Author: Zen and the Art of Computer Programming
With the massive growth of business data and the continuous emergence of various new equipment, software, and Internet applications, traditional stand-alone computing cannot meet the needs of business processing. At the same time, the emergence of big data platforms provides a more efficient and convenient solution. How to deploy a distributed and elastic microservice architecture on a big data platform becomes the key. This article will introduce the microservice architecture based on Kubernetes and Apache Flink.
Apache Flink is an open source, high-throughput, distributed streaming data processing engine designed for highly flexible computing in real-time, interactive, batch, machine learning and other scenarios. Through Apache Flink, users can easily implement a real-time analysis system. Flink can provide a powerful fault tolerance mechanism and horizontal expansion capabilities, so it can be used to process real-time event stream data, as well as fast query processing of large data sets. Due to its wide range of features and rich ecosystem, Apache Flink has been adopted by several enterprises, including Netflix, Twitter, Uber, Datadog, etc.
Kubernetes is an open source container orchestration system (Orchestration System) launched by Google in 2015. It allows users to define, schedule, and manage cluster workloads, enabling automated deployment, scaling, and management of applications in cloud platforms. Kubernetes is scalable and elastic, can cope with complex environmental changes and provide high availability, so that developers and operation and maintenance personnel can focus on application development, testing and release processes, thereby improving the quality of software.
Based on the combination of these two open source systems, Kubernetes can be used to deploy a microservice architecture for streaming data processing on a big data platform. The architecture consists of multiple layered services, each composed of one or more containers. Communication between services is done through asynchronous message queues. In addition, Apache Flink can also be used as the computing engine on the big data platform to coordinate workloads between services at each layer.
This article focuses on how to deploy streaming data processing microservice architecture using Kubernetes and Apache Flink. After reading, readers should be able to understand how to use two popular and open source software to build a distributed and elastic microservice architecture