Most Common Use Cases of Kafka for Data/MLOps Engineers

Introduction: Kafka has become an essential tool for modern data and ML Engineering, revolutionizing the way organizations handle data streams. In this post, we’ll delve into the most common use cases for Kafka, shedding light on how it’s reshaping data management and stream processing in the tech industry.

Let’s dive into the key use cases:

Website Activity Tracking:

• Originating as the original use case by LinkedIn, Kafka facilitates the seamless tracking of events like page views and conversions.
• Events are efficiently piped to Kafka topics via a gateway, ensuring real-time processing or forwarding to downstream analytical systems.
• Kafka acts as an initial buffer, guaranteeing message integrity and scalability for handling large data volumes.

Database Replication:

• Kafka serves as a conduit for database commit logs, enabling reliable replication and synchronization across multiple databases.
• Committed messages are executed in the same order against a new database, ensuring data consistency and fault tolerance.

Log/Metrics Aggregation:

• Leveraging Kafka for centralized log and metrics collection simplifies monitoring and…