What is Apache Kafka, Why and When to use Kafka. Lesson 1

AI

After an outcry, OpenAI swiftly rereleased 4o to paid users. But experts say it should not have removed the model so suddenly.

OpenAI’s decision to replace 4o with the more straightforward GPT-5 follows a steady drumbeat of news about the potentially harmful effects of extensive chatbot use. Reports of incidents in which ChatGPT sparked psychosis in users have been everywhere for the past few months, and in a blog post last week, OpenAI acknowledged 4o’s failure to…

AI

‘Cheapfake’ AI Celeb Videos Are Rage-Baiting People on YouTube

“They’re tweaking my voice or whatever they’re doing, tweaking their own voice to make it sound like me, and people are commenting on it like it is me and it ain’t me,” Washington recently told WIRED, when asked about AI. “I don’t have an Instagram account. I don’t have TikTok. I don’t have any of…

AI

GPT-5 Doesn’t Dislike You—It Might Just Need a Benchmark for Emotional Intelligence

Since the all-new ChatGPT launched on Thursday, some users have mourned the disappearance of a peppy and encouraging personality in favor of a colder, more businesslike one (a move seemingly designed to reduce unhealthy user behavior.) The backlash shows the challenge of building artificial intelligence systems that exhibit anything like real emotional intelligence. Researchers at…

AI

OpenAI Designed GPT-5 to Be Safer. It Still Outputs Gay Slurs

OpenAI is trying to make its chatbot less annoying with the release of GPT-5. And I’m not talking about adjustments to its synthetic personality that many users have complained about. Before GPT-5, if the AI tool determined it couldn’t answer your prompt because the request violated OpenAI’s content guidelines, it would hit you with a…

Introduction

To truly master a technology like Apache Kafka, we must first understand its purpose, origins, and practical applications. This article explores why Kafka exists, its history, the companies leveraging it, and the scenarios where it shines, drawing insights from the official Apache Kafka introduction (https://kafka.apache.org/intro).

What is Apache Kafka?

Apache Kafka is an open-source distributed event streaming platform designed for high-throughput, fault-tolerant, and scalable processing of real-time data feeds. As described on the official Kafka website, it allows systems to publish, subscribe to, store, and process streams of records with low latency. Kafka acts like a high-speed data pipeline, connecting producers (data sources) to consumers (data processors or storage systems) efficiently.

History of Kafka

Kafka was created at LinkedIn in 2010 by Jay Kreps, Neha Narkhede, and Jun Rao to address the need for a unified system to handle massive real-time data streams, such as user activity and operational metrics. Traditional messaging systems couldn’t scale to meet LinkedIn’s demands, leading to Kafka’s development. It was open-sourced in 2011 under the Apache Software Foundation and has since become a cornerstone of modern data architectures, supported by a robust community and Confluent, a company founded by Kafka’s creators.

Who Uses Kafka?

Kafka powers data-intensive operations at major companies, as highlighted on the Apache Kafka website. Notable users include:

LinkedIn: Manages activity streams and metrics.
Netflix: Powers real-time recommendations and system monitoring.
Uber: Processes ride and driver data for analytics.
Airbnb: Handles booking and user interaction events.
Walmart: Supports real-time inventory and e-commerce transactions.
Goldman Sachs: Manages financial transactions and market data.
These organizations rely on Kafka’s ability to process billions of events daily with reliability and scale.

Why Use Kafka?

Kafka’s design, as outlined on its official page, makes it ideal for real-time data streaming. Its key strengths include:

Scalability: Kafka distributes data across clusters to handle massive volumes.
Durability: Persistent storage allows data replay and fault tolerance.
Low Latency: Enables real-time processing for time-sensitive applications.
Flexibility: Supports diverse use cases, from messaging to event-driven architectures.

When to Use Kafka

Kafka excels in scenarios requiring real-time data streaming and processing. The Apache Kafka introduction page emphasizes its role in building real-time streaming data pipelines and applications. Key use cases include:

Real-Time Financial Transactions: Processes payments and trades in stock exchanges, banks, and insurance firms with speed and reliability.
Logistics and Fleet Tracking: Tracks vehicles, shipments, and fleets in real time for logistics and automotive industries.
IoT Data Processing: Captures and analyzes sensor data from devices in factories or wind parks for predictive maintenance.
Customer Interaction Tracking: Enables retail, hospitality, and mobile apps to collect and respond to customer orders instantly.
Healthcare Monitoring: Monitors patient data in hospitals to predict and address emergencies.
Enterprise Data Integration: Connects data across company divisions for unified access and processing.
Event-Driven Architectures: Serves as the foundation for data platforms, microservices, and real-time analytics.

Conclusion

Apache Kafka, born at LinkedIn to solve large-scale data streaming challenges, is a powerful platform for real-time data processing, as evidenced by its adoption by companies like Netflix and Uber. Its scalability, durability, and flexibility make it ideal for use cases like financial transactions, IoT, and event-driven systems.

Reference:

Apache Kafka. (2025). Introduction. Retrieved from https://kafka.apache.org/intro

Source link