Sifei Electric participates in energy management systemThe overall architecture follows the concept of "cloud, management, edge, and end". Based on the cloud platform, a "comprehensive perception, intelligent IoT, and data interoperability" urban rail transit energy efficiency data analysis system is constructed. Through intelligent gateway and cloud access of terminal devices, real-time collection and comprehensive analysis of energy consumption data are achieved, accurately grasping the actual situation of line energy consumption.

Cloud container technology

• Extremely lightweight, only packaging necessary bin/lib

• Second level deployment, depending on the image, the deployment time for containers is approximately between milliseconds and seconds (much stronger than virtual machines)

• Easy to transplant, build once, deploy anywhere

• Elastic scaling, Kubernetes container management platform has very powerful elastic management capabilities

Microservices Architecture

• Quick launch, due to the autonomy and independence of business components, new features and applications can be quickly released and launched without worrying about causing widespread impact and ripple effects on other system functions

• Fully utilize hardware resources

• Support independent scaling and recovery, targeted scaling of certain services in the application to solve performance bottlenecks, and the ability to independently replace or restore a component in a microservice

• The advantages of microservice architecture in application development efficiency, stability, and scalability are the standard architecture for cloud applications

Continuous deployment

• Reducing the scope of changes, adopting agile or iterative development means more frequent releases and fewer changes per release compared to traditional waterfall development models. Due to frequent deployment, each deployment will not have a significant impact on the production system, and the application will gradually grow at a smooth rate

• Automation, powerful deployment automation measures ensure the repeatability of deployment tasks and reduce the possibility of deployment errors

• In terms of software development, testing, deployment, and operation processes, it has improved development efficiency, reduced communication costs, and increased deployment and online speed

System overhead

Compared to creating virtual machine instances, it has faster speed, lower performance and space consumption expenses, and reduces hardware resource investment costs.

Deployment efficiency

Traditional virtual machine deployment takes minutes, while container deployment takes seconds, greatly improving deployment efficiency.

portability

Containers can run on almost any platform, including physical machines, virtual machines, public clouds, private clouds, personal computers, etc. They can be directly migrated from one platform to another, which traditional virtual machines cannot achieve.

markStandardization

Most containers are based on open standards and can run on all major Linux systems with good compatibility.

flexibility

Each microservice can be deployed independently, without the need to coordinate the impact of other services on this service. Traditional architecture deployment requires a large application server to support it. The flexibility of microservice architecture enables continuous deployment of systems and improves the responsiveness of subsequent functional extensions.

coupling

Each microservice focuses only on a specific business function, with clear logic and minimal code, making development and maintenance simple. The system is constructed from several microservices and maintained in a controllable state. The traditional single application architecture often leads to a situation of "pulling one thing and activating the whole body", which is not conducive to development and maintenance.