8.9 Release notes
These release notes identify the main new features included in the 8.9 minor release, including alpha feature releases.
| Minor release date | Scheduled end of maintenance | Changelog(s) | Upgrade guides |
|---|---|---|---|
| 14 April 2026 | 13 October 2028 | Patch Releases and Changelogs | - |
- See release announcements to learn more about supported environment changes and breaking changes or deprecations.
- Refer to the quality board for an overview of known bugs by component and severity.
Technical Changelogs for all 8.9.x releases
Overview of all patch releases and their Changelogs in GitHub
8.9.0-alpha2
| Release date | Changelog(s) | Blog |
|---|---|---|
| 09 December 2025 | - |
Agentic orchestration
A2A Client connectors
Agent-to-Agent (A2A) Client connectors allow you to interact with remote agents using the A2A protocol.
| Connector | Description |
| A2A Client connector | Interact with A2A agents, by retrieving the remote agent’s Agent Card and sending messages to the agent. |
| A2A Client Polling connector | Poll for responses from asynchronous A2A tasks. Typically paired with the A2A Client connector when using the Polling response retrieval method. |
| A2A Client Webhook connector | Receive callbacks from remote A2A agents via HTTP webhooks. Typically paired with the A2A Client connector when using the Notification response retrieval method. |
These connectors support multi-agent collaboration scenarios when combined with the AI Agent connector, as well as providing the ability to discover remote agents, send messages, and receive responses through multiple mechanisms.
MCP client authentication and transport protocol
The Camunda Model Context Protocol (MCP) client now supports OAuth, API key, and custom header–based authentication.
- System administrators can configure secure, policy-compliant access for Camunda AI agents.
- AI developers can discover and invoke enterprise MCP tools safely without exposing open endpoints.
MCP client connectors now also support connections using the streamable HTTP transport protocol.
This feature introduces breaking changes in the element templates and the runtime configuration of the MCP Client. To learn more, see announcements.
Connectors
Amazon Textract connector improvements
The Amazon Textract connector is improved with input field visibility and polling fixes, new sections for enhanced usability, and updated documentation.
Azure Blob Storage connector supports OAuth 2.0
The Azure Blob Storage connector now supports OAuth2.0 authentication with Microsoft Azure.
Azure Blob Storage connector OAuth 2.0
Email connector supports SMTP no authentication mode
The Email connector now supports noAuth authentication mode for SMTP. This feature is useful for customers running local mail servers without authentication requirements.
Runtime performance improvements with virtual threads executor (Self-Managed)
Connectors now use a virtual threads executor by default, using Project Loom to improve performance and scalability.
This allows the connector runtime to handle a larger number of concurrent jobs with lower resource consumption, particularly benefiting I/O-bound workloads typical in connector operations.
Console
Bulk import secrets (SaaS)
You can now add/import secrets in Console by directly uploading or pasting the contents of a .env file.
- Key–value pairs are automatically parsed, validated, and added as secrets.
- This helps reduce configuration errors and copy-pasting when adding secrets.
Cluster description (SaaS)
You can now add a cluster description when creating a cluster or by editing the cluster settings. This helps you document context, ownership, or add operational notes without changing the cluster name.
Import cluster secrets (SaaS)
You can now import and export connector secrets between clusters within your organization.
Export a cluster’s secrets to a key-value file for backup or external workflows, and import secrets from another cluster in a single action. Imports automatically match keys, update existing values, create missing ones, and provide clear feedback on the result. Permissions are enforced so that only authorized users can perform these actions.
Usage metrics for licence model and tenant (Self-Managed)
Self-Managed environment usage metrics now support per-tenant reporting and align with Camunda’s updated licensing model based on the number of tenants.
This feature is already available in the Camunda 8.8 release for Camunda 8 SaaS.
Database and data storage
Configure external RDBMS in Helm
Configure an external relational database (RDBMS) as secondary storage for the Orchestration Cluster when deploying with Helm.
- Supports all databases listed in the RDBMS support policy.
- Includes full configuration parameters, history-cleanup options, and exporter settings.
- Describes how to load JDBC drivers via init containers, custom images, or mounted volumes.
- Provides steps to verify database connectivity.
Open-source OpenSearch support
You can now use the open-source OpenSearch project for data storage in a Self-Managed deployment.
- This allows you to run a fully open source observability stack without using Elasticsearch or the Amazon OpenSearch Service.
- For configuration instructions, see the updated Helm chart values and compatibility matrix.
RDBMS version support policy
A new Camunda 8 Relational Database Management System RDBMS support policy provides information about:
- Officially supported database versions.
- The process for adopting new database versions.
- Timelines for phasing out older database versions.
SQL and Liquibase database scripts
SQL and Liquibase scripts are provided for all Camunda-supported databases.
- These scripts include database and schema creation, drop, and upgrade routines.
- Scripts follow best practices for each supported database type and version.
- The full script package is distributed as part of the official Camunda distribution, available via GitHub or Artifactory.
Modeler
Element template signal support
Element templates now support reusable BPMN signals.
- The
bpmn:Signal#propertybinding allows you to set the name of abpmn:Signalreferred to by the templated element. - This binding is only valid for templates of events with
bpmn:SignalEventDefinition.
Element template bpmn:Signal binding
Web Modeler: Embedded web server changed from Undertow to Tomcat (Self-Managed)
Web Modeler now uses Apache Tomcat as an embedded web server instead of Undertow. Aligning Web Modeler logging with the Orchestration Cluster makes it easier for administrators to configure and maintain Self-Managed deployments.
Web Modeler: IP egress monitoring (SaaS)
A new /meta/ip-ranges REST API endpoint allows you to monitor SaaS Web Modeler egress IP addresses.
- For example, the endpoint is available at https://api.cloud.camunda.io/meta/ip-ranges.
- Send a GET request to the endpoint to retrieve a list of egress IP addresses.
- Only IP addresses for the related services are exposed (Web Modeler).
- You should periodically monitor this list via the API, and make any changes in your systems as required.
- Although expected changes are published via the API at least 24 hours in advance, in exceptional cases Camunda might have to update these addresses within 24 hours and without prior notice. See static outbound IP addresses.
8.9.0-alpha1
| Release date | Changelog(s) | Blog |
|---|---|---|
| 13 November 2025 | - |
JDBC driver management for RDBMS integrations
Camunda 8.9 introduces a standardized approach to JDBC driver management for RDBMS integrations in manual installations.
- A new
/driver-libdirectory separates Camunda-bundled drivers from customer-supplied ones, providing a clear and compliant structure for database connectivity. - Drivers that Camunda can legally distribute are included by default. Customers can add and configure their own drivers (for example, Oracle JDBC).
- Configuration options allow full control, including explicit driver-class designation when required.
This change simplifies compliance and setup for RDBMS environments, ensuring consistent connectivity across PostgreSQL, Oracle, MariaDB, and H2.
MySQL and Microsoft SQL Server secondary storage
Camunda 8.9 extends RDBMS secondary storage to include MySQL and Microsoft SQL Server as additional database options for the Orchestration cluster.
- This enhancement provides greater flexibility for enterprises that depend on these databases due to policy, licensing, or ecosystem requirements, enabling smoother onboarding and infrastructure alignment.
- Zeebe’s primary execution storage remains Raft + RocksDB.
This alpha release introduces foundational support only. External configuration and Operate integration follows in upcoming alpha releases.
RDBMS secondary storage (H2, PostgreSQL, Oracle, MariaDB)
Camunda 8.9 introduces RDBMS secondary storage as an alternative to Elasticsearch or OpenSearch for storing and querying process data.
This feature enables organizations to use relational databases such as H2, PostgreSQL, Oracle, or MariaDB as the secondary storage layer, reducing operational complexity for teams that do not need the scale or performance of Elasticsearch or OpenSearch and prefer an RDBMS-based solution.
Key highlights:
- Flexible database choice: Use relational databases instead of Elasticsearch or OpenSearch.
- Separation of concerns: Zeebe’s primary execution storage remains Raft + RocksDB; this update only extends the secondary storage layer.
- Consistent APIs: Continue using the same REST API and data format as with Elasticsearch or OpenSearch—no query or integration changes needed.
- Simplified operations: Leverage existing RDBMS expertise without maintaining Elasticsearch or OpenSearch clusters.
This alpha release introduces support for H2 in Camunda 8 Run only. Operate and external RDBMS configuration follows in upcoming alpha releases.
Web Modeler: RDBMS support (H2, MariaDB, MySQL)
Web Modeler now supports H2, MariaDB, and MySQL as relational database systems, aligning with the configurations supported by the Orchestration cluster.
This enhancement ensures consistency across environments, simplifies setup for administrators, and improves integration for both SaaS and Self-Managed deployments.