G2

Atharva P.

Cloud BI Engineer

Enterprise (> 1000 emp.)

7/30/2026

"Amazon MSK Makes Kafka Operations Simple with Seamless Scaling and AWS Integrations"

4.5/5

What do you like best about Amazon Managed Streaming for Apache Kafka (Amazon MSK)?

Amazon MSK has significantly simplified operating Apache Kafka by eliminating the complexity of provisioning, patching, monitoring, and maintaining Kafka clusters ourselves. I particularly like its compatibility with native Apache Kafka APIs, automated broker management, seamless scaling, high availability, and tight integration with the AWS ecosystem. The AWS Console provides a clean interface for managing clusters, broker configurations, storage scaling, networking, and monitoring, making administration much easier than self-managed Kafka deployments.

Performance has been excellent for handling high-throughput event streaming workloads with low latency and reliable message delivery. Native integrations with IAM, CloudWatch, Lambda, Glue, Flink, and Amazon MSK Connect make it easy to build end-to-end streaming architectures. Pricing is competitive considering the operational effort saved by using a fully managed Kafka platform instead of maintaining ZooKeeper, brokers, upgrades, and backups. While Amazon MSK itself is not an AI service, it plays a key role in streaming real-time data into SageMaker AI, Amazon Bedrock, and analytics pipelines. Review collected by and hosted on G2.com.

What do you dislike about Amazon Managed Streaming for Apache Kafka (Amazon MSK)?

Running dedicated Kafka brokers can become expensive for small workloads compared to serverless messaging services. Designing partitions, replication factors, and consumer groups also requires Kafka expertise to achieve optimal performance. Review collected by and hosted on G2.com.

What problems is Amazon Managed Streaming for Apache Kafka (Amazon MSK) solving and how is that benefiting you?

Amazon MSK provides a highly available event streaming platform for processing real-time application events across distributed systems.

Example: Application events, operational logs, and IoT telemetry are continuously published into Kafka topics hosted on Amazon MSK. Downstream consumers including Apache Flink, Lambda, Glue Streaming, and analytics platforms process these events in real time to power dashboards, notifications, and machine learning pipelines. This has significantly improved scalability while reducing infrastructure management. Review collected by and hosted on G2.com.