Author: Zen and the Art of Computer Programming
Data Containerization is an IT-related technical concept. One of its proposers, the founder of Docker, first proposed and defined this concept at DockerCon 2013. To put it simply, data and applications are packaged together to form an independent "container", which can be run like an application. One advantage of this is that the same data and applications can be deployed in different environments, reducing the complexity of operation and maintenance. So, what benefits can data containerization bring to enterprises? The author thinks that there are mainly the following points:
① More efficient use of resources: Since each container is a relatively independent process, it can monopolize system resources such as CPU and memory, effectively reducing resource waste; and through horizontal expansion (scale out), multiple sets of Multiple container copies of the same application can effectively use system resources; ② More precise control of application configuration: the isolation feature of the container allows it to configure different parameters, and is not affected by factors such as the host kernel configuration; in addition, the automatic management of the container Tools can also solve the problem of application configuration management; ③ Avoid repeated investment: Containerization can help enterprises save repeated investment in IT resources, such as infrastructure, test environment, development environment, etc.; through centralized management and standardization, containers can also Reduce communication costs between different development teams and shorten the project launch cycle; ④ Improve efficiency: Containerization greatly improves the work efficiency of development, testing and operation and maintenance personnel, because it allows them to start from cumbersome configuration installation, debugging, Freed from publishing and other processes, spend more time on business logic implementation;
All in all, data containerization can help reduce enterprise IT costs, improve product development efficiency, and use resources more effectively.
But how exactly should data containerization be implemented? The author believes that, first of all, it is necessary to integrate the existing IT technology system, process and work of the enterprise