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Crafting a Multi-Node Multi-Broker Kafka Cluster- A Weekend Project

Supplementary Posts

The Role of Materialized Views in Modern Data Stream Processing Architectures + RisingWave

Unlocking the Power of Patterns in Event Stream Processing (ESP): The Critical Role of Apache Flink’s FlinkCEP Library

Real-Time Redefined: Apache Flink and Apache Paimon Influence Data Streaming’s Future

Revolutionize Stream Processing with the Power of Data Fabric

Bridging the Gap: Unlocking the Power of HDFS-Based Data Lakes with Streaming Databases

Which Flow Is Best for Your Data Needs: Time Series vs. Streaming Databases

2 responses to “Crafting a Multi-Node Multi-Broker Kafka Cluster- A Weekend Project”

Revolutionize Stream Processing with the Power of Data Fabric » DataView says:

January 22, 2025 at 12:32 pm

[…] to access data, regardless of its origin. An open-source distributed event-streaming platform like Apache Kafka supports data fabric by handling real-time data streaming across various systems. It also acts as a […]

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Integrating rate-limiting and backpressure strategies synergistically to handle and alleviate consumer lag in Apache Kafka - Real-time Data Streaming, Real-time Data Processing, Real-time Data Analytics | Data Engineering Solution in Bangalore | Apache Ka says:

February 14, 2025 at 3:15 pm

[…] Various third-party monitoring tools and user interfaces offer an intuitive platform for visualizing Kafka lag metrics. Options include Burrow, Grafana for ongoing monitoring, or a local Kafka UI connected to our production Kafka instance. […]

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