Deployment architecture
You can deploy Qlik Big Data Index in a number of Kubernetes environments. The cluster consists of a number of pods. Each pod runs software services that perform specific roles in the cluster.
You use the Management Console server to control the deployed cluster through the REST API. You connect to the Management Console server using the Management Console to configure and start index creation, and to manage services running on indexing and worker pods. Ingress is used to make the management console available on port 80.
Indexing pods are responsible for creating index and symbols from the Parquet data source files on a mounted storage volume (for example, HDFS, S3, EFS, or NFS).
The Qlik Sense client can access data from the index by connecting with a query to the QSL Manager. QSL Manager controls QSL Worker pods that handle the query and retrieve the data.
The single-pod per service cluster is the simplest cluster you can deploy. You can scale the deployment with a multi-pod per service cluster as shown here. Deploy multiple indexer servers and symbol servers to be able to speed up indexing, and deploy QSL workers to handle incoming data queries. You can deploy pods on separate machines, or co-locate them on the same machine.
Services
The following services are running in a Qlik Big Data Index cluster. The service name is prepended with the name of the cluster. When there are multiple pods per service a sequential number is appended.
Service | Pod type |
---|---|
indexer | Indexer server |
indexingmanager | Indexing manager |
license | License server |
managementconsole | Management Console server |
qslexecutor | QSL executor |
qslmanager | QSL manager |
qslworker | QSL worker |
restapi | REST API server |
symbolserver | Symbol server |
nginx-ingress-controller | Ingress controller |
nginx-ingress-default-backend | Ingress controller |
sourcedatacloudgw | Source data cloud gateway |
outputcloudgw | Output cloud gateway |
broker | Data broker |