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Query Hydrolix tables as Elasticsearch indices

In this scenario, user's only data source is Hydrolix, which contains two tables named logs and siem. Quesma is configured to expose Hydrolix tables via Elasticsearch API, making them visible in Kibana/OpenSearch Dashboard (OSD) as Elasticsearch indices. Note: ingest to Hydrolix is currently not supported, let us know if you are interested in this functionality.

Note

In this approach, we require a minimal Elasticsearch/OpenSearch cluster for:

  • storing Kibana/OSD metadata
  • storing user data and authentication (unless its explicitly disabled)

Architecture diagram:

Quesma installation

Prerequisites:

  • Hydrolix 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.
    yaml
    licenseKey: #PLACE_YOUR_LICENSE_KEY_HERE 
    # license key is required for backend connector of `hydrolix` type, 
    # please contact Quesma support (support@quesma.com) to obtain yours  
    frontendConnectors:
      - name: elastic-query
        type: elasticsearch-fe-query
        config:
          listenPort: 8080
    backendConnectors:
      - name: minimal-elasticsearch
        type: elasticsearch
        config:
          url: #PLACE_YOUR_ELASTICSEARCH_URL_HERE
          user: #PLACE_YOUR_ELASTICSEARCH_USERNAME_HERE
          password: #PLACE_YOUR_ELASTICSEARCH_PASSWORD_HERE
      - name: hydrolix-instance
        type: hydrolix
        config:
          url: #PLACE_YOUR_HYDROLIX_URL_HERE
          user: #PLACE_YOUR_HYDROLIX_USER_HERE
          password: #PLACE_YOUR_HYDROLIX_PASSWORD_HERE
          database: #PLACE_YOUR_HYDROLIX_DATABASE_NAME_HERE
    processors:
      - name: query-processor
        type: quesma-v1-processor-query
        config:
          indexes:      # `siem` and `logs` are just examples, 
            siem:       # make sure to replace them with your actual table names in your Hydrolix instance
              target: [ hydrolix-instance ]
            logs:
              target: [ hydrolix-instance ]
            '*':       # DO NOT remove, always required
              target: [ minimal-elasticsearch ]
    pipelines:
      - name: elasticsearch-proxy-read
        frontendConnectors: [ elastic-query ]
        processors: [ query-processor ]
        backendConnectors: [ minimal-elasticsearch, hydrolix-instance ]

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

  1. Run Quesma with the following command:
    bash
    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.
  2. 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.:
    yaml
    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.
  3. Restart Kibana/OSD.
  4. Add DataViews/Index Patterns:
    • For Kibana: in order to view your Hydrolix 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.