Scaling out refers to adding more nodes or clusters to a system to handle increased workload. In Snowflake, increasing the maximum number of clusters in a Multi-Cluster Warehouse is an example of scaling out because it adds more compute resources (clusters) to distribute the workload.
Snowflake supports two ways to scale warehouses:
Scale up by resizing a warehouse.
Scale out by adding clusters to a multi-cluster warehouse (requires Snowflake Enterprise Edition or higher).
Scaling Max Clusters.
Stephen Okon
Increasing the maximum number of clusters in a Multi-Cluster Warehouse is an example of:
A. Scaling rhythmically
B. Scaling max
C. Scaling out
D. Scaling up
The correct answer is B. Scaling max.
Scaling max refers to increasing the maximum limit of resources that can be allocated to a system or application. In the context of a Multi-Cluster Warehouse, increasing the maximum number of clusters would require more resources to be allocated to the system in order to accommodate the additional clusters. This is an example of scaling max because it involves increasing the maximum limit of resources that can be allocated to the Multi-Cluster Warehouse.
Scaling rhythmically, on the other hand, refers to increasing or decreasing resources in a gradual and predictable manner based on the workload of the system. Scaling out involves adding more instances of a system or application to distribute the workload across multiple nodes. Scaling up involves increasing the resources of a single node in order to handle a larger workload.
Correct answer : C
https://docs.snowflake.com/en/user-guide/warehouses-considerations#scaling-up-vs-scaling-out
Snowflake supports two ways to scale warehouses:
1. Scale up by resizing a warehouse.
2. Scale out by adding clusters to a multi-cluster warehouse (requires Snowflake Enterprise Edition or higher).
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