When setting up a microservice architecture, one of the major concerns you may have is whether to have the services communicate directly with each other, or whether to use a broker system. It’s easy to choose the broker model as it is more failure resistant. But what if it causes bottlenecks in the system when faced with heavy traffic? This is where Apache Kafka fits in. It is a messaging system designed to collect, hold and dispense enormous amounts of data.

A Kafka-centric microservice architecture uses Kafka as an intermediary for microservices to communicate with each other.

Here’s how you can benefit by using Kafka in your microservice architecture:

Ease of integration:

Apache Kafka is designed for easy integration and connectivity with a number of open-source systems. You can easily expand your architecture by seamlessly connecting to other data systems and getting data flow for further processing. This way you can enhance your features by utilizing ready-made connectors and connecting to various services.

Scalability:

Without incurring any downtime, you can add additional nodes on the fly, allowing Kafka to be scaled-out. Moreover, inside the Kafka cluster, the message handling is fully transparent and these are seamless. As the business services grow, you can expand the ecosystem too without overpowering the infrastructure. Using the multi-tenancy feature it is east]y to make clusters to share.

Fault tolerant:

One of the best advantages of Kafka is it’s fault tolerance. Kafka has an inherent capability, to be resistant to node/machine failure within a cluster. When message load increases or the number of consumers changes, Kafka automatically rebalances the processing load between the consumers.

Durability and reliable:

Durability is critical at the core of the architecture. Here it refers to the persistence of data/messages on disk. Also, messages replication is one of the reasons why messages are never lost. Also the messages are persistent, that makes it more reliable.

Real time handling:

Kafka can handle real-time data pipeline with high throughput, low latency, and guaranteed reliability.

High concurrency:

Kafka is able to handle thousands of messages per second and that too in low latency conditions with high throughput. In addition, it permits the reading and writing of messages into it at high concurrency.

Distributed:

The distributed architecture of Kafka makes it scalable using capabilities like replication and partitioning.

Wrapping Up

In short, microservices is the most flexible way to provide online services for enterprises and businesses. A Kafka is the go-to choice for microservices.

For expert solutions and guidance on Kafka implementation for your software and SaaS, you can opt for a trusted integration solution provider.