Difference between Resizing, Scaling and Auto-scaling

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What differentiates resizing, scaling, and auto-scaling?

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Scaling and Auto-Scaling Support

Scaling and auto-scaling are available only in the Workspace architecture. Click here to learn more about migrating to Workspaces.

Where can you find these options?

Manual resizing and scaling options are available under the Resize Workspace section, as shown below:

Auto-scaling is available under the Edit Workspace settings:

Resizing

Resizing is achieved by modifying the base size of the compute deployment (for example, from S-12 to S-24). This process will automatically add or remove compute, memory, and cache resources while redistributing data within the workspace to ensure optimal performance.

When data is redistributed during resizing, the time required for a full resize depends on the workspace size and the size of the data working set. This operation is fully online, and the entire process can take anywhere from minutes to hours, depending on data volumes.

Resizing is ideal for workloads that have either grown or shrunk over time and are anticipated to continue operating at the new compute size. For workloads expected to scale up and down rapidly, please refer to the next section, Scaling.

Scaling

Scaling operations are performed by changing the scaleFactor of the deployment. For example, changing the scaleFactor from "1" to "2" or "4". This will automatically increase the amount of vCPU and memory available to workloads from 1x to up to 4x.

This feature is designed to adjust resources up or down to accommodate dynamic changes in workload needs. The time required for this operation to complete will vary depending on workspace size, the number of tables involved, and other factors.

Example:

Autoscaling

Autoscaling is designed to monitor the active compute workload and automatically adjust/scale the deployment based on compute and memory usage. When the workload demands more vCPU or memory than is available, autoscaling will dynamically add compute resources. If the workload decreases and the extra compute is no longer necessary, autoscaling will revert to the base size.

When configuring autoscaling, users can turn the feature on or off and set the maximum amount of vCPUs and Memory to be provisioned (2x or 4x the base amount). This provides dynamic flexibility while allowing users to tightly manage costs.

Autoscaling is ideal for dynamic workloads where the user does not know when peaks in workload may occur and can be turned on or off for each compute deployment independently.

Autoscaling provides three sensitivity levels to handle a workload:

Reference

Workspace Scaling

Scaling Impact on Performance

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