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If you run a system that needs to process numerous events in real time and handle sudden traffic spikes, and you don’t want it to miss a beat, that’s the sort of problem that Apache Kafka was made to fix. It does its work in a few milliseconds.
When a user clicks a button on their screen, multiple systems must spring into action to check permissions, validate data, update records, and send confirmations. Kafka manages this data, ensuring each bit of info gets to its place as fast as possible.
In this article, we’ll describe the core challenges Kafka was designed to address and explain how exactly this solution works.
The Challenges Kafka Aims to Solve
Digital platforms must confront serious challenges on several fronts, and here are some of the main ones:
- Real-time event processing. Users click a button and expect instant results. Whether it’s a purchase confirmation, a status update, or a transaction check, it needs to happen in two seconds or less. The clock starts ticking from the moment the user clicks to the final confirmation. Three seconds of delay is already too long since users are more likely to leave, while business opportunities simply vanish.
- Multi-system distribution. This speed requirement gets exponentially harder when multiple systems are involved. Take sports betting, for instance. One bet sets off a chain of tasks. The system must check the balance, update the odds, log the bet, and send back a message.
- The peak load. Let’s stick with the betting platform example while describing this challenge. During big games, millions of bets can come in every minute, say, due to a sudden goal, an injury, or a controversial referee decision. These surges are intense and totally unpredictable. Yet, the system must handle requests fast, as there’s simply no time for gradual scaling.
While there are different ways to handle data flow between systems, Kafka proves to be the best fit for high-stakes platforms, whether it’s betting, fintech, trading, or e-commerce. Let us show you how this powerful technology works.
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Contact UsHow Kafka Works
Generally, you have several options when choosing the right technology for your system. We’ve worked with them all: RabbitMQ, ActiveMQ, and Kafka. RabbitMQ and ActiveMQ are good at message distribution. However, for higher levels of pressure, you probably will want something a lot more capable.
Apache Kafka is an open-source software platform that processes and moves data instantly between systems. It’s designed to easily scale with growing business needs and can handle millions of updates every second.
Organizations use Kafka for many purposes, such as continuous data movement, system monitoring, and change tracking. The platform stores data securely, keeps working even when problems occur, and smoothly integrates with other business systems.
Kafka works through a system where senders called producers send streams of messages to specific categories referred to as topics. Each topic comprises several storage units called partitions containing the actual messages. Messages are always written at the end of these storage units. A message consists of key, value, and optional header information. A system detects which partition will hold the message that was sent by a producer to a topic.
The rule that only one consumer from each consumer group can read from a partition at any given time ensures messages are processed in the correct order. This setup also enables the system to handle increased workloads by incorporating additional consumers, provided there are sufficient partitions to allocate them.
In addition, Kafka manages data storage with retention policies, which are rules that specify how long messages are retained in a topic due to storage limitations. These policies can vary from one topic to another and operate in two main ways: they either delete data after a specified duration or when the data reaches a certain size.
Two policies can be used together to improve data management. Initially, duplicate messages can be eliminated while retaining only the most recent version of each message. Subsequently, these remaining messages are automatically removed once they exceed the duration specified by the deletion retention policy.
The Power of Right Choices
Kafka is battle-tested in the most demanding scenarios. But perhaps most importantly, Kafka gives businesses room to grow. As your user demands increase and your platform has to expand, you won’t have to make that awful choice between stability and growth. With Kafka, you can scale confidently, add new features freely, and focus on building great products for your users.
IT Outposts has rich experience implementing Kafka for various industries and can help you harness its full potential. Contact our team to discuss how Kafka can make your data infrastructure better!
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Throughout my journey, I have successfully executed and applied numerous strategic approaches that have driven business growth and fortified competitive positions. An integral part of my experience lies in effective business process management, which, in turn, facilitated the adept coordination of cross-functional teams and the attainment of remarkable outcomes.
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