Zephyr Professional Practice Test

What does Z-axis scaling accomplish?

1. Distributes the application across multiple servers

2. Divides application workload among multiple copies

3. Shards data across a set of servers

4. Centralizes all data in one location

The correct answer is: Shards data across a set of servers

Z-axis scaling, also known as scaling out or horizontal scaling, primarily refers to the process of distributing the application workload across multiple servers or instances. It allows for increased performance and capacity by adding more servers rather than enhancing the capabilities of existing ones (which is referred to as vertical scaling). In the context of the given options, sharding data across a set of servers is an effective way to manage large volumes of data and ensure that no single server becomes a bottleneck. By distributing the data, different servers can handle different segments of the data, allowing for improved data access speeds and efficient handling of large datasets, as well as ensuring better fault tolerance. The other choices describe concepts that relate to application architecture and data management but do not accurately capture the essence of z-axis scaling. Distributing applications across multiple servers or dividing application workloads speaks more to the general idea of load balancing or microservices architecture rather than the specific focus on data sharding that z-axis scaling implies. Centralizing all data in one location contradicts the distributed nature of scaling out.