5 Advantages of a Kafka-centric Microservice Architecture

Application architecture is changing from monolithic enterprise systems to flexible, scalable, event-driven methods. Welcome to the microservices era. In this article, we’ll look at why Apache Kafka is an excellent choice for microservices. System architects and executives at both large and small businesses confront a challenge when it comes to creating a microservices system to support their operations. One of the first big considerations you’ll make when building up a microservice architecture is whether to have the services communicate directly with one another or to use a broker system. You’ve probably opted for the broker model since it’s more flexible and resistant to failure. However, if traffic is excessive, you may be afraid that the broker will constitute a bottleneck in the system. Let’s introduce you to Apache Kafka®, a distributed partitioned commit log service that functions similarly to a messaging system but with its own distinct personality. Kafka was created at LinkedIn to ingest event data and is designed to collect, hold, and distribute massive amounts of information.

“More than 80% of all Fortune 100 companies trust, and use Kafka.”

Why Kafka is used in Microservices:

The goal of Apache Kafka is to solve the scaling and reliability issues that hold older messaging queues back. A Kafka-centric microservice architecture uses an application setup where microservices communicate with each other using Kafka as an intermediary. This is achievable thanks to Kafka’s publish-subscribe approach for handling record writing and reading. The publish-subscribe model (pub-sub) is a communication strategy in which the sender sends events — whenever events are available — and each receiver chooses which events to receive asynchronously. Let’s have a look at why Kafka is such an excellent microservices platform.

Why should you put Kafka at the center of your microservice architecture?

1. The Kafka environment
   Apache Kafka is built for easy integration with a variety of open-source platforms, and the ecosystem continues to grow year after year. We’d even go so far as to claim that Kafka works best when combined with tools like analytic engines and search engines. You may quickly connect Kafka to other data systems with Kafka Connect, allowing data streams to flow with minimal latency for consumption or additional processing.
   
   This allows you to extend your design to a large open-source ecosystem of ready-to-use connectors to a variety of services, practically all of which are free.
   
   
2. Easy Integration to existing systems
   Choosing Kafka doesn’t mean you have to abandon all you’ve done previously. Combining Kafka with other systems is also applicable to systems you already have.
   You can use Kafka to send all of your data to legacy systems, or just a part of it, to ensure backward compatibility or to keep using systems you’ve already invested in.
   
   
3. Access control with advanced features
   Although the data you process may be sent to several endpoints, Kafka allows you to manage access to it through a single centralized approach. Only specified queues are written to and read from by producers and consumers. This serves as an effective access control method without the need for a separate authentication structure to be built on top.
   
   You can increase the security of your system by restricting access to business-critical or classified components with ACLs. At the same time, you may empower people by providing them with data that they might not otherwise have access to. Data scientists may, for example, examine the influence of error reporting and website analytics on customer satisfaction.
   
   
4. Fault tolerance and scaling through clustering
   The clustered design of Kafka makes it fault-tolerant and scalable. Kafka will automatically equalize the processing burden between the consumers if the message load grows or the number of Kafka consumers varies. Simply add nodes to boost throughput and scale up your services.
   
   It’s also worth noting that this eliminates the requirement for any external High Availability solutions.

5. Any content can be stored and processed
   
   Kafka is unconcerned with the content of the messages it keeps, therefore it can be used for anything. This implies you can add any type of producers and consumers to the mix as your business’s demands evolve. Without more infrastructure investments in service data processing, your company may expand and diversify.
   
   

Summing Up

The strong and scalable Kafka is the best choice for the majority of microservices use cases. It solves many of the challenges with microservice orchestration while providing features that microservices strive for, such as scalability, efficiency, and speed. Not only does Kafka provide high availability, but it also ensures that outages are minimized and that errors are handled gracefully with minimal service interruption. The capacity of Kafka to hold data for a specified amount of time is crucial. You can use this feature to rewind and replay events as needed. With each passing day, event-driven architecture grows in popularity. This isn’t just a coincidence. From the standpoint of software developers, it provides an efficient technique of connecting microservices, which can aid in the development of future-proof systems. Furthermore, event-driven architectures become more flexible, resilient, and dependable when combined with modern streaming data tools like Apache Kafka. Our software engineers are eager to help you find and implement the technology stack best suited to your business needs. Contact us to take the next step in building out your organization’s data streaming infrastructure.