Apache Kafka is a distributed data streaming platform that can publish, subscribe to, store, and process streams of records in real time. It is designed to handle data streams from multiple sources and deliver them to multiple consumers. In short, it moves massive amounts of data—not just from point A to B, but from points A to Z and anywhere else you need, all at the same time.
Apache Kafka is an alternative to a traditional enterprise messaging system. It started out as an internal system developed by Linkedin to handle 1.4 trillion messages per day, but now it's an open source data streaming solution with application for a variety of enterprise needs.
Apache Kafka is built into streaming data pipelines that share data between systems and/or applications, and it is also built into the systems and applications that consume that data. Apache Kafka supports a range of use cases where high throughput and scalability are vital. Since Apache Kafka minimizes the need for point-to-point integrations for data sharing in certain applications, it can reduce latency to milliseconds. This means data is available to users faster, which can be advantageous in use cases that require real-time data availability, such as IT operations and e-commerce.
Apache Kafka can handle millions of data points per second, which makes it well-suited for big data challenges. However, Kafka also makes sense for companies that are not currently handling such extreme data scenarios. In many data processing use cases, such as the Internet of Things (IoT) and social media, data is increasing exponentially, and may quickly overwhelm an application you are building based on today's data volume. In terms of data processing, you must consider scalability, and that means planning for the increased proliferation of your data.
IT Operations is all about data. IT Operations needs access to the data, and they need it quickly. This is the only way to keep websites, applications, and systems up and running and performing at all times. Apache Kafka is a good fit for IT Operations functions that rely on collecting data from a variety of sources such as monitoring, alerting, and reporting; log management; and tracking website activity.
Internet of Things
According to Gartner, IoT is expected to include more than 20 billion devices by 2020. The value of IoT is the actionable data generated by this multitude of sensors. Apache Kafka is designed for scalability to handle the massive amount of data expected from IoT.
E-commerce is a growing opportunity for using Apache Kafka, which can process data such as page clicks, likes, searches, orders, shopping carts, and inventory.
Kubernetes is the ideal platform for Apache Kafka. Developers need a scalable platform to host Kafka applications, and Kubernetes is the answer.
Like Apache Kafka, Kubernetes also makes your development process more agile. Kubernetes—the technology behind Google’s cloud services—is an open source system for managing containerized applications, and it eliminates many of the manual processes associated with containers. Using Apache Kafka in Kubernetes streamlines the deployment, configuration, management, and use of Apache Kafka.
By combining Kafka and Kubernetes, you gain all the benefits of Kafka, and also the advantages of Kubernetes: scalability, high availability, portability and easy deployment.
The scalability of Kubernetes is a natural complement to Kafka. In Kubernetes, you can scale resources up and down with a simple command, or scale automatically based on usage as needed to make the best use of your computing, networking, and storage infrastructure. This capability enables Apache Kafka to share a limited pool of resources with other applications. Kubernetes also offers Apache Kafka portability across infrastructure providers and operating systems. With Kubernetes, Apache Kafka clusters can span across on-site and public, private, or hybrid clouds, and use different operating systems.