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Simplify Your Work on Integrations with Apache Kafka
Apache Kafka Message Broker is a distributed streaming platform that can handle millions of events daily. Kafka guarantees an easy integration into the project infrastructure, as well as system reliability and scalability.
Kafka Connect is an Apache Kafka framework that provides scalability and flexibility for moving data between Kafka and other repositories. This framework allows the broker to act as an ESB service bus.
Project Architecture with Kafka
Apache Kafka Features
Stream Data Processing
The Kafka Real-Time Stream Processing works with the real-time data at the rate of message generation. The message processing is continuous and without blocking. Many business processes are also continuous and don't need a response to start the processing. Streaming Data is essential for such business processes as reporting suspicious transactions or tracking mail deliveries.
Tracking the App Activity
Any messages appearing in the application can be published in a special Kafka topic. It might be any document in the ERP system or any user action on the website, including clicks, adding to favorites, adding/removing from the Cart, filling in forms, viewing pages (and a visit depth), can be sent and distributed by the specified Kafka topics. So, other topics (consumers) can subscribe to the necessary topics for various purposes, such as monitoring, analysis, reporting, personalization, etc.
Logging and Log Records Monitoring
Kafka provides the opportunity for the logging and log records monitoring. Log records can be published in Kafka topics, and logs can be stored and processed in the cluster for as long as it is necessary. If you have a special monitoring app, it will be able to get data from Kafka topics in the on-line mode.
All Kafka messages are added to the log (saved to a drive) and stored until the moment of clearing the log history, which a user sets in advance. Due to this feature, Kafka can be used as a reliable source of data (unlike RabbitMQ, which deletes messages right after delivery).
Apache Kafka Advantages
One of the main Kafka's advantages is its reliability. For example, if one of the Kafka brokers goes down for some reason, it will redirect the entire data flow to other brokers and automatically distribute the load between them, thus maintaining the system's normal operation.
Apache Kafka allows users to process any data volumes. You can start working with one broker to test the Kafka capacities, and then increase the number of brokers to operate the system in full. You can also increase the volume during the current number of brokers — it won't have any impact on the overall system operability.
Due to its high throughput, Apache Kafka can process more than a million events per second. This makes Kafka the most popular message broker for working with big data.
A major manufacturer and retailer of seating and cabinet furniture, mattresses and sleep products.
For such a big company with multiple information systems, a point–to-point integration is not the best choice. The customer wanted a light data migration mechanism with a simple logic with a sole function of transmitting data from one system to another. At the same time, it was necessary to take into account the company's need for systems' weak interconnection, so that it was possible to remove or replace one of the systems in such a way that other systems were not affected.
To cope with the customer's task, we've integrated Kafka into the enterprise infrastructure of the project. Kafka is a distributed system that allows users to exchange messages and provides permanent data storage capacities.
We Discuss Apache Kafka on our YouTube Channel
Alternative Options — Talend, Mule, WSO2
Talend ESB is a universal tool for fast integration of services and applications. Installing and configuring Talend allows developers to focus on the project's business logic, rather than on the complexity of technologies.
Comparison of ESB Solutions. Check the Video on our YouTube Channel
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