Kafka is not for you!

Kafka is not for you!

Kafka is widely use as a messaging or Message Broker system. As we all knows that Kafka has high throughput means it can handle millions of requests and data at a time without facing any problem. It provide the amazing scalability powers to you. It retains the messages for a period. It can use for large scale data pipeline processing.

And now you think if Kafka provides many features then why i am saying Kafka is not for you.

  1. Complex setup and management :-
    Kafka required detailed knowledge of its architecture to understand like Topics, Partitions, Replications, Consumers, Groups and Brokers. There are lot of stuff to deal with it.
    Also setting up and managing Kafka cluster along with its dependencies like Zookeeper and K-raft is kind a hectic.

  2. Require High Resources :-
    Kafka need significant amount of memory, CPU and disk I/O to function properly. Which makes it not ideal for low specification machine.
    It demands careful tuning for performance to run Efficiently.

  3. Lack of Advanced Routing :-
    Kafka’s messaging service is based on partitioning. Means in case key were not present then it will assign messages to partition in Round Robin manner.
    Thus Kafka is not Ideal for complex messages routing patterns.

There are many points which i can added in this list but the main idea is to let you know that sometime make things over complicated create a less practical or less optimize server.

There is quote : You can cut the vegetable with Sword but you don’t do that why because vegies can be cut with a simple knife.

Then why do over engineering of less requirement task. Kafka comes with many features but it is also require the resources to handle that features.

So When to use Kafka:

  1. Use Kafka when you followed the Microservice architecture and want to communication with other services.

  2. When you have large amount of users and your system requires to handle millions of Events and Messages per seconds.,

  3. When you want to implement real time data integration or streaming and processing like in Trading app, Netflix and others.

  4. When you want to horizontal scale the server without any fault tolerance.

Thank You for your time….