Author: Zen and the Art of Computer Programming
1 Introduction
With the rapid development of Internet business and users' increasingly strong demand for high-speed response and smooth experience, website servers are also rapidly expanding to meet large traffic access while ensuring high availability, scalability and security of the system. The traditional publish-subscribe model architecture can no longer adapt to such changing application scenarios, so many distributed middleware based on Message Queuing (MQ) have emerged. Among them, Kafka is the most popular one. It has a prosperous open source community ecosystem, rich functions, and excellent performance. It is widely used in real-time data processing, log collection, search engines and other fields. On the other hand, microservice architecture is booming, and cloud-native applications based on container technology are becoming mainstream, relying more on orchestration frameworks (Orchestration Frameworks), such as Kubernetes, Docker Swarm, etc. They are all distributed, but deployed in different ways. For new or just getting started developers, this complex architecture, tools and technology may not be familiar. Therefore, how to automate the deployment and upgrade of "pure" Redis to the production environment is an important topic. This article will introduce in detail the automated deployment and upgrade solution based on Redis, and demonstrate through examples how to use the monitoring modules and scripts in Redis to achieve automated deployment.
2. Overview of automated deployment Automated deployment means that developers can automatically complete the deployment process without manually performing complex configuration, installation, construction, testing, release, etc. processes. The goal is to complete deployment tasks as soon as possible after release, improve the delivery quality of software products, reduce the workload of operation and maintenance personnel, and save costs. Here, Redis is a NoSQL database with fast and low-latency characteristics. It can be used as an enterprise-level cache server to store hot data or user-requested data to improve application response speed. If Redis can be deployed into a production environment and automatically deployed and upgraded, it can significantly reduce the risk of manual operations, improve efficiency, improve control levels, and improve IT performance.
Traditional deployment methods mainly includeÿ