Use cases for Apache Kafka: How can you add business value?
Apache Kafka is the leading open source event streaming platform. This platform enables organizations to use real-time data instead of batch data. This new way of using data has a lot of use cases.
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Kafka is a scalable, community distributed event streaming platform and publish-subscribe messaging system. Kafka is used to develop distributed applications and facilitate the implementation of event driven architecture. In this blog, we will take a closer look at the different use cases and applications regarding Apache Kafka.
In this blog you will read the following:
- What is Apache Kafka
- Apache Kafka use case: What is Kafka used for?
- Increase revenue
- Decrease costs
- Mitigate risk
- When not to use Apache Kafka
What is Apache Kafka?
Apache Kafka is an open source event streaming data platform. Kafka was originally developed by LinkedIn, as it expanded on its features LinkedIn donated Kafka To Apache.
How does Kafka operate? Kafka works like most traditional pub-sub message systems in that the platform enables users to publish and subscribe to event streams. Kafka however differs from the more traditional event stream platform in 3 ways;
- Kafka is build as a distributed system that runs as a cluster. This enables the platform to scale and to handle any number of applications.
- Kafka can store data for as long as necessary; most traditional event stream platforms remove messages after the consumer confirms the receiving of messages.
How does Kafka work?
In general, Kafka accepts events written by producers and sends events to consumers. Kafka stores the events or records chronologically in partitions on brokers. Brokers are servers, and multiple brokers make a cluster. A record in Kafka contains information about an event, with each record consisting of a key and value containing event data and headers that can be used for metadata storage These groups are called topics. Consumers get their data by subscribing to specific topics.
Apache Kafka use case: What is Kafka used for?
Now that we have learned about the basic principles of Apache Kafka, we can take a look at the different use cases where event streaming can be beneficial. In general, we can divide the use cases for Kafka into three strategic drivers: increase revenue, decrease costs and mitigate risk. These strategic drives all operate within a certain domain where organizations can benefit from real-time data.
Increase revenue
Increasing revenue is something every commercial organization strives for. When we look at use cases where real-time data can really make a difference, we are looking at the core business platform and the customer experience.
A 360° customer view
As the number of devices and interactions with your brand increases, leveraging this data can be increasingly difficult. Using this data is, however, critical for staying ahead of your competitors. By using an event streaming platform like Apache Kafka you can simplify your data infrastructure, allowing you to combine multiple data sources with ease.
Because most applications are designed to only process a couple of interactions, combining multiple sources enables you to assemble a holistic view of your customers. Having this 360° view of your customer facilitates better customer experience, in turn increasing revenue.
Building a core operations platform
A core operation’s platform functions like a central nervous system within the organization. This platform can consist of a website that serves as a hub for ecommerce, inventory management, payment processing and logistics manager. All these components produce real-time data that can be used to build a bird’s eye view of the business at large. This view helps you to point out places within the organization where there is opportunity to increase revenue.
Real-time app updates
Many organizations have build applications to streamline the experience customers have when using their services. Some businesses have the need to keep customers up to date based on certain events. When you use an event streaming platform, the process of connection data to the right service becomes quite easy. This process can be automated without the need for multiple integrations, everything can be connected using Apache Kafka. These real-time updates based on data can help up-sell your product, in turn increasing revenue.
Decrease costs
When you operate a business, decreasing costs is one way of working towards financial stability. Using real-time data can help you with operational efficiency. In addition, using an event streaming platform can be very helpful when migrating your IT infrastructure to the cloud.
Enabling automation using the Internet of Things
The Internet of Things consists of physical objects with sensors, processing ability that exchange data with one another. To connect all these objects, a centralized event streaming platform is the best solution to take advantage of all the possibilities. Using Kafka it doesn’t matter how many objects are connected, your data infrastructure won’t have to scale. This vast flow of data can be leveraged to transform business, increase efficiency and automate business processes.
Modernizing legacy IT infrastructure
Many enterprises still rely on mainframes for mission-critical applications like inventory control, payroll or financial transactions. For a majority of organizations, these processes still rely on batch processing. Enterprises that want to have real-time access to enable microservices or other business operations need a tool like Kafka for this.
Replacing middleware
Because Kafka enables users to produce data to any number of applications, replacing certain middleware becomes quite easy. Because of this, it is possible to run certain processes in parallel. This enables you to migrate everything without consequences relating to downtime, testing and ensuring being operational.
Mitigate risk
To ensure business continuity and regulatory compliance, mitigating risk is important for any organization. Using a central event streaming platform will make this a lot easier. We have actually written a blog about security for Apache Kafka. You can read the blog here!
Real-time risk analysis and fraud detection
As your infrastructure scales, fraud detection becomes necessary, in some cases even needed to comply with regulation. Combining the latest up-to-date data available at all times enables you to seek out bad actors with great precision. Because the Kafka framework allows you to produce and consume as many topics as you would like, you are able to spot patterns in real time. Something traditional batch processing can’t do without a significant delay. Some specific use cases include: payments fraud, anti-laundering, identity theft and internal theft. Levering real-time fraud detection is especially important within the financial services industry and use cases emerge within the healthcare industry.
Online security
When we talk about online security, we mainly focus on system logs and log aggregation. Engineers may want to use syslog for managing and security auditing. In addition, is can be used for debugging, analysis and general information security. Because it is easy to integrate multiple producers and consumers using Kafka, you can simplify your infrastructure to facilitate security.
When not to use Apache Kafka
As you have red before, Apache Kafka has a lot of use cases. These use cases mostly relate to the need for real-time data and the decoupling of processes. Apache Kafka may however not be the best solution for certain applications. Below, we give two examples of when it might not be the right solution for you.
Using Apache Kafka as your primary database
Even though Apache Kafka can be used as a database and provides you with ACID guarantees (properties to guarantee data validity despite errors, power failures or other difficulties), the platform is not competitive with other databases. Kafka is first and foremost an event streaming platform for integration at scale with zero downtime or data loss. Due to these characteristics, Kafka is mostly used as a central streaming layer. While other databases can build views for their specific use cases or function like a data lake for long-term storage of data, Kafka can not.
The need for “hard” real-time.
Defining real-time is quite difficult, the term often describes different things when talking about different subjects. Kafka is only “soft” real-time and built to work in an IT world. Sometimes there is a need for “hard” real-time, what we mean by this is the need for sub millisecond latency. When you need hard real-time Apache Kafka is not be the right choice for you.
In conclusion
As an event streaming platform, Apache Kafka has numerous use cases relating to increasing revenue, decreasing costs or mitigating risk. Do you want to talk about how your organization can benefit from real-time data to one of our in-house Kafka experts; Click here.
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Apache Kafka can help increase revenue by enhancing customer experience and improving operational efficiency. For instance, Kafka enables organizations to create a 360° customer view by aggregating data from multiple sources, offering a holistic understanding of customer behavior. It also helps in building a core operations platform that unifies ecommerce, payment processing, and logistics, allowing businesses to identify new revenue opportunities. Additionally, Kafka facilitates real-time app updates, helping businesses up-sell and engage customers more effectively through timely and relevant notifications.
Apache Kafka reduces costs by streamlining processes and enabling automation. By centralizing data from Internet of Things (IoT) devices, Kafka allows for automated workflows and real-time decision-making without overhauling the entire data infrastructure. It also supports legacy IT modernization, enabling real-time access to data that was traditionally processed in batches, thereby improving operational efficiency. Moreover, Kafka can replace middleware, allowing for seamless migration to cloud infrastructure without significant downtime or additional costs.
Apache Kafka is highly effective for real-time risk analysis and fraud detection, especially in industries like finance and healthcare. Kafka’s ability to stream data in real-time allows businesses to spot fraudulent activities, such as identity theft or payment fraud, as they occur, which traditional batch processing cannot achieve with the same speed. Additionally, Kafka simplifies log aggregation for online security, facilitating faster detection of security breaches, system vulnerabilities, and other anomalies critical to maintaining business continuity and regulatory compliance.
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