Overview

Cloud Native GIS refers to the GIS-related technologies designed and optimized for the cloud environment. Based on the microservice architecture, and taking the container as the deployment carrier, it can realize autopatch, operation and maintenance management, and make better use of the cloud platform to enable more efficient, flexible, up-to-date, and stable GIS systems.

SuperMap Cloud Native GIS divides the traditional GIS monolithic application into multiple independently deployable microservice, which achieves more finegrained elastic scaling and flexible deployment of GIS, deploys microservice into containers instead of virtual machines, reduces resources occupancy and realizes the rapid scaling; through autopatch technology of GIS containers, dynamic resource scheduling, the cloud environment differences shielding, management and migration costs reducing can be realized. By applying cloud native, GIS system developers can focus on the business to response more quickly to customer needs.

Highlights

The storage and distributed calculation of GIS data Cloud Native

  • Supports multi-categories spatial data distributed storage to improve the computational efficiency of massive spatial data.
  • Supports distributed processing and analysis of massive classical spatial data to achieve the magnitude performance improvement.
  • Supports a variety of public cloud storage services, cloud databases to take advantage of the cloud platform.

GIS microservice architecture and service management

  • Supports GIS function split into microservice and elastic scaling.
  • Achieves comprehensive microservice for maps, 3D, big data, and AI.

Container-based multi-node deployment and elastic scaling

  • Supports containerized deployment, faster deployment speed and lower performance cost than virtual machines.
  • Provides general autopatch based on Kubernetes, adapts various public and private clouds.
  • Supports GIS service node management for multinode deployment.
  • Supports GIS node rolling upgrade, elastic scaling and failure recovery.
  • Provides built-in distributed storage resource pool and computing resource pool (HBase, Spark, etc.).

Integrated intelligent operation and maintenance and management

  • Realizes real-time monitoring of all microservice resources.
  • Supports centralized management of GIS logs.
  • Supports visitor statistical analysis to guide GIS background optimization.
  • Supports self-repair, microservice can automatically recover from machine failure.
  • Supports seamless upgrade, partial upgrade / rollback without interrupting service.