Abstract:
The present invention discloses a cloud infrastructure-based management system and method for maintenance deployment of an application system. A cloud infrastructure-based method for maintenance and deployment of an application system, comprising: obtaining a scheduling deployment policy of an application; obtaining performance of an application instance or task processing state data of the application instance; and performing application scheduling deployment according to the scheduling deployment policy of the application and the performance of the application instance or the task processing state data of the application instance, generating a deployment instruction for the application instance, and completing deployment configuration of the application instance, wherein the deployment instruction comprises an application attribute and a range of attribute values. In this way, the present invention support automatic deployment of an application system, avoiding software re-architecture needed for the application system's migration deployment from a traditional system to a cloud platform.
Abstract:
Some embodiments provide a microservice component-based database system, to split a database kernel into microservice components that can be enabled and run independently and whose functions are decoupled, and implement flexible database assembly and management. The microservice component can be deployed based on a system resource and a service form. The components can collaborate with each other by using a lightweight communication mechanism. A component manager provides capabilities such as registration and deregistration of a service component, component resource management, component fault tolerance, and component upgrade, to implement dynamic management of the component in a running environment. A job scheduler selects, based on a job submitted by a user, an optimal execution path including a plurality of components, and performs resource management and scheduling in a job execution process, to implement load balancing and high availability.