What's new in 1.5.5 SP3
Cloudera Data Engineering on premises 1.5.5 SP3 introduces a set of new features for Cloudera Data Engineering.
- Tainted node support
- Cloudera Embedded Container Service now automatically applies both the Kubernetes taint and label when a node profile is selected in Cloudera Manager. Administrators do not have to manually run the kubectl label commands to map profiles. Selecting a Cloudera Data Engineering profile in and running Refresh ECS now applies both the taint and label in one step. For more information, see Dedicating Cloudera Embedded Container Service nodes for Cloudera Data Engineering.
- Seamless configuration updates for Cloudera Data Engineering Service or Virtual Cluster
- Cloudera Data Engineering simplifies managing configuration changes for existing Cloudera Data Engineering Services and Virtual Clusters (VCs). Now, when you update settings such as proxy and LDAP in the Cloudera Management Service, or Kerberos in the Cloudera Base on premises, a banner is automatically displayed within the affected service. You can apply these changes directly with a single click, completely eliminating the need to manually update configurations or redeploy services and VCs. For more information, see Updating and synchronizing stale configurations.
- S3-compatible credential management
- You can register shared, S3-compatible object storage credentials that workloads can reuse across your Cloudera on premises deployment. For more information, see Connecting to S3 compatible accounts for Cloudera Data Engineering jobs or sessions.
- Cloudera Base on premises component support
- Cloudera Data Engineering supports connections to Cloudera Base on premises components, including Kafka, Hbase, Phoenix, and Ozone. For more information, see
- External IDE connectivity through Spark Connect-based sessions (GA)
- External IDE connectivity through Spark Connect-based sessions is now generally
available (GA) and provides the following new functionalities:
- Supports JVM clients such as Java and Scala.
- Increases session timeout from 8 hours to a maximum value of 90 days to enable long-running external IDE Spark Connect sessions.
- Supports dynamic allocation of external IDE Spark Connect sessions.
- Supports adding JAR artifacts up to a maximum file size of 200 MB.
- User Access Management support for Airflow jobs
- Only a user with Administrator privileges such as
DEAdmin,Service Admin, andVC Admincan manage connections, variables and XCOM in the Airflow UI. All users can create or manage Airflow jobs. For more information, see Access roles in Cloudera Data Engineering. - Airflow package removals
- The following default packages have been removed from the Cloudera Data Engineering 1.5.5 SP3 release due to identified CVE risks:
- apache-airflow-providers-google (Related CVE: CVE-2026-27459)
- apache-airflow-providers-snowflake (Related CVE: CVE-2025-50213)
If your DAGs rely on any of these packages, you must take one of the following actions:
- Install the required packages manually using Airflow custom providers. For more
information, see Adding custom operators and libraries.
This approach restores the functionality without requiring DAG code changes but keeps your environment exposed to the associated CVE risks.
- Update DAG code. Modify your DAG code to remove or replace references to the discontinued packages.
For more information, see Supported Airflow operators and hooks.
- End of support for CDS 3.3 (Cloudera Distribution of Apache Spark) in Cloudera Base on premises 7.1.9
- For Spark runtimes, CDS 3.3 (Cloudera Distribution of Apache Spark) in Cloudera Base on premises 7.1.9 is deprecated and will be end of support in August 2026. Meanwhile, all other Spark runtimes will follow the Cloudera Base on premises end of life timeline. For more information, see CDS Overview.
