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    Home»Big Data»Amazon MSK Express brokers now support Intelligent Rebalancing for 180 times faster operation performance
    Big Data

    Amazon MSK Express brokers now support Intelligent Rebalancing for 180 times faster operation performance

    AdminBy AdminNovember 11, 2025No Comments5 Mins Read3 Views
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    Amazon MSK Express brokers now support Intelligent Rebalancing for 180 times faster operation performance
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    Effective today, all new Amazon Managed Streaming for Apache Kafka (Amazon MSK) Provisioned clusters with Express brokers will support Intelligent Rebalancing at no additional cost. With this new capability you can perform automatic partition balancing operations when scaling Apache Kafka clusters up or down. Intelligent Rebalancing maximizes the capacity utilization of Amazon MSK clusters with Express brokers by optimally rebalancing Kafka resources on them for better performance, eliminating the need to manage partitions independently or by using third-party tools. Intelligent Rebalancing on Amazon MSK Express brokers performs these operations up to 180 times faster compared to Standard brokers.

    We launched Amazon MSK Express brokers in November 2024 to reimagine Apache Kafka for ease of use, best-in-class price performance, and predictable availability. Amazon MSK Express brokers are designed to deliver up to three times more throughput per-broker, scale up to 20 times faster, and reduce recovery time by 90 percent as compared to Standard brokers running Apache Kafka. Since launch, we have expanded Amazon MSK Express brokers to additional AWS Regions, instance types, and most recently increased support to 5x more partitions per Express broker, improving price-performance by up to 50% for partition-bound workloads.

    With Intelligent Rebalancing, Amazon MSK Express broker clusters are continuously monitored for resource imbalance or overload based on intelligent Amazon MSK defaults to maximize cluster performance. When required, brokers are efficiently scaled, without affecting cluster availability for clients to produce and consume data. Customers can now take full advantage of the scaling and performance benefits of Amazon MSK Provisioned clusters for Express brokers while simplifying cluster management operations.

    In this post we’ll introduce the Intelligent Rebalancing feature and show an example of how it works to improve operation performance.

    When to use Intelligent Rebalancing

    With Intelligent Rebalancing, Amazon MSK Express brokers now offer a fully automated solution for managing and scaling Kafka clusters, requiring no additional tools or configuration. Intelligent Rebalancing is enabled by default on all new Amazon MSK Express brokers clusters, so we recommend always keeping it on. Intelligent Rebalancing uses Amazon MSK best practices to trigger automatic rebalancing during the following situations:

    • Scaling in and out clusters: When customers add or remove brokers from their Amazon MSK Express brokers clusters, Intelligent Rebalancing automatically redistributes partitions to balance resource utilization across the brokers. This ensures that the cluster continues to operate at peak performance, making scaling in and out possible with a single update operation.
    • Steady-state rebalancing: Even during normal operations, Intelligent Rebalancing continuously monitors the Amazon MSK Express brokers cluster and triggers rebalancing when it detects resource imbalances or hotspots. For example, if certain brokers become overloaded due to uneven distribution of partitions or skewed traffic patterns, Intelligent Rebalancing will automatically move partitions to less utilized brokers to restore balance.

    How to use Intelligent Rebalancing

    To demonstrate the power of Intelligent Rebalancing, let’s run a few tests on an Amazon MSK Express brokers cluster:

    Scaling test: We’ll start by creating an Amazon MSK Express brokers cluster with 3 brokers. We’ll then rapidly scale the cluster up to 6 brokers and back down to 3 brokers, simulating a sudden spike in workload. With Intelligent Rebalancing enabled, you’ll see that the rebalancing of partitions is completed within 5-10 minutes, so that the cluster can sustain the increased throughput without any drop in performance.


    You can track the current and historical rebalancing operations using the metric RebalanceInProgress. In the picture below, you can also see that the clients on the producer side are not impacted during this rebalancing.

    Next, we’ll create an imbalance in the cluster by directing a large portion of the traffic to a single broker. You’ll see that Intelligent Rebalancing detects this imbalance within minutes and automatically redistributes the partitions, restoring the cluster to an optimal state.

    The intelligent rebalancing feature detects hotspots and automatically redistributes affected partitions across other brokers to optimize resource utilization. Without Intelligent Rebalancing, the resource imbalance would persist, potentially leading to performance issues or the need for manual intervention by the customer.

    These tests showcase how Intelligent Rebalancing with Amazon MSK Express brokers enables scaling Kafka clusters seamlessly while maintaining consistently high performance, even under varying workload conditions.

    Conclusion

    Intelligent Rebalancing for Amazon MSK Provisioned clusters with Express brokers are currently being rolled out over the next few weeks in all AWS Regions where Amazon MSK Express brokers are supported. This feature is automatically enabled for all new Amazon MSK Provisioned clusters with Express brokers at no additional cost.

    To get started, visit the Amazon MSK console. For more information, see the Amazon MSK Developer Guide.


    About the authors

    Swapna Bandla

    Swapna Bandla

    Swapna is a Senior Streaming Solutions Architect at AWS. With a deep understanding of real-time data processing and analytics, she partners with customers to architect scalable, cloud-native solutions that align with AWS Well-Architected best practices. Swapna is passionate about helping organizations unlock the full potential of their data to drive business value. Beyond her professional pursuits, she cherishes quality time with her family.

    Masudur Rahaman Sayem

    Masudur Rahaman Sayem

    Masudur is a Streaming Data Architect at AWS with over 25 years of experience in the IT industry. He collaborates with AWS customers worldwide to architect and implement sophisticated data streaming solutions that address complex business challenges. He has a keen interest and passion for distributed architecture, which he applies to designing enterprise-grade solutions at internet scale.

    Shakhi Hali

    Shakhi Hali

    Shakhi is a Principal Product Manager for Amazon Managed Streaming for Apache Kafka (Amazon MSK) at AWS. She is passionate about helping customers generate business value from real-time data. Before joining MSK, Shakhi was a PM with Amazon S3. In her free time, Shakhi enjoys traveling, cooking, and spending time with family.



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