Cloudera Data Engineering cluster types

Learn more about the available cluster types that you can use in your Cloudera Data Engineering service.

On the Cloudera Data Engineering UI, DE and Platform administrators can create new Virtual Clusters and select the required cluster type at Administration > Create a Virtual Cluster.

Cloudera Data Engineering offers these cluster types:
  • Core
  • All purpose

In the same Cloudera Data Engineering Service, you can run some workloads on Core and some workloads on All purpose clusters.

Core cluster functionalities:

  • Autoscaling cluster
  • Spot instances
  • SDX
  • Open Lakehouse with Iceberg
  • Job lifecycle management
  • Centralized monitoring
  • Workflow orchestration (Airflow)

All Purpose cluster functionalities (on top of functionalities available with Core clusters as well):

  • Interactive sessions
  • External IDE connectivity
  • Spark streaming
  • JDBC connector (Coming soon)

At Administration > Enable a Service > Capacity & Costs > Autoscale Range, you can set the autoscale range for the On-demand Instances, that is for the Core clusters. The range you set on this page for the On-demand Instances is used also for the All purpose Instances, that is for the All purpose clusters.

At Administration > Service Details, you can modify the autoscale value range of:

  • On-demand Instances
  • All purpose On-demand Instances
  • Spot Instances
  • All purpose Spot Instances

You can use Spot Instances and All purpose Spot Instances to save compute costs.