Unlock Scalable Multi‑Cluster Management with Container‑Based PaaS

Using container technology to build a PaaS (Platform as a Service) cloud platform, this solution demonstrates centralized resource management, dynamic allocation, monitoring, sharing, and scheduling, as well as unified application deployment and business continuity, achieving high availability across multiple data centers and adapting system architecture for the cloud era.

By introducing Docker, Kubernetes and a micro‑service architecture, existing applications are split into smaller, interrelated services that are containerized for packaging, deployment, and control. These services are built around business capabilities, can be deployed independently, and allow differentiated management strategies for different micro‑services.

The container‑centric framework meets current business system needs while providing a forward‑looking, advanced technical foundation for rapid future growth. The architecture is divided into several layers:

1) Resource Management Layer

OpenStack or a bare‑metal resource pool (IaaS) provides interfaces for upper layers to acquire resources.

2) Common Service Layer

Container services based on Docker and Kubernetes deliver platform services, on which foundational and user‑defined services are deployed. Micro‑service composition and orchestration expose business‑level service bundles via REST APIs.

3) Application Layer

This layer offers portals for user access and operations management, typically via web services or REST APIs for browsers, smart terminals, or external systems.

Docker runs on Linux hosts, using kernel isolation to create lightweight containers that are faster to start, mask environment differences, and simplify migration and scaling, improving development, testing, deployment, upgrade, and maintenance efficiency.

Kubernetes, built on container technology, provides comprehensive cluster management capabilities including multi‑level security, multi‑tenant support, service registration and discovery, built‑in load balancing, fault detection and self‑repair, rolling upgrades, online scaling, automated resource scheduling, and fine‑grained quota management.

Application Splitting and Service Deployment

The PaaS platform adopts a micro‑service architecture with containerization for design, orchestration, authorization, and configuration, decoupling tightly coupled applications. Different deployment strategies are used based on usage frequency and service call overhead:

HTTP/SOAP applications are deployed with open‑source cache clusters, bundling the application and MySQL in a single image and using third‑party caches for session data, enabling rapid horizontal scaling for high‑traffic scenarios.

Pure compute applications without databases (e.g., DCC modules) are containerized to provide massive compute power, with multi‑node master deployment ensuring high availability.

MySQL clusters are containerized with master‑slave replication and shared storage backups, achieving high reliability, security, and near‑bare‑metal performance.

These fine‑grained micro‑services are lightweight and flexible, supporting agile delivery across diverse scenarios. Container‑based service design, orchestration, and configuration eliminate tight coupling, providing a solid technical foundation for system upgrades and extensions, greatly enhancing operational efficiency and performance.

Unified Management of Multi‑Cluster Resources

The PaaS platform achieves unified resource management through:

Certificate‑authenticated Kubernetes API servers that ingest cluster node counts, configurations, and data‑center details.

Binding clusters to tenants, allocating clusters to specific tenants, and isolating resources and access permissions per tenant.

Allowing tenants to partition cluster resources further, deploying varied applications, and implementing domain isolation (e.g., placing web and proxy services in DMZ/internet zones, core services in central zones with Mesos for large compute clusters).

Using Kubernetes multi‑cluster management, operators can easily monitor resource status, cluster counts, machine configurations, data‑center conditions, and utilization, significantly improving management and monitoring across clusters and data centers.

High Availability Across Multi‑Cluster and Multi‑Data‑Center Environments

Key high‑availability scenarios include:

Automated service deployment across data‑center clusters via Kubernetes, allowing proportional container instance distribution (e.g., 6:4 between clusters A and B).

Gray‑scale upgrades where new versions are first deployed to a subset of clusters before full rollout.

Dynamic scaling during peak loads, automatically extending services to disaster‑recovery data centers.

Automatic failover to disaster‑recovery data centers when the primary center fails.

Overall, a container‑based PaaS enables centralized management of complex multi‑cluster environments across networks and data centers, accelerates software version releases, provides comprehensive monitoring, and supports flexible horizontal scaling, while ongoing research is needed to standardize and further evolve container technologies.