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What Are the Scenarios of Resizing a Cluster, Changing the Node Flavor, Scale-out, and Scale-in?

Resizing a cluster has a great impact on your workloads. It is similar to migrating an old cluster to a new one, with changes on nodes and specifications. You are advised to perform lightweight operations, such as scale-out, scale-in, and flavor change. The following table lists the application scenarios of the cluster modification options.

Table 1 Cluster modification options

Option

Applicable Scenario

Remarks

Scale-out

If your business grows and you have higher requirements on storage capacity and performance, or the CPU of your cluster is insufficient, you are advised to scale out your cluster.

Nodes cannot be added to a hybrid data warehouse (standalone).

Scale-in

During off-peak hours when a large amount of cluster capacity is idle, you can reduce the number of nodes to reduce costs.

A hybrid data warehouse (cluster mode) cannot be scaled in to a standalone cluster.

Changing the Node Flavor

This option changes cluster flavors (including CPU, memory, and others) to meet service requirements. It does not change the number of nodes.

Currently, you can only change the flavors of cloud data warehouse clusters and stream data warehouse clusters that only use ECS and EVS resources for computing and storage.

Changing all specifications

You can resize your cluster when:

  • Your clusters are BMS clusters or they do not support flavor change.
  • You want to change the cluster topology instead of scale-out or scale-in which simply adds nodes or delete nodes ring by ring.
  • Your cluster is aged and you want to change it to a new cluster without migrating data.

Currently, only standard data warehouse clusters are supported.
Parent topic: Cluster Management