Updated on 2022-12-02 GMT+08:00

Multi-Tenant Model

Related Model

The following figure shows a multi-tenant model.

Figure 1 Multi-tenant model

Table 1 describes the concepts involved in Figure 1.

Table 1 Concepts in the model

Concept

Description

User

A natural person who has a username and password and uses the big data cluster.

There are three different users in Figure 1: user A, user B, and user C.

Role

A role is a carrier of one or more permissions. Permissions are assigned to specific objects, for example, access permissions for the /tenant directory in HDFS.

Figure 1 shows four roles: t1, t2, t3, and Manager_tenant.

  • Roles t1, t2, and t3 are automatically generated when tenants are created. The role names are the same as the tenant names. That is, roles t1, t2, and t3 map to tenants t1, t2, and t3. Role names and tenant names need to be used in pair.
  • Role Manager_tenant is defaulted in the cluster and cannot be used separately.

Tenant

A tenant is a resource set in a big data cluster. Multiple tenants are referred to as multi-tenancy. The resource sets further divided under a tenant are called sub-tenants.

Figure 1 shows three tenants: t1, t2, and t3.

Resource

  • Computing resources include CPUs and memory.

    The computing resources of a tenant are allocated from the total computing resources in the cluster. One tenant cannot occupy the computing resources of another tenant.

    In Figure 1, computing resources 1, 2, and 3 are allocated for tenants t1, t2, and t3 respectively from the cluster's computing resources.

  • Storage resources include disks and third-party storage systems.

    The storage resources of a tenant are allocated from the total storage resources in the cluster. One tenant cannot occupy the storage resources of another tenant.

    In Figure 1, storage resources 1, 2, and 3 are allocated for tenants t1, t2, and t3 respectively from the cluster's storage resources.

If a user wants to use a tenant's resources or add or delete a sub-tenant of a tenant, the user needs to be bound to both the tenant role and role Manager_tenant. Table 2 lists the roles bound to each user in Figure 1.

Table 2 Roles bound to each user

User

Role

Permission

User A

  • Role t1
  • Role t2
  • Role Manager_tenant
  • Uses the resources of tenants t1 and t2.
  • Adds or deletes sub-tenants of tenants t1 and t2.

User B

  • Role t3
  • Role Manager_tenant
  • Uses the resources of tenant t3.
  • Adds or deletes sub-tenants of tenant t3.

User C

  • Role t1
  • Role Manager_tenant
  • Uses the resources of tenant t1.
  • Adds or deletes sub-tenants of tenant t1.

A user can be bound to multiple roles, and one role can also be bound to multiple users. Users are associated with tenants after being bound to the tenant roles. Therefore, tenants and users form a many-to-many relationship. One user can use the resources of multiple tenants, and multiple users can use the resources of the same tenant. For example, in Figure 1, user A uses the resources of tenants t1 and t2, and users A and C uses the resources of tenant t1.

The concepts of a parent tenant, sub-tenant, level-1 tenant, and level-2 tenant are all designed for the multi-tenant service scenarios. Pay attention to the differences these concepts and the concepts of a leaf tenant resource and non-leaf tenant resource on FusionInsight Manager.

  • Level-1 tenant: determined based on the tenant's level. For example, the first created tenant is a level-1 tenant and its sub-tenant is a level-2 tenant.
  • Parent tenant and sub-tenant: indicates the hierarchical relationship between tenants.
  • Non-leaf tenant resource: indicates the tenant type selected during tenant creation. This tenant type can be used to create sub-tenants.
  • Leaf tenant resource: indicates the tenant type selected during tenant creation. This tenant type cannot be used to create sub-tenants.

Multi-Tenant Platform

Tenant is a core concept of the FusionInsight big data platform. It plays an important role in big data platforms' transformation from user-centered to multi-tenant to keep up with enterprises' multi-tenant application environments. Figure 2 shows the transformation of big data platforms.

Figure 2 Platform transformation from user-centered to multi-tenant

On a user-centered big data platform, users can directly access and use all resources and services.

  • However, user applications may use only partial cluster resources, resulting in low resource utilization.
  • The data of different users may be stored together, decreasing data security.

On a multi-tenant big data platform, users use required resources and services by accessing the tenants.

  • Resources are allocated and scheduled based on application requirements and used based on tenants, increasing resource utilization.
  • Users can access the resources of tenants only after being associated with tenant roles, enhancing access security.
  • The data of tenants is isolated, ensuring data security.