearch indices. Quesma also supports ingesting data via Elasticsearch-compatible API (e.g. _bulk/_doc endpoint) to:

• Both ClickHouse tables, by translating incoming Elasticsearch POST requests targeting siem/logs indices to ClickHouse INSERT queries.
• Existing Elasticsearch/OpenSearch indices (index1, index2 and index3) by relaying traffic directly to the original Elasticsearch/OpenSearch instance.

If you are interesed in more details about ingesting your data, refer to Ingest page.

Quesma installation

Prerequisites:

• ClickHouse is running.
• Kibana/OSD and Elasticsearch/OpenSearch are running.
• Docker is installed, at least 20.10 version.

Installation steps:

1. Create a configuration file named quesma.yaml with the following content, make sure to replace placeholders (#PLACE_YOUR*) with actual values.

   licenseKey: #PLACE_YOUR_LICENSE_KEY_HERE 
   # license key is required for backend connector of `clickhouse` type, 
   # please contact Quesma support (support@quesma.com) to obtain yours
   # in case you are using self-hosted clickhouse instance, you can use `clickhouse-os` backend connector and continue without the license key  
   frontendConnectors:
     - name: elastic-query
       type: elasticsearch-fe-query
       config:
         listenPort: 8080
     - name: elastic-ingest
       type: elasticsearch-fe-ingest
       config:
         listenPort: 8080
   backendConnectors:
     - name: elasticsearch-instance
       type: elasticsearch
       config:
         url: #PLACE_YOUR_ELASTICSEARCH_URL_HERE
         user: #PLACE_YOUR_ELASTICSEARCH_USERNAME_HERE
         password: #PLACE_YOUR_ELASTICSEARCH_PASSWORD_HERE
     - name: clickhouse-instance
       type: clickhouse-os
       #type: clickhouse # use for ClickHouse cloud service only
       config:
         url: #PLACE_YOUR_CLICKHOUSE_URL_HERE
         user: #PLACE_YOUR_CLICKHOUSE_USER_HERE
         password: #PLACE_YOUR_CLICKHOUSE_PASSWORD_HERE
         database: #PLACE_YOUR_CLICKHOUSE_DATABASE_NAME_HERE
   processors:
     - name: query-processor
       type: quesma-v1-processor-query
       config:
         indexes:  # the list below is just an example, 
           siem:   # make sure to replace them with your actual table or index names
             target: [ clickhouse-instance ]
           logs:
             target: [ clickhouse-instance ]
           index1:
             target: [ elasticsearch-instance ]
           index2:
             target: [ elasticsearch-instance ]
           index3:
             target: [ elasticsearch-instance ]
           '*':       # DO NOT remove, always required
             target: [ elasticsearch-instance ]     
     - name: ingest-processor
       type: quesma-v1-processor-ingest
       config:
         indexes:  # the list below is just an example, 
           siem:   # make sure to replace them with your actual table or index names
             target: [ clickhouse-instance ]
           logs:
             target: [ clickhouse-instance ]
           index1:
             target: [ elasticsearch-instance ]
           index2:
             target: [ elasticsearch-instance ]
           index3:
             target: [ elasticsearch-instance ]
           '*':       # DO NOT remove, always required
             target: [ elasticsearch-instance ]              
   pipelines:
     - name: elasticsearch-proxy-read
       frontendConnectors: [ elastic-query ]
       processors: [ query-processor ]
       backendConnectors: [ elasticsearch-instance, clickhouse-instance ]
     - name: elasticsearch-proxy-write # remove if you do NOT want to write data to Elasticsearch nor ClickHouse
       frontendConnectors: [ elastic-ingest ]
       processors: [ ingest-processor ]
       backendConnectors: [ elasticsearch-instance, clickhouse-instance ]

Note: To learn more about configuration options, refer to Configuration primer

2. Run Quesma with the following command:

   docker run --name quesma -p 8080:8080 \
    -e QUESMA_CONFIG_FILE=/configuration/quesma.yaml \
   -v $(pwd)/quesma.yaml:/configuration/quesma.yaml quesma/quesma:latest

   You have now a running Quesma instance running with Elasticsearch API endpoint on port 8080. You can also enable Quesma's admin panel at localhost:9999 by adding -p 9999:9999 to docker run command.
3. Reconfigure client endpoint:
   • For Kibana: update your Kibana configuration, so that it points to Quesma Elasticsearch API endpoint mentioned above, instead of Elasticsearch original endpoint. In your Kibana configuration file, replace the elasticsearch.hosts value with Quesma's host and port, e.g.:

   elasticsearch.hosts: ["http://quesma:8080"]

   or optionally use ELASTICSEARCH_HOSTS environment variable.
   • For OpenSearchDashboards: modify opensearch_dashboards.yml file and change opensearch.hosts property. Also, make sure to update the Elasticsearch/OpenSearch endpoint configuration for any clients ingesting data.
4. Restart Kibana/OSD.
5. Add DataViews/Index Patterns:
   • For Kibana: in order to view your ClickHouse tables in Kibana, you need to create Data Views for tables (indexes) from the config. If you're unsure how to do it, follow the Data Views creation guide for more information.
   • For OpenSearchDashboards: you may need to add Index Patterns. See instructions.