Stackable Operator for Apache Druid
The Stackable Operator for Apache Druid is an operator that can deploy and manage Apache Druid clusters on Kubernetes. Apache Druid is an open-source, distributed data store designed to quickly process large amounts of data in real-time. It enables users to ingest, store, and query massive amounts of data in real-time, a great tool for handling high-volume data processing and analysis. This operator provides several resources and features to manage Druid clusters efficiently.
To get started with the Stackable Operator for Apache Druid, follow the Getting Started guide. It guides you through the installation of the Operator and its dependencies (ZooKeeper, HDFS, an SQL database) and the steps to query your first sample data.
The Operator is installed along with the DruidCluster CustomResourceDefinition, which supports five roles: Router, Coordinator, Broker, MiddleManager and Historical. These roles correspond to Druid processes.
The Operator watches DruidCluster objects and creates multiple Kubernetes resources for each DruidCluster based on its configuration.
For every RoleGroup a StatefulSet is created. Each StatefulSet can contain multiple replicas (Pods). Each Pod has at least two containers: the main Druid container and a preparation container which just runs once at startup. If Log aggregation is enabled, there is a sidecar container for logging too. For every Role and RoleGroup the Operator creates a Service.
A ConfigMap is created for each RoleGroup containing 3 files:
runtime.properties files generated from the DruidCluster configuration (See Usage guide for more information), plus a
log4j2.properties file used for Log aggregation.
For the whole DruidCluster a discovery ConfigMap is created which contains information on how to connect to the Druid cluster.
The Druid Operator has the following dependencies:
An SQL database to store metadata.
Apache ZooKeeper via the Stackable Operator for Apache ZooKeeper. Apache ZooKeeper is used by Druid for internal communication between processes.
The Stackable Secret Operator is required for things like S3 access credentials or LDAP integration.
Have a look at the getting started guide for an example of a minimal working setup. Druid works well with other Stackable supported products, such as Apache Kafka for data ingestion Trino for data processing or Superset for data visualization. OPA can be connected to create authorization policies. Have a look at the Usage guide for more configuration options and have a look at the demos for complete data pipelines you can install with a single command.
stackablectl supports installing Demos with a single command. The demos are complete data piplines which showcase multiple components of the Stackable platform working together and which you can try out interactively. Both demos below include Druid as part of the data pipeline: