In today’s fast-paced digital economy, businesses are fighting to stay ahead and devise new ways to streamline operations, enhance responsiveness and work with real-time insights. We are now in an era defined by being proactive, rather than reactive. In order to stay ahead, businesses need to enable proactive decision making—and this stems from building an IT infrastructure that provides the foundation for the availability of real-time data.
A core part of the solution needed comes from messaging infrastructure and many businesses already have a strong foundation in place. Among others, IBM MQ has been recognized as the top messaging broker because of its simplicity of use, flexibility, scalability, security and many other reasons. A messaging queue technology is essential for businesses to stay afloat, but building out event-driven architecture fueled by messaging might just be your x-factor.
Messaging that can be relied on
IBM MQ facilitates the reliable exchange of messages between applications and systems, making sure that critical data is delivered promptly and exactly once to protect against duplicate or lost data. For 30 years, IBM MQ users have realized the immense value of investing in this secure messaging technology—but what if it could go further?
IBM MQ boasts the ability to seamlessly integrate with other processing tools with its connectors (including Kafka connectors), APIs and standard messaging protocols. Essentially, it sets an easy stage for building a strong real-time and fault-tolerant technology stack businesses once could only dream of.
IBM MQ is an industry leader for a reason, there’s no doubt about that. Investing in future-proof solutions is critical for businesses trying to thrive in such a dynamic environment. IBM MQ’s 30 years of success and reliability in a plethora of use cases is not something that should be ignored, especially when it has been continuously reinventing itself and proving its adaptability as different technologies have emerged with its flexible deployment options (available on-prem, on cloud and hybrid). However, IBM MQ and Apache Kafka can sometimes be viewed as competitors, taking each other on in terms of speed, availability, cost and skills. Will picking one over the other provide the optimum solution for all your business operations?
MQ and Apache Kafka: Teammates
Simply put, they are different technologies with different strengths, albeit often perceived to be quite similar. Among other differences, MQ focuses on precise and asynchronous instant exchange of data with directed interactions, while Apache Kafka focuses on high throughput, high volume and data processing in sequence to reduce latency. So, if MQ is focused on directed interactions and Kafka is focused on gaining insights, what might the possibilities be if you used them together?
We know IBM MQ excels in ensuring precision and reliability in message delivery, making it perfect for critical workloads. The focus is on trusted delivery, regardless of the situation and provision of instantaneous responses. If combined with Apache Kafka’s high availability and streamlined data collection—enabling applications or other processing tools to spot patterns and trends—businesses would immediately be able to harness the MQ data along with other streams of events from Kafka clusters to develop real-time intelligent solutions.
The more intelligence, the better
Real-time responsiveness and intelligence should be injected as much as possible into every aspect of your technology stacks. With increasing amounts of data inundating your business operations, you need a streaming platform that helps you monitor the data and act on it before it’s too late. The core of building this real-time responsiveness lies in messaging, but its value can be expanded through event-driven architectures.
Consider a customer-centric business responding to thousands of orders and customer events coming through every minute. With a strong messaging infrastructure that prevents messages from falling through the cracks, your teams can build customer confidence through message resilience—no orders get lost and you can easily find them in your queue manager. But, with event-driven technologies, you can add an extra layer of stream processing to detect trends and opportunities, increase your customer retention, or adapt to dynamic pricing.
Event-driven technologies have been emerging in our digital landscape, starting with Apache Kafka as an industry leader in event streaming. However, IBM Event Automation’s advanced capabilities leverage the power of Apache Kafka and help enterprises bring their event-driven architectures to another level through event processing and event endpoint management capabilities. It takes a firehose of raw data streams coming from the directed interactions of all your applications and Kafka connectors or Kafka topics, allowing analysts and wider teams to derive insights without needing to write java, SQL, or other codes. In other words, it provides the necessary context for your business events.
With a low-code and intuitive user interface and functionality, businesses can empower less technical users to fuel their work with real-time insights. This significantly lowers the skills barrier by enabling business technologists to use the power of events without having to go to advanced developer teams first and have them pull information from a data storage. Consequently, users can see the real-time messages and cleverly work around them by noticing order patterns and perhaps even sending out promotional offers among many other possibilities.
At the same time, event endpoint management capabilities help IT administrators to control who can access data by generating unique authentication credentials for every user. They can enable self-service access so users can keep up with relevant events, but they can also add layers of controls to protect sensitive information. Uniquely, it allows teams the opportunity to explore the possibilities of events while also controlling for sensitive information.
Source: ibm.com
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