Azure HDInsight on AKS archived release notes
Note
We will retire Azure HDInsight on AKS on January 31, 2025. Before January 31, 2025, you will need to migrate your workloads to Microsoft Fabric or an equivalent Azure product to avoid abrupt termination of your workloads. The remaining clusters on your subscription will be stopped and removed from the host.
Important
This feature is currently in preview. The Supplemental Terms of Use for Microsoft Azure Previews include more legal terms that apply to Azure features that are in beta, in preview, or otherwise not yet released into general availability. For information about this specific preview, see Azure HDInsight on AKS preview information. For questions or feature suggestions, please submit a request on AskHDInsight with the details and follow us for more updates on Azure HDInsight Community.
Azure HDInsight on AKS is one of the most popular services among enterprise customers for open-source analytics on Azure. If you would like to subscribe on release notes, watch releases on this GitHub repository.
Release date: March 20, 2024
This release applies to the following
- Cluster Pool Version: 1.1
- Cluster Version: 1.1.1
- AKS version: 1.27
New Features
Apache Flink Application Mode Cluster
Application mode clusters are designed to support dedicated resources for large and long-running jobs. When you have resource-intensive or extensive data processing tasks, you can use the Application Mode Cluster. This mode allows you to allocate dedicated resources for specific Apache Flink applications, ensuring that they have the necessary computing power and memory to handle large workloads effectively.
For more information, see Apache Flink Application Mode cluster on HDInsight on AKS.
Private Clusters for HDInsight on AKS
With private clusters, and outbound cluster settings you can now control ingress and egress traffic from HDInsight on AKS cluster pools and clusters.
- Use Azure Firewall or Network Security Groups (NSGs) to control the egress traffic, when you opt to use outbound cluster pool with load balancer.
- Use Outbound cluster pool with User defined routing to control egress traffic at the subnet level.
- Use Private AKS cluster feature - To ensure AKS control plane, or API server has internal IP addresses. The network traffic between AKS Control plane / API server and HDInsight on AKS node pools (clusters) remains on the private network only.
- Avoid creating public IPs for the cluster. Use private ingress feature on your clusters.
For more information, see Control network traffic from HDInsight on AKS Cluster pools and cluster.
In place Upgrade
Upgrade your clusters and cluster pools with the latest software updates. This means that you can enjoy the latest cluster package hotfixes, security updates, and AKS patches, without recreating clusters. For more information, see Upgrade your HDInsight on AKS clusters and cluster pools.
Important
To take benefit of all these latest features, you are required to create a new cluster pool with 1.1 and cluster version 1.1.1.
Known issues
- Workload identity limitation:
- There's a known limitation when transitioning to workload identity. This limitation is due to the permission-sensitive nature of FIC operations. Users can't perform deletion of a cluster by deleting the resource group. Cluster deletion requests must be triggered by the application/user/principal with FIC/delete permissions. In case, the FIC deletion fails, the high-level cluster deletion also fails.
- User Assigned Managed Identities (UAMI) support – There's a limit of 20 FICs per UAMI. You can only create 20 Federated Credentials on an identity. In HDInsight on AKS cluster, FIC (Federated Identity Credential) and SA have one-to-one mapping and only 20 SAs can be created against an MSI. If you want to create more clusters, then you are required to provide different MSIs to overcome the limitation.
- Creation of federated identity credentials is currently not supported on user-assigned managed identities created in these regions
Operating System version
- Mariner OS 2.0
Workload versions
Workload | Version |
---|---|
Trino | 426 |
Flink | 1.17.0 |
Apache Spark | 3.3.1 |
Supported Java and Scala versions
Workload | Java | Scala |
---|---|---|
Trino | Open JDK 17.0.7 | - |
Flink | Open JDK 11.0.21 | 2.12.7 |
Spark | Open JDK 1.8.0_345 | 2.12.15 |
The preview is available in the following regions.
If you have any more questions, contact Azure Support or refer to the Support options page. If you have product specific feedback, write us on aka.ms/askhdinsight.
Release date: February 05, 2024
This release applies to the following
- Cluster Pool Version: 1.1
- Cluster Version: 1.1.0
- AKS version: 1.27
Tip
To create a new HDInsight on AKS cluster on 1.1.0, you are required to create a new cluster pool with version 1.1
New Features
- Workload Identity is supported by default for cluster pools on 1.1
- Trino clusters support Trino 426 from 1.1.0 release
- HDInsight on AKS now includes all changes up to Trino 426 with several notable improvements provided by the community. Learn more about Trino here.
- Trino cluster shape now supports load-based autoscale from 1.1.0 release
- Trino on HDInsight on AKS now supports load-based autoscale making cluster more cost efficient. Learn more about it here.
- Trino cluster shape adds simplified hive metastore and catalogs configuration
- HDInsight on AKS has simplified external Hive metastore configuration for Trino cluster. you can now specify external metastore in config.properties and enable it for each catalog with single parameter. Learn more about enhancements here.
- Trino cluster shape adds sharded sql connector
- Flink clusters now support Flink 1.17.0 from HDInsight on AKS 1.1.0 release
- HDInsight on AKS now supports Flink 1.17.0 release, with significant improvements on checkpoints, subtask level flame graph, watermark alignments. Learn more about the Flink 1.17 release here
- Flink SQL Gateway is now supported from HDInsight on AKS 1.1.0 release with Flink session clusters
Bug Fixes & CVEs
- This release includes several critical CVE fixes across the platform and open source components.
- Trino cluster shape excludes system tables from caching automatically
- Trino cluster shape improves Power BI timestamp timezones handling
Known issues
- Workload identity limitation:
- There's a known limitation when transitioning to workload identity. This is due to the permission-sensitive nature of FIC operations. Users can't perform deletion of a cluster by deleting the resource group. Cluster deletion requests must be triggered by the application/user/principal with FIC/delete permissions. In case, the FIC deletion fails, the high-level cluster deletion will also fail.
New regions
- East Asia
Operating System version
- Mariner OS 2.0
Workload versions
Workload | Version |
---|---|
Trino | 426 |
Flink | 1.17.0 |
Apache Spark | 3.3.1 |
Supported Java and Scala versions
Workload | Java | Scala |
---|---|---|
Trino | Open JDK 17.0.7 | - |
Flink | Open JDK 11.0.21 | 2.12.7 |
Spark | Open JDK 1.8.0_345 | 2.12.15 |
The preview is available in the following regions.
If you have any more questions, contact Azure Support or refer to the Support options page. If you have product specific feedback, write us on aka.ms/askhdinsight.
Next steps
Release date: December 13, 2023
This hotfix release applies to the following
- Cluster Pool Version: 1.0
- Cluster Version: 1.0.6
Known Issues
Secure Tenants User Interface Support
- This release addresses an issue where the open source component web URLs for HDInsight on AKS Clusters were inaccessible. For applying this fix, reach out to Azure support to enable this on your subscription/tenant.
How to apply the Hotfix
- Recreate Your Cluster
- To apply this hotfix, existing users are required to recreate their cluster on an existing cluster pool.
Operating System version
- Mariner OS 2.0
Workload versions
Workload | Version |
---|---|
Trino | 410 |
Flink | 1.16 |
Apache Spark | 3.3.1 |
Supported Java and Scala versions
Workload | Java | Scala |
---|---|---|
Trino | Open JDK 17.0.7 | - |
Flink | Open JDK 11.0.21 | 2.12.7 |
Spark | Open JDK 1.8.0_345 | 2.12.15 |
The preview is available in the following regions.
If you have any more questions, contact Azure Support or refer to the Support options page.