June 25, 2026

Istio Ambient mode support

Cloudera Data Engineering now supports Istio Ambient mode, which is a sidecar-less data plane architecture to reduce compute costs, simplify operations and scale networking capabilities.

Job ownership specification during Cloudera Data Engineering job restoration

To enhance security and prevent unauthorized job scheduling, restoring jobs as another user requires DEAdmin privileges. Aligning with security requirements, this feature ensures that regular users cannot restore jobs on behalf of other users. The --use-stored-user and the --do-as flags of the cde backup restore command specify the job ownership during restoration.

For more information, see Restoring Cloudera Data Engineering jobs from backup.

Data Lake 7.3.2 support

Cloudera Data Engineering with the Security Hardened image supports Data Lake 7.3.2 with Spark version 3.5.4.

For more information, see Upgrading to Cloudera Data Lake 7.3.2 with Cloudera Data Engineering.

Configurable diagnostics bundle batch job CPU and memory resources

With DEAdmin role, optionally, you can configure CPU and memory allocation in the Generate Diagnostics Bundle dialog box in the Cloudera Data Engineering UI. This helps prevent inaccurate resource allocation and potential Out-of-Memory (OOM) errors during bundle generation for large environments.

For more information, see Allocating resources for CPU and memory for generating the diagnostics bundle.

In-place upgrade progress messages in the Cloudera Data Engineering UI

When performing an in-place upgrade on a Cloudera Data Engineering Service, a progress message in the UI displays the current step out of the total number of upgrade steps.

Postgres support removal

In Cloudera Data Engineering 1.26.1 and higher versions the support for Postgres is removed.

Job-level Instance Type Override (GA)

The Job-level Instance Type Override feature, previously available as a technical preview, now reached General Availability (GA).

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.

Kubernetes version upgrade to 1.34

The Kubernetes version that Cloudera Data Engineering uses is upgraded to Kubernetes 1.34.

For more information, see Compatibility for Cloudera Data Engineering and Runtime components.

Airflow version upgrade to 2.11.2

The Airflow version that Cloudera Data Engineering uses is upgraded to Airflow 2.11.2.

Airflow package removals

The following default packages have been removed from the Cloudera Data Engineering 1.26.1 release due to identified CVE risks:

• apache-airflow-providers-google (Related CVE: CVE-2026-27459)
• apache-airflow-providers-snowflake (Related CVE: CVE-2025-50213)
• apache-airflow-providers-amazon (Related CVE: CVE-2024-12745)

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.
• Update DAG code. Modify your DAG code to remove or replace references to the discontinued packages.

Airflow 2 deprecation

Airflow 2 has been deprecated, aligning with the upstream end-of-support, which took effect in April 2026.

Cloudera Data Engineering will continue to support Airflow 2 with security updates and will publish further notices pertaining to changes required to maintain Airflow 2.

When Airflow 3 is introduced in Cloudera Data Engineering, upgrades to Airflow 3 will also be communicated to plan migrations accordingly.

MySQL version upgrade to 8.4.7

The MySQL version that Cloudera Data Engineering uses is upgraded to MySQL 8.4.7 for both AWS and Azure.