Damandeep singh @Daman0203 - Twitter Profile

Just got into reading, and The Almanack of Naval Ravikant is hitting different. Crazy how much perspective this book packs- every page is straight-up gold.

Daman0203's tweet photo. Just got into reading, and The Almanack of Naval Ravikant is hitting different. Crazy how much perspective this book packs- every page is straight-up gold. https://t.co/lj7CfkEf1i

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Nikki Siapno

@NikkiSiapno

over 1 year ago

What is Kafka, and how does it work? Apache Kafka is an open source distributed streaming platform designed for building real-time data pipelines and streaming applications. Kafka operates as a distributed pub-sub messaging system. Allowing applications to publish and subscribe to real-time or near-real-time data feeds. The high throughput, scalability, fault-tolerance, durability, and ecosystem Kafka provides have made it a very popular choice for use cases where real-time data feeds are required. The key components of Kafka include: 🔸 Producer Producers publish (write) messages to a Kafka topic. 🔸 Consumer Consumers/subscribers subscribe to topics and process (read) the feed of published messages. 🔸 Broker Brokers are Kafka servers that store data and serve clients. Multiple brokers form a cluster. 🔸 Topic Topics are a feed name or message category to which messages are published by producers. 🔸 Partition Messages are organized into topics, which can then be further divided into partitions. This increases parallelism and scalability allowing consumers to read different partitions at the same time. Kafka can be used for many use cases. A few of the more common use cases include: 🔹 Aggregating data from different sources: Whether it's ETL pipelines, data lakes, or log aggregation; ingesting, organizing, transforming, and distributing data are core functions of Kafka. 🔹 Stream processing: Kafka can be used to build real-time analytics applications. 🔹 Event processing: systems or applications that rely on processing events in real-time such as IoT devices. 🔹 Monitoring: Kafka is well suited for storing logs and metrics, allowing for real-time monitoring and alerts. Designed for fault tolerance, high throughput, durability, and scalability, Kafka serves as an intermediary service for handling large data. While Kafka provides many advantages for building real-time data pipelines and streaming applications, it's not without its drawbacks. The most noteworthy being the layers of complexity it adds to the system architecture. In saying that, if real-time data feed is required, Kafka is a popular choice. ~~ Thanks to our partner FusionAuth who keeps our content free to the community. Almost all auth providers force you into multi-tenant SaaS. FusionAuth gives you full control—self-host, scale, and deploy your way. Try it out (see why dev teams are loving it): https://t.co/UfnLCOBBhO