Apache Kafka deployments are used by thousands of businesses worldwide. As an open-source distributed event streaming platform, companies can build high-performance data pipelines, analytics, and more, utilizing real-time and batch data processing. There is arguably no better choice than a free message broker that prioritizes high throughput, reliability, availability, and low latency.
Here is how to use Apache Kafka for business.
What Is Apache Kafka?
Understanding the core components of Apache Kafka is essential for any business. It should leverage this platform’s capabilities and integrate Kafka into its existing IT infrastructure.
Producers are clients who publish records for Kafka, driving data streams into the system. Topics, essentially categorizing messages, are divided into partitions to distribute the load across multiple servers. Consumers subscribe to these topics and processing the incoming stream of published messages.
Brokers play a crucial role as the servers in this setup. A single Kafka server is a broker responsible for receiving messages, assigning offsets, and committing data to storage. Clusters consist of multiple brokers working together to maintain load balance and ensure smooth operation. Partitions manage the sequence of messages, each identified by a unique offset or sequential ID.
Key Features for Business
Kafka stands out for its impressive features. It can handle large volumes of data effortlessly, allowing you to process massive amounts of information without hitting limits. Fault tolerance is another significant feature. By replicating data across multiple brokers, Kafka reduces the risk of data loss. Even if one broker fails, high availability remains intact.
One of its strengths is its scalability. You can scale your Kafka environment up or down without downtime. Durability is also ensured through a commit log that stores data on disk. If in-memory data gets erased, it isn’t completely lost.
Large Amounts of Messages
Create real-time data pipelines and streaming applications where high volumes of data are processed and stored. Kafka is different from your traditional message broker. Its architecture is more robust and scalable, with a built-in partitioning system, parallel processing, and elevated performance. This ensures application logs can be closely monitored.
Create and Manage Multiple Databases
Every business needs a strong and secure database that’s easy to monitor and manage, whether for customer relationship management, enterprise resource planning, or general use. Make infrastructures plug-and-play with messaging queues, file systems, and more for CRM, ERP, and other systems.
Track User Activity
Apache Kafka is popular for businesses because it tracks user activity on websites in real time. Monitor page clicks, views, and interactions. This stream of event data can be processed and analyzed as it occurs, enabling enterprises to better understand customer behaviour and optimize user experience.
Collect and Monitor Metrics
For software and hardware systems, Kafka collects operational metrics for monitoring. Prioritize system health, performance, and availability. Take the high-frequency data being written and funnel it into analytical tools for all sorts of benefits, such as proactive alerting, trend analysis, and performance optimization.
Monitor Application Logs
Applications, servers, and systems generate piles of log data. Use Kafka as a centralized hub to collect logs from multiple sources and filter them into the same monitoring and analysis system. This keeps log data management simple, allowing you to store, search, and troubleshoot as needed efficiently.
Identify Emerging Trends
Leverage Kafka to build processing pipelines that filter, transform, and enrich real-time data streams to generate immediate insights and trends. This can be proposed in various ways, including integrating Kafka with frameworks like Apache Flink or Kafka Streams for more features. This is how Kafka is used in the finance sector.
Event Sourcing for Audits
Kafka is a great platform for event sourcing. Events are stored in topics that can be used to replay historical events and rebuild an application state. This can assist with debugging, forecasting, or reconstructing. In this context, Kafka is often used for auditing, compliance checks, and data consistency across distributed systems.
Data Between Microservices
Apache Kafka’s ability to handle vast data streams with reliability and unparalleled speed makes it easy to sort data between microservices. Use it as your centrepiece to communicate asynchronously through events, decoupling services in an architecture encompassing every utility you use.
A Tool of Strategy
There are endless ways to use Apache Kafka. Kafka has limitless forecasting and strategizing potential. It can generate reports based on analytics, improve customer service, increase operational efficiency, monitor cloud-based data storage services, detect fraud, uphold security standards, and more. Kafka is central to building business strategies based on highly accurate data analytics.
