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Cloud Digital Leader Practice Question: Horizontal scaling, and how does it differ from…

What is horizontal scaling, and how does it differ from vertical scaling?

⚠ Common exam trap

The GCDL exam often tests the common misconception that horizontal scaling means adding resources to a single server (like upgrading RAM), when in fact it means adding more servers to share the load.

Answer choices

Why each option matters

Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.

Correct answer & explanation

✓

Horizontal scaling adds more instances to distribute load; vertical scaling increases the size of existing instances.

Horizontal scaling (scale-out) adds more instances (e.g., additional virtual machines or containers) to distribute the workload across multiple nodes, improving fault tolerance and capacity. Vertical scaling (scale-up) increases the resources (CPU, RAM, storage) of an existing instance, often hitting hardware limits and requiring downtime. Option B correctly captures this distinction.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

  • ✗

    Horizontal scaling adds CPU/memory to existing servers; vertical scaling adds more servers.

    Why it's wrong here

    This statement reverses the correct definitions. Horizontal scaling (scaling out) adds more instances, such as VMs or containers, to distribute workload across a pool, while vertical scaling (scaling up) increases the CPU, memory, or disk size of a single existing instance. Therefore, the claim that horizontal adds CPU/memory to existing servers and vertical adds more servers is exactly backwards.

  • ✓

    Horizontal scaling adds more instances to distribute load; vertical scaling increases the size of existing instances.

    Why this is correct

    This is the accurate definition. Horizontal scaling, also known as scaling out, involves adding more instances (e.g., VMs, containers) to a resource pool and using a load balancer to distribute traffic across them, which improves throughput and fault tolerance. Vertical scaling, or scaling up, increases the capacity of an existing instance by adding more CPU, RAM, or storage, but it is limited by the maximum size of a single machine and often requires a restart.

  • ✗

    Horizontal scaling is for databases only; vertical scaling is for web servers.

    Why it's wrong here

    This is a false oversimplification; both scaling approaches apply to any resource type. Web servers commonly scale horizontally by running multiple application instances behind a load balancer, and they can also scale vertically by using a larger VM image. Databases can scale vertically with bigger instances, and horizontally through techniques like sharding, read replicas, and distributed database systems, so neither technique is exclusive to a particular tier.

  • ✗

    Horizontal scaling requires application downtime; vertical scaling is always online.

    Why it's wrong here

    This statement is incorrect on both counts. Horizontal scaling typically adds instances behind a load balancer without requiring downtime, as new instances can be provisioned and begin serving traffic immediately. In contrast, vertical scaling often requires a restart of the VM or instance to apply the new resource allocation, though some managed cloud databases can scale vertically with minimal disruption. Thus, horizontal is not necessarily downtime-prone, and vertical is not always online.

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Written by Johnson Ajibi, MSc IT Security

Senior Network & Security Engineer · founder of Courseiva

This GCDL practice question is part of Courseiva's free Google Cloud certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the GCDL exam.