Why to learn and use Kafka?


Why to learn and use Kafka?

The Story

Suppose Raman wants to build an app named Movile which mainly focuses on streaming movie and series with server in Bangalore.
Initial architecture is straight forward, consisting of one type of target (website) and getting data from one source (server). Deployment was also smooth.

Now Raman wants to deploy mobile app as a new target and not to forget Smart TV. He also wants to get input from user activity about movies to implement recommendation system and multiple other features.

The Problem

As we all know, integrating these features comes with multiple issues and difficulty like different types of data transfer protocols and multiple variety of structured and unstructured data like JSON, CSV, JPEG, MP4, MKV etc.
Not to forget that data source or target structure can also change, which will require changeover of complete architecture.

With all this in mind, Raman approached his friend Aman, Aman introduced him to Kafka

Why Kafka

Kafka allows to decouple data streams and systems, so now source systems will have their data end up in Kafka

These are the list of some of the Kafka features:

  • Scalability: Kafka scales easily without downtime.
  • Volume: Kafka work easily with the huge volume of data streams.
  • Transformations: Kafka offers option to derive new data streams using the data streams from producers.
  • Reliability: Kafka is distributed, partitioned, replicated and fault tolerant.
  • Durability: Kafka uses Distributed commit log, that means messages persists on disk as fast as possible.
  • Performance: Kafka has high throughput. Even if many TB of messages is stored, it maintains stable performance.
  • Extensibility: There are as many ways by which applications can plug in.
  • Replication: By using ingest pipelines, it can replicate the events.

After implementing Kafka, Raman does not have to worry about multiple integration issues while successfully scaling his App up.


While designing a microservices based architecture, any system designer or architect requires to add or integrate multiple different feature and scale them separately.

For this use case, Kafka have solved integration while keeping performance of the system intact like adding a new entry in the pre existing freeway.

Therefore, Kafka is worth giving a shot if you want to scale up and out your system.

Frequently Asked Questions (FAQ)
1. What is Kafka?
   - Kafka is a distributed streaming platform that allows for the decoupling of data streams and systems. It is valuable for handling diverse data types and sources, making it essential for scenarios like building mobile apps, implementing recommendation systems, and more.

2. How can Kafka help in handling different data types and sources?
   - Kafka provides a solution for integrating various data types (JSON, CSV, images, videos, etc.) and handling different data transfer protocols. It allows for seamless data flow from source systems to Kafka.

3. What are some key features of Kafka?
   - Kafka offers scalability without downtime, can handle large volumes of data streams, supports data transformations, is reliable and fault-tolerant, ensures message durability through distributed commit logs, maintains high throughput, and provides extensibility for integrating applications.

4. How does Kafka enhance system performance and scalability?
   - Kafka's distributed, partitioned, replicated, and fault-tolerant architecture enables it to handle large data volumes without compromising performance. It also allows for easy scaling up and out.

5. Can Kafka handle changes in data source or target structure?
   - Yes, Kafka's decoupled architecture allows for flexibility in handling changes in data source or target structure without requiring a complete overhaul of the system's architecture.

6. How does Kafka ensure message durability?
   - Kafka ensures message durability by utilizing a distributed commit log, which means that messages are persisted on disk as quickly as possible, ensuring that they are not lost in case of failures.

7. How does Kafka support replication of events?
   - Through ingest pipelines, Kafka can efficiently replicate events, ensuring that data is available across different parts of the system.

8. Is Kafka suitable for microservices-based architecture?
   - Yes, Kafka is highly valuable in microservices-based architectures, especially when there is a need to integrate multiple features and scale them separately. It helps in maintaining system performance while adding new functionalities.

9. How has Kafka benefited real-world scenarios?
   - Kafka enables seamless integrating of features like mobile and Smart TV apps, implement a recommendation system, and handle diverse data types. It eliminated integration issues and ensured smooth scaling of his application.

10. Should I consider using Kafka for my system architecture?
   - If you're designing a system that requires seamless integration of diverse features and scaling them independently, Kafka is definitely worth considering. Its capabilities make it a powerful tool for handling complex data streams and system interactions.

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