# X Cloud Autoscaling Behavior and Best Practices

## How X Cloud Autoscaling Works

ScyllaDB Cloud continuously monitors your cluster to keep resource usage as
close as possible to a specified target utilization. For example, if you set
a target of 90% storage utilization, the system automatically adjusts
the cluster configuration to try to maintain that level.
This is an ongoing process. If a cluster needs adjustment, ScyllaDB Cloud will
perform a scaling operation.

### Scaling

* **Scaling Up:** If utilization rises above the target threshold, the system
  adds more instances or transitions to larger instance sizes to adjust
  the cluster shape. This usually occurs when utilization exceeds the target
  by more than 5%.
* **Scaling Down:** If utilization falls below the target, the system reduces
  the number of instances or switches to smaller instance sizes to reduce
  costs. This occurs when utilization falls more than 5% below the target.
  The resulting configuration should remain as close as possible to the target
  while factoring in capacity precision.

### Scaling Precision

While the cluster capacity gravitates toward your target, achieving an exact
value is not always possible because scaling occurs in increments fixed  based
on instance capacity. This precision is limited by the size of the smallest
available instance, which, in most cases, is 503 GB. This means that while
a 50 TB cluster might see 1% storage adjustments, a small 503 GB cluster would
scale by 100% increments.

You can restrict this, further reducing the precision of scaling.

## Instance Selection and Optimization

By default, X Cloud uses all instance types within a selected family. In some
cases, you may want to restrict the instance sizes used. This is convenient if
you want to take advantage of specific pricing agreements. However, such
limitations may introduce scaling precision or lead to capacity issues.

### Reduced Scaling Precision

Limiting available instance types can be useful for optimizing the cost, but can reduce scaling granularity.
For example,
disabling the smallest type (e.g., i8g.large) forces the ScyllaDB Cloud to use
larger increments like i8g.xlarge (1006 GB) or i8g.2xlarge (2013 GB), making
scaling of clusters less precise.

### Cloud Provider Capacity Issues

Highly restrictive configurations can expose your cluster to capacity shortages
within specific cloud regions or availability zones. If a cloud provider runs
out of a specific instance size, the ScyllaDB Cloud normally proposes
an alternative configuration to ensure success. However, if you have blocked
those alternatives, reconfiguration may become impossible.

## Recommendations for Optimal Scaling

* **Best Practice**: Allow **all instance types** within a selected family to
  be used in the autoscaling process, ensuring the highest precision and
  stability.
* **Minimum Requirement**: If you have to restrict instance selection, allow
  at least **three instance types** within the family to maintain basic scaling
  flexibility.