Category: Amazon Managed Streaming for Apache Kafka (Amazon MSK)

In this post, we’ll show you how to use Kiro powers, a new capability that equips Kiro with contextual knowledge and tooling. You can simplify your MSK cluster management, from initial setup to diagnosing common issues, all through natural language conversations.

In this post, we introduce the workload simulation workbench for Amazon Managed Streaming for Apache Kafka (Amazon MSK) Express Broker. The simulation workbench is a tool that you can use to safely validate your streaming configurations through realistic testing scenarios.

In this post, we show you how to use the new topic management capabilities of Amazon MSK to streamline your Apache Kafka operations. We demonstrate how to manage topics through the console, control access with AWS Identity and Access Management (IAM), and bring topic provisioning into your continuous integration and continuous delivery (CI/CD) pipelines.

In this post, we show you how Kafka clients can use Zilla Plus to securely access your MSK Serverless clusters through Identity and Access Management (IAM) authentication over PrivateLink, from as many different AWS accounts or VPCs as needed. We also show you how the solution provides a way to support a custom domain name for your MSK Serverless cluster.

In this post, we show you how Amazon Managed Streaming for Apache Kafka (Amazon MSK) Express brokers brokers streamline the end-to-end activities for Kafka administration.

In this post, we demonstrate how to use AWS IAM Roles Anywhere to request temporary AWS security credentials, using x.509 certificates for client applications which enables secure interactions with an Amazon Managed Streaming for Apache Kafka (Amazon MSK) cluster. The solution described in this post is compatible with both Amazon MSK Provisioned and Serverless clusters.

In this post, I show you how to implement effective monitoring for your Kafka clusters using Amazon MSK and Amazon CloudWatch. You’ll learn how to track critical metrics like broker health, resource utilization, and consumer lag, and set up automated alerts to prevent operational issues.

In this post, we demonstrate how to use Iceberg Kafka Connect with Amazon Managed Streaming for Apache Kafka (Amazon MSK) Connect to accelerate real-time data ingestion into data lakes, simplifying the synchronization process from transactional databases to Apache Iceberg tables.

Amazon MSK Express brokers are a key component to dynamically scaling clusters to meet demand. Express based clusters deliver 3 times higher throughput, 20 times faster scaling capabilities, and 90% faster broker recovery compared to Amazon MSK Provisioned clusters. In addition, Express brokers support intelligent rebalancing for 180 times faster operation performance, so partitions are automatically and consistently well distributed across brokers. Intelligent rebalancing automatically tracks cluster health and triggers partition redistribution when resource imbalances are detected, maintaining performance across brokers. This post demonstrates how to use the intelligent rebalancing feature and build a custom solution that scales Express based clusters horizontally (adding and removing brokers) dynamically based on Amazon CloudWatch metrics and predefined schedules. The solution provides capacity management while maintaining cluster performance and minimizing overhead.

In this post, we present a scalable solution that addresses the challenge of migrating your large binary objects (LOBs) from Oracle to AWS by using a streaming architecture that separates LOB storage from structured data. This approach avoids size constraints, reduces Oracle licensing costs, and preserves data integrity throughout extended migration periods.