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October 8, 2025
Kafka 4.1 brings a new wave of improvements that make stream processing faster, simpler, and more secure. Building on the momentum of the Kafka 4 release, this update introduces major upgrades like Queues for Kafka (KIP-932) for cooperative message consumption, a more efficient Kafka Streams rebalance protocol (KIP-1071), and native JWT-bearer authentication (KIP-1139) to strengthen security. While some features are still in preview, Kafka 4.1 continues to smooth out operations, cut down on rebalancing overhead, and make scaling easier for modern data teams.
Keep reading to discover how these changes will impact your Apache Kafka deployments and whether it makes sense to upgrade now or wait till all the new features are production-ready.
Kafka 4.1 Release Date
Back to topKafka 4.1.0 was released on September 2, 2025.
Kafka 4.1 Features
Queues for Kafka (KIP-932): Enabling Cooperative Message Processing
One of the stalwart functions of Kafka is its immutable write-ahead log (WAL). This functionality has been at the core of Kafka’s streaming capabilities and extreme scalability. While the WAL is part of what made Kafka so successful, it also created direct coupling of consumers and partitions in a 1:1 relationship — which often times results in the unintended consequence having to over partition topics to meet demand in use cases where specific assignments to partitions are just not required (i.e. non-ordered data, or decoupled data events).
Now instead of having to provision additional partitions to meet this demand for consumers, Queues for Kafka will allow organizations to implement more traditional JMS queues-like behavior in a one-to-many relationship by utilizing “Share Groups”. The fundamental differences between share groups and consumer groups are (from the wiki):
- The consumers in a share group cooperatively consume records with partitions that may be assigned to multiple consumers
- The number of consumers in a share group can exceed the number of partitions in a topic
- Records are acknowledged on an individual basis, although the system is optimized to work in batches for improved efficiency
- Delivery attempts to consumers in a share group are counted to enable automated handling of unprocessable records
Several new concepts have been introduced to Kafka to enable share groups. Group coordinators are extended to support share groups as the share coordinator. The share coordinator utilizes an internal topic to manage share-group state persistence. The concept of a share-partition, a topic-partition designated for subscriptions in a shared group, and a share-partition leader have also been added. Share-partitions leaders are a broker component co-located with topic-partition leaders that manage the share group’s view of the topic-partition.
Queues for Kafka was added as an early access feature in 4.0 and promoted to preview in 4.1, but it is not ready for production just yet. It's also important to note that 4.0 clusters that have had the early-access code enabled cannot be upgraded to 4.1 for compatibility reasons. However, 4.1 clusters and onward will be upgradeable even after the preview-code is enabled. So if you are starting with Queues for Kafka fresh with 4.1 onward, you will no longer be restricted in your upgrade paths.
Learn how to develop your Kafka partition strategy
Enhanced Kafka Streams Rebalance Protocol (KIP-1071): Optimizing Stream Processing
KIP-848, introduced as a general access feature in 4.0, was designed to resolve several issues: full-group stop the world issues due to membership changes; ephemeral changes to member.id assignments tied to heartbeat statuses (meaning a single missed heartbeat could trigger a stop the world rebalance event); and lastly, brittle client-side assignments that would allow for a slow or overloaded leader to severely delay rebalances. These three issues in particular made large groups more difficult and inefficient to manage and made rebalancing more expensive than it needed to be.
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KIP-848 addressed these issues by allowing incremental assignments, removing ephemeral memberships by introducing durable member IDs, and eliminating fragile client-side assignment by moving coordination to the broker, which made consumer groups faster, more resilient, and extensible.
KIP-1071, now in early access, takes the foundation from KIP-848 and applies it to Kafka Streams’ task rebalances. Instead of the old, heavy, client-led process where one Streams instance acted as leader and every rebalance meant a full stop-and-sync, Streams can now rely on the broker-coordinated protocol with stable member IDs and incremental assignments. That means tasks move faster, only the affected ones are reassigned, and a restarted instance can reclaim its state without forcing the whole application to reshuffle. In practice, this translates to shorter downtime, less state churn, and smoother scaling for Streams apps.
Read about Kafka stream processing
Native JWT-Bearer Authentication (KIP-1139): Streamlining Enterprise Security
When Kafka originally implemented basic support for machine-to-machine OAuth in Kafka 3.1, it only supported the client_credentials grant type. As such, secrets had to be specified with plain-text values in the configuration. OAuth 2.0 has a wide array of supported grant type specifications; one of the most commonly used supported grant type is JWT Bearer tokens.
With the implementation of KIP-1139, clients can start leveraging the inherently more secure grant type method based on a cryptographically signed JWT assertion rather than a plain text secret. This greatly reduces the potential for security incidents as the secret no longer has to be included in the deployment and information used to generate the assertion can be rotated as dictated by an organization’s security policy.
The new org.apache.kafka.common.security.oauthbearer package houses all classes, interfaces, and exceptions for this new implementation.
See best practices for Kafka security
Back to topStrategic Kafka Upgrade Considerations
Here are some things to keep in mind as you determine when to upgrade to Kafka 4.1.
Production Readiness Assessment
While some of the major additions to Kafka 4.1 are not considered ready for production quite yet, below are some additional changes that are considered ready for general use:
- Multi-version Kafka Connect plugins (KIP-891)
- Run multiple versions of the same connector/SMT/converter side-by-side for safer upgrades and rollbacks.
- Producer safety improvements (KIP-1118)
- Prevents deadlocks by disallowing
producer.flush()inside a callback.
- Prevents deadlocks by disallowing
- Consumer API improvements
Consumer.close(CloseOptions)for more flexible group handling. (KIP-1092)- Rebalance on rack topology change and more memory-efficient assignments for large groups. (KIP-1101)
- Admin API & transactions enhancements
ListTransactionscan filter by transactional ID pattern (better scalability).- Transactional API error handling/documentation standardized (KIP-1050).
These features, along with the other non-preview gated code, represent a safe evolutionary upgrade for core Kafka, Kafka Connect, and client libraries without any major breaking changes for standard deployments. With the caveat of 4.0 clusters that have enabled Queues for Kafka in early access, the upgrade path from 4.0 and late 3.x deployments should be fairly uneventful and straightforward for this 4.1 release.
Back to topWhat to Expect in Future 4.x Releases
In future 4.x releases, we should see the full release to general availability for Queues for Kafka and the new Streams Rebalancing protocol. We also will most likely see an across-the-board decommissioning of the old legacy consumer group protocol. Of course, further refinements to the KRaft quorum protocol and other controller improvements will presumably be on the agenda as well.
Back to topFinal Thoughts
Kafka 4.1 delivers meaningful improvements without demanding an immediate upgrade. For most teams, it’s a solid, stable release that refines core functionality and prepares the groundwork for bigger changes ahead. If your current deployment is running smoothly on 4.0 or a late 3.x version, there’s no rush — especially if you’ve been testing early-access features like Queues for Kafka.
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