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Many organizations today require data to be constantly in motion to ensure service quality and the smooth operation of online applications. Event-driven integration is becoming more prevalent in IT because it offers an efficient method for exchanging information between systems through a robust streaming platform. How exactly does this concept benefit businesses? In the banking environment, there is an increasing demand for digitization across all processes and services. As a result, the number of systems and their data exchanges are growing. At the same time, clients expect products and services to be available at all times with immediate responses to their requests.
Events Carry Information
Alongside established trends in integration, such as decentralization, containerization, API management, and the creation of smaller, more flexible solutions, event streaming is another topic that requires attention. It is an architectural and technological concept that addresses the growing demands within the integration sphere, particularly in event-driven integration.
In this integration model, an event is defined as the description of something (a fact) – for example, a customer address or an accounting balance. It also includes notifications of a status change, such as a change of customer address, exceeding an allowed limit, or various instructions for action within a system.
Managing Event Streams with Apache Kafka
One effective way to manage and process events is through the use of a data streaming platform. Apache Kafka, an open-source distributed streaming platform, has become the predominant technology in this area. It can be used to create applications and feeds for real-time streaming data.
Apache Kafka was developed by engineers at LinkedIn who needed a tool for the fast, secure, and scalable transfer of large volumes of data worldwide. The integration tools available at the time did not adequately meet these requirements. Today, Kafka is used across various industries and companies, from medium-sized businesses to global corporations.
“When utilizing this streaming platform as a backbone for integration, service and microservice systems can exchange events in real time, creating new events in response to what the end user is doing in the application,” explains Petr Dlouhy, an integration expert at Trask, a leading IT firm in Central Europe.
“For instance, when an item is added to the cart in an e-shop, an event can trigger the creation of updated cart contents, set a new corresponding price, and update the stock. Kafka also enables failover mode 24/7, securely storing events with their data in the Kafka cluster, making them available to multiple applications and services,” adds Dlouhy.
This is essential, as today’s clients expect services to run without interruptions, be scalable, and address needs immediately.
Several Benefits of Event Streaming Based on Apache Kafka
- Real-time reaction to events across digital channels: For example, offering personalized services such as insurance proposals in mobile banking when a credit card purchase occurs.
- Real-time Fraud Detection: Analyzing multiple streams of transaction data to identify unusual patterns or anomalies, allowing swift action to prevent fraudulent activities.
- Personalized Customer Experiences: Collecting and processing real-time customer data enables businesses to deliver personalized offers, product recommendations, and proactive customer service.
- Managing risk and compliance: Continuous monitoring of transaction data can flag potential issues, ensuring regulatory compliance and timely intervention.
- Operational Efficiency and Performance Monitoring: Tracking and analyzing operational data across various functions allows for proactive identification of inefficiencies and real-time monitoring to ensure smooth operations.
These advantages are made possible by the asynchronous nature of communication between systems in Kafka. Systems remain loosely coupled and independent, allowing for easy updates, scalability, and replication across the globe to meet increasing client demands.
However, before beginning any project, it is critical to conduct data analysis, select appropriate integration patterns, define transmission channels (topics) in Kafka, and establish schemas. Managing potential errors during the creation and reading of messages is also essential – as with any integration, proper design is key to success.
Situations Where Event-driven Architecture Excels
Kafka’s use is particularly relevant when there is a need to process large amounts of data in real time. Event-driven integration thrives in environments that employ microservice architecture, offering scalability, fault tolerance, and agility.
Typical examples include log processing (both application and audit), user activity monitoring, and the online evaluation of client offerings. In particular, "classic" application integration requires careful planning of event distribution and consumption, as implementing event streaming for existing systems can be more complex than other types of integration.
Successful implementation of these systems provides significant long-term benefits, such as faster responses to client requests, effective scaling as the client base grows, and ensuring stable, continuous service availability.
Organizations seeking to improve real-time data processing and enhance flexibility should consider partnering with an experienced IT provider that can deliver tailored solutions to foster growth and innovation.
Author
Contact Info:
Name: Martin Citron
Email: Send Email
Organization: Trask
Website: https://www.thetrask.com/blog/streams-of-events-are-changing-the-integration-paradigm
Release ID: 89144751
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